Erin Mordecai
Associate Professor of Biology and Senior Fellow at the Woods Institute for the Environment
Bio
My research focuses on the ecology of infectious disease. I am interested in how climate, species interactions, and global change drive infectious disease dynamics in humans and natural ecosystems. This research combines mathematical modeling and empirical work.
I finished my PhD in 2012 at the University of California Santa Barbara in Ecology, Evolution, and Marine Biology. I then completed a 2-year NSF postdoctoral research fellowship in the Intersection of Biology and Mathematical and Physical Sciences and Engineering at the University of North Carolina at Chapel Hill and North Carolina State University. I have been at Stanford since January 2015.
Academic Appointments
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Associate Professor, Biology
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Member, Bio-X
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Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
Honors & Awards
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Leading Interdisciplinary Collaborations Fellow, Woods Institute for the Environment, Stanford University (2018-2019)
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Early Career Fellow, Ecological Society of America (2019)
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Walter J. Gores Award for Teaching, Stanford University (2019)
Boards, Advisory Committees, Professional Organizations
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Affiliate, Woods Institute for the Environment (2018 - Present)
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Editorial Advisory Board Member, Lancet Planetary Health (2019 - Present)
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Member, Jasper Ridge Faculty Advisory Committee (2015 - Present)
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Associate Editor, Ecology Letters (2019 - Present)
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Faculty Fellow, Center for Innovation in Global Health (2015 - Present)
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Faculty Fellow, King Center on Global Development (2019 - Present)
Professional Education
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B.S., University of Georgia, Honors Interdisciplinary Studies in Mathematical Biology (2007)
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PhD, University of California Santa Barbara, Ecology, Evolution, and Marine Biology (2012)
Current Research and Scholarly Interests
Our research focuses on the ecology of infectious disease. We are interested in how climate, species interactions, and global change drive infectious disease dynamics in humans and natural ecosystems. This research combines mathematical modeling and empirical work. Our main study systems include vector-borne diseases in humans and fungal pathogens in California grasses.
2024-25 Courses
- Disease Ecology
BIO 176, BIO 276 (Aut) - Ecology and Evolution of Infectious Disease in a Changing World
BIO 2N (Spr) -
Independent Studies (7)
- Directed Reading in Biology
BIO 198 (Aut, Win, Spr) - Directed Reading in Environment and Resources
ENVRES 398 (Aut, Win, Spr) - Directed Research in Environment and Resources
ENVRES 399 (Aut, Win, Spr) - Graduate Research
BIO 300 (Aut, Win, Spr) - Honors Program in Earth Systems
EARTHSYS 199 (Aut, Win, Spr) - Teaching Practicum in Biology
BIO 290 (Aut, Win, Spr) - Undergraduate Research
BIO 199 (Aut, Win, Spr)
- Directed Reading in Biology
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Prior Year Courses
2023-24 Courses
- Introduction to Ecology
BIO 81 (Aut)
2022-23 Courses
2021-22 Courses
- Introduction to Ecology
BIO 81 (Aut)
- Introduction to Ecology
Stanford Advisees
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Samantha Bents -
Doctoral Dissertation Reader (AC)
Magdalena Warren -
Postdoctoral Faculty Sponsor
Jasmine Childress, Mauricio Cruz Loya, Rachel Fay, Caroline Glidden, Daniela de Angeli Dutra -
Doctoral Dissertation Advisor (AC)
Isabel Delwel, Johannah Farner, Desire Nalukwago -
Doctoral Dissertation Co-Advisor (AC)
Emma Krasovich Southworth, Aly Singleton -
Postdoctoral Research Mentor
Jasmine Childress
Graduate and Fellowship Programs
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Biology (School of Humanities and Sciences) (Phd Program)
All Publications
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Molecular epidemiology and evolutionary characteristics of dengue virus 2 in East Africa.
Nature communications
2024; 15 (1): 7832
Abstract
Despite the increasing burden of dengue, the regional emergence of the virus in Kenya has not been examined. This study investigates the genetic structure and regional spread of dengue virus-2 in Kenya. Viral RNA from acutely ill patients in Kenya was enriched and sequenced. Six new dengue-2 genomes were combined with 349 publicly available genomes and phylogenies used to infer gene flow between Kenya and other countries. Analyses indicate two dengue-2 Cosmopolitan genotype lineages circulating in Kenya, linked to recent outbreaks in coastal Kenya and Burkina Faso. Lineages circulating in Western, Southern, and Eastern Africa exhibiting similar evolutionary features are also reported. Phylogeography suggests importation of dengue-2 into Kenya from East and Southeast Asia and bidirectional geneflow. Additional lineages circulating in Africa are also imported from East and Southeast Asia. These findings underscore how intermittent importations from East and Southeast Asia drive dengue-2 circulation in Kenya and Africa more broadly.
View details for DOI 10.1038/s41467-024-51018-0
View details for PubMedID 39244569
View details for PubMedCentralID 3651993
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A flexible model for thermal performance curves.
bioRxiv : the preprint server for biology
2024
Abstract
Temperature responses of many biological traits-including population growth, survival, and development-are described by thermal performance curves (TPCs) with phenomenological models like the Briere function or mechanistic models related to chemical kinetics. Existing TPC models are either simple but inflexible in shape, or flexible yet difficult to interpret in biological terms. Here we present flexTPC: a model that is parameterized exclusively in terms of biologically interpretable quantities, including the thermal minimum, optimum, and maximum, and the maximum trait value. FlexTPC can describe unimodal temperature responses of any skewness and thermal breadth, enabling direct comparisons across populations, traits, or taxa with a single model. We apply flexTPC to various microbial and entomological datasets, compare results with the Briere model, and find that flexTPC often has better predictive performance. The interpretability of flexTPC makes it ideal for modeling how thermal responses change with ecological stressors or evolve over time.
View details for DOI 10.1101/2024.08.01.605695
View details for PubMedID 39149255
View details for PubMedCentralID PMC11326125
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A Mosquito Parasite Is Locally Adapted to Its Host but Not Temperature
AMERICAN NATURALIST
2024
View details for DOI 10.1086/730522
View details for Web of Science ID 001250675000001
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Plasticity in mosquito size and thermal tolerance across a latitudinal climate gradient.
The Journal of animal ecology
2024
Abstract
Variation in heat tolerance among populations can determine whether a species is able to cope with ongoing climate change. Such variation may be especially important for ectotherms whose body temperatures, and consequently, physiological processes, are regulated by external conditions. Additionally, differences in body size are often associated with latitudinal clines, thought to be driven by climate gradients. While studies have begun to explore variation in body size and heat tolerance within species, our understanding of these patterns across large spatial scales, particularly regarding the roles of plasticity and genetic differences, remains incomplete. Here, we examine body size, as measured by wing length, and thermal tolerance, as measured by the time to immobilisation at high temperatures ("thermal knockdown"), in populations of the mosquito Aedes sierrensis collected from across a large latitudinal climate gradient spanning 1300 km (34-44° N). We find that mosquitoes collected from lower latitudes and warmer climates were more tolerant of high temperatures than those collected from higher latitudes and colder climates. Moreover, body size increased with latitude and decreased with temperature, a pattern consistent with James' rule, which appears to be a result of plasticity rather than genetic variation. Our results suggest that warmer environments produce smaller and more thermally tolerant populations.
View details for DOI 10.1111/1365-2656.14149
View details for PubMedID 39030760
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Population-specific thermal responses contribute to regional variability in arbovirus transmission with changing climates.
iScience
2024; 27 (6): 109934
Abstract
Temperature is increasing globally, and vector-borne diseases are particularly responsive to such increases. While it is known that temperature influences mosquito life history traits, transmission models have not historically considered population-specific effects of temperature. We assessed the interaction between Culex pipiens population and temperature in New York State (NYS) and utilized novel empirical data to inform predictive models of West Nile virus (WNV) transmission. Genetically and regionally distinct populations from NYS were reared at various temperatures, and life history traits were monitored and used to inform trait-based models. Variation in Cx. pipiens life history traits and population-dependent thermal responses account for a predicted 2.9°C difference in peak transmission that is reflected in regional differences in WNV prevalence. We additionally identified genetic signatures that may contribute to distinct thermal responses. Together, these data demonstrate how population variation contributes to significant geographic variability in arbovirus transmission with changing climates.
View details for DOI 10.1016/j.isci.2024.109934
View details for PubMedID 38799579
View details for PubMedCentralID PMC11126822
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Climate and urbanization drive changes in the habitat suitability of Schistosoma mansoni competent snails in Brazil.
Nature communications
2024; 15 (1): 4838
Abstract
Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria and Bulinus snails, thus controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we used machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of forward-transmitting Biomphalaria hosts throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution-while accounting for non-linearities that are difficult to detect from local case studies-can help inform schistosomiasis control strategies.
View details for DOI 10.1038/s41467-024-48335-9
View details for PubMedID 38898012
View details for PubMedCentralID PMC11186836
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Re-assessing thermal response of schistosomiasis transmission risk: Evidence for a higher thermal optimum than previously predicted.
PLoS neglected tropical diseases
2024; 18 (6): e0011836
Abstract
The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7°C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3°C and 23.6-27.9°C (95% CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.
View details for DOI 10.1371/journal.pntd.0011836
View details for PubMedID 38857289
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Investigating the Yanomami malaria outbreak puzzle: surge in mining during Bolsonaro's government triggered peak in malaria burden.
Research square
2024
Abstract
The Yanomami, an Indigenous people from the Amazon, confront multifaceted challenges endangering their health and cultural integrity. Of immediate concern is the surge in malaria cases in their territory during Bolsonaro's government. We investigated the impact of land use on malaria incidence among the Yanomami leveraging satellite imagery and ran difference-in-differences analyses to ask whether the Yanomami suffered disproportionately from malaria when illegal mining was rising in the region (2016-2022). We show a remarkable ~300% rise in malaria from 2016 to 2022 and point to mining as the primary driver of malaria among the Yanomami; when mining increases by 1%, malaria increases by 31%. After mining unfolded, the burden of malaria among the Yanomami was disproportionately higher, up to 15%, than in non-indigenous communities. Our findings underscore the impact of illegal mining on the high malaria burden suffered by the Yanomami and the importance of rainforest conservation and land sovereignty for Indigenous health.
View details for DOI 10.21203/rs.3.rs-4313946/v1
View details for PubMedID 38746301
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Interconnecting global threats: climate change, biodiversity loss, and infectious diseases.
The Lancet. Planetary health
2024; 8 (4): e270-e283
Abstract
The concurrent pressures of rising global temperatures, rates and incidence of species decline, and emergence of infectious diseases represent an unprecedented planetary crisis. Intergovernmental reports have drawn focus to the escalating climate and biodiversity crises and the connections between them, but interactions among all three pressures have been largely overlooked. Non-linearities and dampening and reinforcing interactions among pressures make considering interconnections essential to anticipating planetary challenges. In this Review, we define and exemplify the causal pathways that link the three global pressures of climate change, biodiversity loss, and infectious disease. A literature assessment and case studies show that the mechanisms between certain pairs of pressures are better understood than others and that the full triad of interactions is rarely considered. Although challenges to evaluating these interactions-including a mismatch in scales, data availability, and methods-are substantial, current approaches would benefit from expanding scientific cultures to embrace interdisciplinarity and from integrating animal, human, and environmental perspectives. Considering the full suite of connections would be transformative for planetary health by identifying potential for co-benefits and mutually beneficial scenarios, and highlighting where a narrow focus on solutions to one pressure might aggravate another.
View details for DOI 10.1016/S2542-5196(24)00021-4
View details for PubMedID 38580428
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Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape.
Research square
2024
Abstract
Land use change drives both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting countryside biodiversity, public health, and livelihoods requires understanding the scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. Evidence increasingly shows that species richness for many taxa correlates with local tree cover.We investigated whether mosquito species richness, community composition, and presence of disease vector species responded to land use and tree cover - and if so, whether at spatial scales similar to other taxa.We paired a field survey of mosquito communities in agricultural, residential, and forested lands in rural southern Costa Rica with remotely sensed tree cover data. We compared mosquito community responses to tree cover surrounding survey sites measured across scales, and analyzed community responses to land use and environmental gradients.Tree cover was positively correlated with mosquito species richness, and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus, particularly at small spatial scales of 80 - 200m. Land use predicted community composition and Ae. albopictus presence. Environmental gradients of tree cover, temperature, and elevation explained 7% of species turnover among survey sites.The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa, including arthropods, and also confer protection against disease vector occurrence. The identified spatial range of tree cover benefits can inform land management for conservation and public health protection.
View details for DOI 10.21203/rs.3.rs-3954302/v1
View details for PubMedID 38464276
View details for PubMedCentralID PMC10925468
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Perceived experts are prevalent and influential within an antivaccine community on Twitter.
PNAS nexus
2024; 3 (2): pgae007
Abstract
Perceived experts (i.e. medical professionals and biomedical scientists) are trusted sources of medical information who are especially effective at encouraging vaccine uptake. The role of perceived experts acting as potential antivaccine influencers has not been characterized systematically. We describe the prevalence and importance of antivaccine perceived experts by constructing a coengagement network of 7,720 accounts based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the antivaccine community. Perceived experts had a sizable presence across the coengagement network, including within the antivaccine community where they were 9.8% of individual, English-language users. Perceived experts within the antivaccine community shared low-quality (misinformation) sources at similar rates and academic sources at higher rates compared to perceived nonexperts in that community. Perceived experts occupied important network positions as central antivaccine users and bridges between the antivaccine and provaccine communities. Using propensity score matching, we found that perceived expertise brought an influence boost, as perceived experts were significantly more likely to receive likes and retweets in both the antivaccine and provaccine communities. There was no significant difference in the magnitude of the influence boost for perceived experts between the two communities. Social media platforms, scientific communications, and biomedical organizations may focus on more systemic interventions to reduce the impact of perceived experts in spreading antivaccine misinformation.
View details for DOI 10.1093/pnasnexus/pgae007
View details for PubMedID 38328781
View details for PubMedCentralID PMC10847722
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Mosquito thermal tolerance is remarkably constrained across a large climatic range.
Proceedings. Biological sciences
2024; 291 (2015): 20232457
Abstract
How mosquitoes may respond to rapid climate warming remains unknown for most species, but will have major consequences for their future distributions, with cascading impacts on human well-being, biodiversity and ecosystem function. We investigated the adaptive potential of a wide-ranging mosquito species, Aedes sierrensis, across a large climatic gradient by conducting a common garden experiment measuring the thermal limits of mosquito life-history traits. Although field-collected populations originated from vastly different thermal environments that spanned over 1200 km, we found limited variation in upper thermal tolerance between populations. In particular, the upper thermal limits of all life-history traits varied by less than 3°C across the species range and, for most traits, did not differ significantly between populations. For one life-history trait-pupal development rate-we did detect significant variation in upper thermal limits between populations, and this variation was strongly correlated with source temperatures, providing evidence of local thermal adaptation for pupal development. However, we found that maximum environmental temperatures across most of the species' range already regularly exceed the highest upper thermal limits estimated under constant temperatures. This result suggests that strategies for coping with and/or avoiding thermal extremes are likely key components of current and future mosquito thermal tolerance.
View details for DOI 10.1098/rspb.2023.2457
View details for PubMedID 38264779
View details for PubMedCentralID PMC10806440
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High prevalence of Zika virus infection in populations of Aedes aegypti from South-western Ecuador.
PLoS neglected tropical diseases
2024; 18 (1): e0011908
Abstract
We performed an arboviral survey in mosquitoes from four endemic Ecuadorian cities (Huaquillas, Machala, Portovelo and Zaruma) during the epidemic period 2016-2018. Collections were performed during the pre-rainy season (2016), peak transmission season (2017) and post-rainy season (2018). Ae. aegypti mosquitoes were pooled by date, location and sex. Pools were screened by RT-PCR for the presence of ZIKV RNA, and infection rates (IRs) per 1,000 specimens were calculated. A total of 2,592 pools (comprising 6,197 mosquitoes) were screened. Our results reveal high IRs in all cities and periods sampled. Overall IRs among female mosquitoes were highest in Machala (89.2), followed by Portovelo (66.4), Zaruma (47.4) and Huaquillas (41.9). Among male mosquitoes, overall IRs were highest in Machala (35.6), followed by Portovelo (33.1), Huaquillas (31.9) and Zaruma (27.9), suggesting that alternative transmission routes (vertical/venereal) can play important roles for ZIKV maintenance in the vector population of these areas. Additionally, we propose that the stabilization of ZIKV vertical transmission in the vector population could help explain the presence of high IRs in field-caught mosquitoes during inter-epidemic periods.
View details for DOI 10.1371/journal.pntd.0011908
View details for PubMedID 38236943
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Non-household environments make a major contribution to dengue transmission: Implications for vector control.
medRxiv : the preprint server for health sciences
2024
Abstract
Aedes-borne pathogens have been increasing in incidence in recent decades despite vector control activities implemented in endemic settings. Vector control for Aedes-transmitted arboviruses typically focuses on households because vectors breed in household containers and bite indoors. Yet, our recent work shows a high abundance of Aedes spp. vectors in public spaces. To investigate the impact of non-household environments on dengue transmission and control, we used field data on the number of water containers and abundance of Aedes mosquitoes in Household (HH) and Non-Household (NH) environments in two Kenyan cities, Kisumu and Ukunda, from 2019-2022. Incorporating information on human activity space, we developed an agent-based model to simulate city-wide conditions considering HH and five types of NH environments in which people move and interact with other humans and vectors during peak biting times. We additionally evaluated the outcome of vector control activities implemented in different environments in preventive (before an epidemic) and reactive (after an epidemic commences) scenarios. We estimated that over half of infections take place in NH environments, where the main spaces for transmission are workplaces, markets, and recreational locations. Accordingly, results highlight the important role of vector control activities at NH locations to reduce dengue. A greater reduction of cases is expected as control activities are implemented earlier, at higher levels of coverage, with greater effectiveness when targeting only NH as opposed to when targeting only HH. Further, local ecological factors such as the differential abundance of water containers within cities are also influential factors to consider for control. This work provides insight into the importance of vector control in both household and non-household environments in endemic settings. It highlights a specific approach to inform evidence-based decision making to target limited vector control resources for optimal control.
View details for DOI 10.1101/2024.01.08.24301016
View details for PubMedID 38260355
View details for PubMedCentralID PMC10802645
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Climate warming is expanding dengue burden in the Americas and Asia.
medRxiv : the preprint server for health sciences
2024
Abstract
Climate change poses significant threats to public health, with dengue representing a growing concern due to its high existing burden and sensitivity to climatic conditions. Yet, the quantitative impacts of temperature warming on dengue, both in the past and in the future, remain poorly understood. In this study, we quantify how dengue responds to climatic fluctuations, and use this inferred temperature response to estimate the impacts of historical warming and forecast trends under future climate change scenarios. To estimate the causal impact of temperature on the spread of dengue in the Americas and Asia, we assembled a dataset encompassing nearly 1.5 million dengue incidence records from 21 countries. Our analysis revealed a nonlinear relationship between temperature and dengue incidence with the largest marginal effects at lower temperatures (around 15°C), peak incidence at 27.8°C (95% CI: 27.3 - 28.2°C), and subsequent declines at higher temperatures. Our findings indicate that historical climate change has already increased dengue incidence 18% (12 - 25%) in the study region, and projections suggest a potential increase of 40% (17 - 76) to 57% (33 - 107%) by mid-century depending on the climate scenario, with some areas seeing up to 200% increases. Notably, our models suggest that lower emissions scenarios would substantially reduce the warming-driven increase in dengue burden. Together, these insights contribute to the broader understanding of how long-term climate patterns influence dengue, providing a valuable foundation for public health planning and the development of strategies to mitigate future risks due to climate change.
View details for DOI 10.1101/2024.01.08.24301015
View details for PubMedID 38260629
View details for PubMedCentralID PMC10802639
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Species distribution modeling for disease ecology: A multi-scale case study for schistosomiasis host snails in Brazil.
PLOS global public health
2024; 4 (8): e0002224
Abstract
Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis is transmitted to humans through contact with the free-living infectious stage of Schistosoma spp. parasites released from freshwater snails, the parasite's obligate intermediate hosts. In this study, we compared snail SDM performance across machine learning (ML) approaches (MaxEnt, Random Forest, and Boosted Regression Trees), geographic extents (national, regional, and state), types of presence data (expert-collected and publicly-available), and snail species (Biomphalaria glabrata, B. straminea, and B. tenagophila). We used high-resolution (1km) climate, hydrology, land-use/land-cover (LULC), and soil property data to describe the snails' ecological niche and evaluated models on multiple criteria. Although all ML approaches produced comparable spatially cross-validated performance metrics, their suitability maps showed major qualitative differences that required validation based on local expert knowledge. Additionally, our findings revealed varying importance of LULC and bioclimatic variables for different snail species at different spatial scales. Finally, we found that models using publicly-available data predicted snail distribution with comparable AUC values to models using expert-collected data. This work serves as an instructional guide to SDM methods that can be applied to a range of vector-borne and zoonotic diseases. In addition, it advances our understanding of the relevant environment and bioclimatic determinants of schistosomiasis risk in Brazil.
View details for DOI 10.1371/journal.pgph.0002224
View details for PubMedID 39093879
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Temperature dependence of mosquitoes: comparing mechanistic and machine learning approaches.
bioRxiv : the preprint server for biology
2023
Abstract
Mosquito vectors of pathogens (e.g., Aedes , Anopheles , and Culex spp. which transmit dengue, Zika, chikungunya, West Nile, malaria, and others) are of increasing concern for global public health. These vectors are geographically shifting under climate and other anthropogenic changes. As small-bodied ectotherms, mosquitoes are strongly affected by temperature, which causes unimodal responses in mosquito life history traits (e.g., biting rate, adult mortality rate, mosquito development rate, and probability of egg-to-adult survival) that exhibit upper and lower thermal limits and intermediate thermal optima in laboratory studies. However, it remains unknown how mosquito thermal responses measured in laboratory experiments relate to the realized thermal responses of mosquitoes in the field. To address this gap, we leverage thousands of global mosquito occurrences and geospatial satellite data at high spatial resolution to construct machine-learning based species distribution models, from which vector thermal responses are estimated. We apply methods to restrict models to the relevant mosquito activity season and to conduct ecologically-plausible spatial background sampling centered around ecoregions for comparison to mosquito occurrence records. We found that thermal minima estimated from laboratory studies were highly correlated with those from the species distributions (r = 0.90). The thermal optima were less strongly correlated (r = 0.69). For most species, we did not detect thermal maxima from their observed distributions so were unable to compare to laboratory-based estimates. The results suggest that laboratory studies have the potential to be highly transportable to predicting lower thermal limits and thermal optima of mosquitoes in the field. At the same time, lab-based models likely capture physiological limits on mosquito persistence at high temperatures that are not apparent from field-based observational studies but may critically determine mosquito responses to climate warming.
View details for DOI 10.1101/2023.12.04.569955
View details for PubMedID 38105988
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Local tree cover predicts mosquito species richness and disease vector presence in a tropical countryside landscape.
bioRxiv : the preprint server for biology
2023
Abstract
Land use change is an important driver of both biodiversity loss and zoonotic disease transmission in tropical countryside landscapes. Developing solutions for protecting biodiversity, public health, and livelihoods in working landscapes requires understanding the spatial scales at which habitat characteristics such as land cover shape biodiversity, especially for arthropods that transmit pathogens. A growing body of evidence shows that species richness for many taxa correlates with tree cover at small spatial scales of <100 m, indicating that local tree cover management is a promising conservation tool. To investigate whether mosquito species richness, community composition, and presence of specific disease vector species respond to tree cover- and if so, whether at spatial scales similar to other taxa-we surveyed mosquito communities along a tree cover gradient and across agricultural, residential, and forested land uses in rural southern Costa Rica. We found that tree cover was both positively correlated with mosquito species richness and negatively correlated with the presence of the common invasive dengue vector Aedes albopictus , particularly at small spatial scales of 80 - 200m. Beyond tree cover, land use type predicted community composition and Ae. albopictus presence, but not species richness. The results suggest that preservation and expansion of tree cover at local scales can protect biodiversity for a wide range of taxa and also confer protection against disease vector occurrence.
View details for DOI 10.1101/2023.12.05.570170
View details for PubMedID 38105954
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Tackling climate change and deforestation to protect against vector-borne diseases.
Nature microbiology
2023; 8 (12): 2220-2222
View details for DOI 10.1038/s41564-023-01533-5
View details for PubMedID 38030900
View details for PubMedCentralID 6744319
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Temperature and intraspecific variation affect host-parasite interactions.
Oecologia
2023
Abstract
Parasites play key roles in regulating aquatic ecosystems, yet the impact of climate warming on their ecology and disease transmission remains poorly understood. Isolating the effect of warming is challenging as transmission involves multiple interacting species and potential intraspecific variation in temperature responses of one or more of these species. Here, we leverage a wide-ranging mosquito species and its facultative parasite as a model system to investigate the impact of temperature on host-parasite interactions and disease transmission. We conducted a common garden experiment measuring parasite growth and infection rates at seven temperatures using 12 field-collected parasite populations and a single mosquito population. We find that both free-living growth rates and infection rates varied with temperature, which were highest at 18-24.5°C and 13°C, respectively. Further, we find intraspecific variation in peak performance temperature reflecting patterns of local thermal adaptation-parasite populations from warmer source environments typically had higher thermal optima for free-living growth rates. For infection rates, we found a significant interaction between parasite population and nonlinear effects of temperature. These findings underscore the need to consider both host and parasite thermal responses, as well as intraspecific variation in thermal responses, when predicting the impacts of climate change on disease in aquatic ecosystems.
View details for DOI 10.1007/s00442-023-05481-z
View details for PubMedID 38006450
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Mosquito thermal tolerance is remarkably constrained across a large climatic range.
bioRxiv : the preprint server for biology
2023
Abstract
How mosquitoes may respond to rapid climate warming remains unknown for most species, but will have major consequences for their future distributions, with cascading impacts on human well-being, biodiversity, and ecosystem function. We investigated the adaptive potential of a wide-ranging mosquito species, Aedes sierrensis, across a large climatic gradient by conducting a common garden experiment measuring the thermal limits of mosquito life history traits. Although field-collected populations originated from vastly different thermal environments that spanned over 1,200 km, we found remarkably limited variation in upper thermal tolerance between populations, with the upper thermal limits of fitness varying by <1°C across the species range. For one life history trait-pupal development rate-we did detect significant variation in upper thermal limits between populations, and this variation was strongly correlated with source temperatures, providing evidence of local thermal adaptation for pupal development. However, we found environmental temperatures already regularly exceed our highest estimated upper thermal limits throughout most of the species range, suggesting limited potential for mosquito thermal tolerance to evolve on pace with warming. Strategies for avoiding high temperatures such as diapause, phenological shifts, and behavioral thermoregulation are likely important for mosquito persistence.
View details for DOI 10.1101/2023.03.02.530886
View details for PubMedID 37961581
View details for PubMedCentralID PMC10634975
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A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.
BMC infectious diseases
2023; 23 (1): 708
Abstract
Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used.We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.).We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures.Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping.
View details for DOI 10.1186/s12879-023-08717-8
View details for PubMedID 37864153
View details for PubMedCentralID 7004335
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Temperature and intraspecific variation affect host-parasite interactions.
bioRxiv : the preprint server for biology
2023
Abstract
Parasites play key roles in regulating aquatic ecosystems, yet the impact of climate warming on their ecology and disease transmission remains poorly understood. Isolating the effect of warming is challenging as transmission involves multiple interacting species and potential intraspecific variation in temperature responses of one or more of these species. Here, we leverage a wide-ranging mosquito species and its facultative parasite as a model system to investigate the impact of temperature on host-parasite interactions and disease transmission. We conducted a common garden experiment measuring parasite growth and infection rates at seven temperatures using 12 field-collected parasite populations and a single mosquito population. We find that both free-living growth rates and infection rates varied with temperature, which were highest at 18-24.5°C and 13°C, respectively. Further, we find intraspecific variation in peak performance temperature reflecting patterns of local thermal adaptation-parasite populations from warmer source environments typically had higher thermal optima for free-living growth rates. For infection rates, we found a significant interaction between parasite population and nonlinear effects of temperature. These findings underscore the need to consider both host and parasite thermal responses, as well as intraspecific variation in thermal responses, when predicting the impacts of climate change on disease in aquatic ecosystems.
View details for DOI 10.1101/2023.08.24.554680
View details for PubMedID 37662401
View details for PubMedCentralID PMC10473705
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The Importance of Including Non-Household Environments in Dengue Vector Control Activities.
Viruses
2023; 15 (7)
Abstract
Most vector control activities in urban areas are focused on household environments; however, information relating to infection risks in spaces other than households is poor, and the relative risk that these spaces represent has not yet been fully understood. We used data-driven simulations to investigate the importance of household and non-household environments for dengue entomological risk in two Kenyan cities where dengue circulation has been reported. Fieldwork was performed using four strategies that targeted different stages of mosquitoes: ovitraps, larval collections, Prokopack aspiration, and BG-sentinel traps. Data were analyzed separately between household and non-household environments to assess mosquito presence, the number of vectors collected, and the risk factors for vector presence. With these data, we simulated vector and human populations to estimate the parameter m and mosquito-to-human density in both household and non-household environments. Among the analyzed variables, the main difference was found in mosquito abundance, which was consistently higher in non-household environments in Kisumu but was similar in Ukunda. Risk factor analysis suggests that small, clean water-related containers serve as mosquito breeding places in households as opposed to the trash- and rainfall-related containers found in non-household structures. We found that the density of vectors (m) was higher in non-household than household environments in Kisumu and was also similar or slightly lower between both environments in Ukunda. These results suggest that because vectors are abundant, there is a potential risk of transmission in non-household environments; hence, vector control activities should take these spaces into account.
View details for DOI 10.3390/v15071550
View details for PubMedID 37515236
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The role and influence of perceived experts in an anti-vaccine misinformation community.
medRxiv : the preprint server for health sciences
2023
Abstract
The role of perceived experts (i.e., medical professionals and biomedical scientists) as potential anti-vaccine influencers has not been characterized systematically. We describe the prevalence and importance of anti-vaccine perceived experts by constructing a coengagement network based on a Twitter data set containing over 4.2 million posts from April 2021. The coengagement network primarily broke into two large communities that differed in their stance toward COVID-19 vaccines, and misinformation was predominantly shared by the anti-vaccine community. Perceived experts had a sizable presence within the anti-vaccine community and shared academic sources at higher rates compared to others in that community. Perceived experts occupied important network positions as central anti-vaccine nodes and bridges between the anti- and pro-vaccine communities. Perceived experts received significantly more engagements than other individuals within the anti- and pro-vaccine communities and there was no significant difference in the influence boost for perceived experts between the two communities. Interventions designed to reduce the impact of perceived experts who spread anti-vaccine misinformation may be warranted.
View details for DOI 10.1101/2023.07.12.23292568
View details for PubMedID 37546922
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Human footprint is associated with shifts in the assemblages of major vector-borne diseases.
Nature sustainability
2023; 6 (6): 652-661
Abstract
Predicting how increasing intensity of human-environment interactions affects pathogen transmission is essential to anticipate changing disease risks and identify appropriate mitigation strategies. Vector-borne diseases (VBDs) are highly responsive to environmental changes, but such responses are notoriously difficult to isolate because pathogen transmission depends on a suite of ecological and social responses in vectors and hosts that may differ across species. Here we use the emerging tools of cumulative pressure mapping and machine learning to better understand how the occurrence of six medically important VBDs, differing in ecology from sylvatic to urban, respond to multidimensional effects of human pressure. We find that not only is human footprint-an index of human pressure, incorporating built environments, energy and transportation infrastructure, agricultural lands and human population density-an important predictor of VBD occurrence, but there are clear thresholds governing the occurrence of different VBDs. Across a spectrum of human pressure, diseases associated with lower human pressure, including malaria, cutaneous leishmaniasis and visceral leishmaniasis, give way to diseases associated with high human pressure, such as dengue, chikungunya and Zika. These heterogeneous responses of VBDs to human pressure highlight thresholds of land-use transitions that may lead to abrupt shifts in infectious disease burdens and public health needs.
View details for DOI 10.1038/s41893-023-01080-1
View details for PubMedID 37538395
View details for PubMedCentralID PMC10399301
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Phylogenetic and biogeographical traits predict unrecognized hosts of zoonotic leishmaniasis.
PLoS neglected tropical diseases
2023; 17 (5): e0010879
Abstract
The spatio-temporal distribution of leishmaniasis, a parasitic vector-borne zoonotic disease, is significantly impacted by land-use change and climate warming in the Americas. However, predicting and containing outbreaks is challenging as the zoonotic Leishmania system is highly complex: leishmaniasis (visceral, cutaneous and muco-cutaneous) in humans is caused by up to 14 different Leishmania species, and the parasite is transmitted by dozens of sandfly species and is known to infect almost twice as many wildlife species. Despite the already broad known host range, new hosts are discovered almost annually and Leishmania transmission to humans occurs in absence of a known host. As such, the full range of Leishmania hosts is undetermined, inhibiting the use of ecological interventions to limit pathogen spread and the ability to accurately predict the impact of global change on disease risk. Here, we employed a machine learning approach to generate trait profiles of known zoonotic Leishmania wildlife hosts (mammals that are naturally exposed and susceptible to infection) and used trait-profiles of known hosts to identify potentially unrecognized hosts. We found that biogeography, phylogenetic distance, and study effort best predicted Leishmania host status. Traits associated with global change, such as agricultural land-cover, urban land-cover, and climate, were among the top predictors of host status. Most notably, our analysis suggested that zoonotic Leishmania hosts are significantly undersampled, as our model predicted just as many unrecognized hosts as unknown hosts. Overall, our analysis facilitates targeted surveillance strategies and improved understanding of the impact of environmental change on local transmission cycles.
View details for DOI 10.1371/journal.pntd.0010879
View details for PubMedID 37256857
View details for PubMedCentralID PMC10231829
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A mosquito parasite is locally adapted to its host but not temperature.
bioRxiv : the preprint server for biology
2023
Abstract
Climate change will alter interactions between parasites and their hosts. Warming may affect patterns of local adaptation, shifting the environment to favor the parasite or host and thus changing the prevalence of disease. We assessed local adaptation in the facultative ciliate parasite Lambornella clarki, which infects the western tree hole mosquito Aedes sierrensis. We conducted laboratory infection experiments with mosquito larvae and parasites collected from across a climate gradient, pairing sympatric or allopatric populations across three temperatures that were either matched or mismatched to the source environment. L. clarki parasites were locally adapted to their hosts, with 2.6x higher infection rates on sympatric compared to allopatric populations, but were not locally adapted to temperature. Infection peaked at the intermediate temperature of 13°C. Our results highlight the importance of host selective pressure on parasites, despite the impact of temperature on infection success.
View details for DOI 10.1101/2023.04.21.537840
View details for PubMedID 37131754
View details for PubMedCentralID PMC10153241
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Human footprint is associated with shifts in the assemblages of major vector-borne diseases
NATURE SUSTAINABILITY
2023
View details for DOI 10.1038/s41893-023-01080-1
View details for Web of Science ID 000948642200003
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Social divisions and risk perception drive divergent epidemics and large later waves
EVOLUTIONARY HUMAN SCIENCES
2023; 5
View details for DOI 10.1017/ehs.2023.2
View details for Web of Science ID 000943031500001
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Social divisions and risk perception drive divergent epidemics and large later waves.
Evolutionary human sciences
2023; 5: e8
Abstract
During infectious disease outbreaks, individuals may adopt protective measures like vaccination and physical distancing in response to awareness of disease burden. Prior work showed how feedbacks between epidemic intensity and awareness-based behaviour shape disease dynamics. These models often overlook social divisions, where population subgroups may be disproportionately impacted by a disease and more responsive to the effects of disease within their group. We develop a compartmental model of disease transmission and awareness-based protective behaviour in a population split into two groups to explore the impacts of awareness separation (relatively greater in- vs. out-group awareness of epidemic severity) and mixing separation (relatively greater in- vs. out-group contact rates). Using simulations, we show that groups that are more separated in awareness have smaller differences in mortality. Fatigue (i.e. abandonment of protective measures over time) can drive additional infection waves that can even exceed the size of the initial wave, particularly if uniform awareness drives early protection in one group, leaving that group largely susceptible to future infection. Counterintuitively, vaccine or infection-acquired immunity that is more protective against transmission and mortality may indirectly lead to more infections by reducing perceived risk of infection and therefore vaccine uptake. Awareness-based protective behaviour, including awareness separation, can fundamentally alter disease dynamics. Social media summary: Depending on group division, behaviour based on perceived risk can change epidemic dynamics & produce large later waves.
View details for DOI 10.1017/ehs.2023.2
View details for PubMedID 37587926
View details for PubMedCentralID PMC10426078
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Data-driven predictions of potential Leishmania vectors in the Americas.
PLoS neglected tropical diseases
2023; 17 (2): e0010749
Abstract
The incidence of vector-borne diseases is rising as deforestation, climate change, and globalization bring humans in contact with arthropods that can transmit pathogens. In particular, incidence of American Cutaneous Leishmaniasis (ACL), a disease caused by parasites transmitted by sandflies, is increasing as previously intact habitats are cleared for agriculture and urban areas, potentially bringing people into contact with vectors and reservoir hosts. Previous evidence has identified dozens of sandfly species that have been infected with and/or transmit Leishmania parasites. However, there is an incomplete understanding of which sandfly species transmit the parasite, complicating efforts to limit disease spread. Here, we apply machine learning models (boosted regression trees) to leverage biological and geographical traits of known sandfly vectors to predict potential vectors. Additionally, we generate trait profiles of confirmed vectors and identify important factors in transmission. Our model performed well with an average out of sample accuracy of 86%. The models predict that synanthropic sandflies living in areas with greater canopy height, less human modification, and within an optimal range of rainfall are more likely to be Leishmania vectors. We also observed that generalist sandflies that are able to inhabit many different ecoregions are more likely to transmit the parasites. Our results suggest that Psychodopygus amazonensis and Nyssomia antunesi are unidentified potential vectors, and should be the focus of sampling and research efforts. Overall, we found that our machine learning approach provides valuable information for Leishmania surveillance and management in an otherwise complex and data sparse system.
View details for DOI 10.1371/journal.pntd.0010749
View details for PubMedID 36809249
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Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction.
Parasites & vectors
2023; 16 (1): 11
Abstract
West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement.We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill.Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill.Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases).
View details for DOI 10.1186/s13071-022-05630-y
View details for PubMedID 36635782
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Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: a global analysis
LANCET PLANETARY HEALTH
2022; 6 (11): E870-E879
View details for Web of Science ID 000960726200008
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Ecological drivers of dog heartworm transmission in California.
Parasites & vectors
2022; 15 (1): 388
Abstract
BACKGROUND: Effectively controlling heartworm disease-a major parasitic disease threatening animal health in the US and globally-requires understanding the local ecology of mosquito vectors involved in transmission. However, the key vector species in a given region are often unknown and challenging to identify. Here we investigate (i) the key vector species associated with transmission of the parasite, Dirofilaria immitis, in California and (ii) the climate and land cover drivers of vector presence.METHODS: To identify key mosquito vectors involved in transmission, we incorporated long-term, finely resolved mosquito surveillance data and dog heartworm case data in a statistical modeling approach (fixed-effects regression) that rigorously controls for other unobserved drivers of heartworm cases. We then used a flexible machine learning approach (gradient boosted machines) to identify the climate and land cover variables associated with the presence of each species.RESULTS: We found significant, regionally specific, positive associations between dog heartworm cases and the abundance of four vector species: Aedes aegypti (Central California), Ae. albopictus (Southern California), Ae. sierrensis (Central California), and Culiseta incidens (Northern and Central California). The proportion of developed land cover was one of the most important ecological variables predicting the presence or absence of the putative vector species.CONCLUSION: Our results implicate three previously under-recognized vectors of dog heartworm transmission in California and indicate the land cover types in which each putative vector species is commonly found. Efforts to target these species could prioritize surveillance in these land cover types (e.g. near human dwellings in less urbanized settings for Ae. albopictus and Cs. incidens) but further investigation on the natural infection prevalence and host-biting rates of these species, as well as the other local vectors, is needed.
View details for DOI 10.1186/s13071-022-05526-x
View details for PubMedID 36274157
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Not all mosquitoes are created equal: A synthesis of vector competence experiments reinforces virus associations of Australian mosquitoes.
PLoS neglected tropical diseases
2022; 16 (10): e0010768
Abstract
The globalization of mosquito-borne arboviral diseases has placed more than half of the human population at risk. Understanding arbovirus ecology, including the role individual mosquito species play in virus transmission cycles, is critical for limiting disease. Canonical virus-vector groupings, such as Aedes- or Culex-associated flaviviruses, have historically been defined using virus detection in field-collected mosquitoes, mosquito feeding patterns, and vector competence, which quantifies the intrinsic ability of a mosquito to become infected with and transmit a virus during a subsequent blood feed. Herein, we quantitatively synthesize data from 68 laboratory-based vector competence studies of 111 mosquito-virus pairings of Australian mosquito species and viruses of public health concern to further substantiate existing canonical vector-virus groupings and quantify variation within these groupings. Our synthesis reinforces current canonical vector-virus groupings but reveals substantial variation within them. While Aedes species were generally the most competent vectors of canonical "Aedes-associated flaviviruses" (such as dengue, Zika, and yellow fever viruses), there are some notable exceptions; for example, Aedes notoscriptus is an incompetent vector of dengue viruses. Culex spp. were the most competent vectors of many traditionally Culex-associated flaviviruses including West Nile, Japanese encephalitis and Murray Valley encephalitis viruses, although some Aedes spp. are also moderately competent vectors of these viruses. Conversely, many different mosquito genera were associated with the transmission of the arthritogenic alphaviruses, Ross River, Barmah Forest, and chikungunya viruses. We also confirm that vector competence is impacted by multiple barriers to infection and transmission within the mesenteron and salivary glands of the mosquito. Although these barriers represent important bottlenecks, species that were susceptible to infection with a virus were often likely to transmit it. Importantly, this synthesis provides essential information on what species need to be targeted in mosquito control programs.
View details for DOI 10.1371/journal.pntd.0010768
View details for PubMedID 36194577
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Global Change and Emerging Infectious Diseases.
Annual review of resource economics
2022; 14: 333-354
Abstract
Our world is undergoing rapid planetary changes driven by human activities, often mediated by economic incentives and resource management, affecting all life on Earth. Concurrently, many infectious diseases have recently emerged or spread into new populations. Mounting evidence suggests that global change-including climate change, land-use change, urbanization, and global movement of individuals, species, and goods-may be accelerating disease emergence by reshaping ecological systems in concert with socioeconomic factors. Here, we review insights, approaches, and mechanisms by which global change drives disease emergence from a disease ecology perspective. We aim to spur more interdisciplinary collaboration with economists and identification of more effective and sustainable interventions to prevent disease emergence. While almost all infectious diseases change in response to global change, the mechanisms and directions of these effects are system specific, requiring new, integrated approaches to disease control that recognize linkages between environmental and economic sustainability and human and planetary health.
View details for DOI 10.1146/annurev-resource-111820-024214
View details for PubMedID 38371741
View details for PubMedCentralID PMC10871673
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Scaling effects of temperature on parasitism from individuals to populations.
The Journal of animal ecology
2022
Abstract
Parasitism is expected to change in a warmer future, but whether warming leads to substantial increases in parasitism remains unclear. Understanding how warming effects on parasitism in individual hosts (e.g., parasite load) translate to effects on population-level parasitism (e.g., prevalence, R0 ) remains a major knowledge gap. We conducted a literature review and identified 24 host-parasite systems that had information on the temperature dependence of parasitism at both individual host and host population levels: 13 vector-borne systems and 11 environmentally transmitted systems. We found a strong positive correlation between the thermal optima of individual- and population-level parasitism, though several of the environmentally transmitted systems exhibited thermal optima >5°C apart between individual and population levels. Parasitism thermal optima were close to vector performance thermal optima in vector-borne systems but not hosts in environmentally transmitted systems, suggesting these thermal mismatches may be more common in certain types of host-parasite systems. We also adapted and simulated simple models for both types of transmission modes and found the same pattern across the two modes: thermal optima were more strongly correlated across scales when there were more traits linking individual- to population-level processes. Generally, our results suggest that information on the temperature dependence, and specifically the thermal optimum, at either the individual- or population-level should provide a useful-though not quantitatively exact-baseline for predicting temperature dependence at the other level, especially in vector-borne parasite systems. Environmentally transmitted parasitism may operate by a different set of rules, in which temperature-dependence is decoupled in some systems, requiring the need for trait-based studies of temperature-dependence at individual and population levels.
View details for DOI 10.1111/1365-2656.13786
View details for PubMedID 35900837
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Global Health Needs Modernized Containment Strategies to Prepare for the Next Pandemic.
Frontiers in public health
2022; 10: 834451
Abstract
COVID-19 continues to be a public health crisis, while severely impacting global financial markets causing significant economic and social hardship. As with any emerging disease, pharmaceutical interventions required time, emphasizing the initial and continuing need for non-pharmaceutical interventions. We highlight the role of anthropological and historical perspectives to inform approaches to non-pharmaceutical interventions for future preparedness. The National Academy of Medicine, a not-for-profit, non-governmental US-based medical watchdog organization, published a key document early in the COVID-19 pandemic which points to inadequate quarantine and containment infrastructure as a significant obstacle to an effective pandemic response. In considering how to implement effective quarantine policies and infrastructure, we argue that it is essential to take a longitudinal approach to assess interventions that have been effective in past pandemics while simultaneously addressing and eliminating the negative socio-historical legacies of ineffective quarantine practices. Our overview reinforces the need for social equity and compassion when implementing containment.
View details for DOI 10.3389/fpubh.2022.834451
View details for PubMedID 35769777
View details for PubMedCentralID PMC9234159
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Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis.
Annals of the American Thoracic Society
1800
Abstract
RATIONALE: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts.OBJECTIVES: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models.METHODS: Regionally-resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review.RESULTS: Effect estimates, and associated uncertainties, varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1-1.1% per 1 degree C) was estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel, and include: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socio-economic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models.CONCLUSIONS: This work provides an example for how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.
View details for DOI 10.1513/AnnalsATS.202110-1193OC
View details for PubMedID 35073249
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Global Change and Emerging Infectious Diseases
ANNUAL REVIEW OF RESOURCE ECONOMICS
2022; 14: 333-354
View details for DOI 10.1146/annurev-resource-111820-024214
View details for Web of Science ID 000865583800015
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Ecological and socioeconomic factors associated with the human burden of environmentally mediated pathogens: a global analysis.
The Lancet. Planetary health
2022; 6 (11): e870-e879
Abstract
BACKGROUND: Billions of people living in poverty are at risk of environmentally mediated infectious diseases-that is, pathogens with environmental reservoirs that affect disease persistence and control and where environmental control of pathogens can reduce human risk. The complex ecology of these diseases creates a global health problem not easily solved with medical treatment alone.METHODS: We quantified the current global disease burden caused by environmentally mediated infectious diseases and used a structural equation model to explore environmental and socioeconomic factors associated with the human burden of environmentally mediated pathogens across all countries.FINDINGS: We found that around 80% (455 of 560) of WHO-tracked pathogen species known to infect humans are environmentally mediated, causing about 40% (129 488 of 359 341 disability-adjusted life years) of contemporary infectious disease burden (global loss of 130 million years of healthy life annually). The majority of this environmentally mediated disease burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak associations between disease burden and biodiversity or agricultural land use at the global scale. In contrast, the proportion of people with rural poor livelihoods in a country was a strong proximate indicator of environmentally mediated infectious disease burden. Political stability and wealth were associated with improved sanitation, better health care, and lower proportions of rural poverty, indirectly resulting in lower burdens of environmentally mediated infections. Rarely, environmentally mediated pathogens can evolve into global pandemics (eg, HIV, COVID-19) affecting even the wealthiest communities.INTERPRETATION: The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals.FUNDING: Bill & Melinda Gates Foundation, National Institutes of Health, National Science Foundation, Alfred P. Sloan Foundation, National Institute for Mathematical and Biological Synthesis, Stanford University, and the US Defense Advanced Research Projects Agency.
View details for DOI 10.1016/S2542-5196(22)00248-0
View details for PubMedID 36370725
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Physiology and ecology combine to determine host andvector importance for Ross River virus.
eLife
2021; 10
Abstract
Identifying the key vector and host species that drive the transmission of zoonotic pathogens is notoriously difficult but critical for disease control. We present a nested approach for quantifying the importance of host and vectors that integrates species' physiological competence with their ecological traits. We apply this framework to a medically important arbovirus, Ross River virus (RRV), in Brisbane, Australia. We find that vertebrate hosts with high physiological competence are not the most important for community transmission; interactions between hosts and vectors largely underpin the importance of host species. For vectors, physiological competence is highly important. Our results identify primary and secondary vectors of RRV and suggest two potential transmission cycles in Brisbane: an enzootic cycle involving birds and an urban cycle involving humans. The framework accounts for uncertainty from each fitted statistical model in estimates of species' contributions to transmission and has has direct application to other zoonotic pathogens.
View details for DOI 10.7554/eLife.67018
View details for PubMedID 34414887
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How will mosquitoes adapt to climate warming?
eLife
2021; 10
Abstract
The potential for adaptive evolution to enable species persistence under a changing climate is one of the most important questions for understanding impacts of future climate change. Climate adaptation may be particularly likely for short-lived ectotherms, including many pest, pathogen, and vector species. For these taxa, estimating climate adaptive potential is critical for accurate predictive modeling and public health preparedness. Here, we demonstrate how a simple theoretical framework used in conservation biology-evolutionary rescue models-can be used to investigate the potential for climate adaptation in these taxa, using mosquito thermal adaptation as a focal case. Synthesizing current evidence, we find that short mosquito generation times, high population growth rates, and strong temperature-imposed selection favor thermal adaptation. However, knowledge gaps about the extent of phenotypic and genotypic variation in thermal tolerance within mosquito populations, the environmental sensitivity of selection, and the role of phenotypic plasticity constrain our ability to make more precise estimates. We describe how common garden and selection experiments can be used to fill these data gaps. Lastly, we investigate the consequences of mosquito climate adaptation on disease transmission using Aedes aegypti-transmitted dengue virus in Northern Brazil as a case study. The approach outlined here can be applied to any disease vector or pest species and type of environmental change.
View details for DOI 10.7554/eLife.69630
View details for PubMedID 34402424
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Understanding the emergence of contingent and deterministic exclusion in multispecies communities
ECOLOGY LETTERS
2021
Abstract
Competitive exclusion can be classified as deterministic or as historically contingent. While competitive exclusion is common in nature, it has remained unclear when multispecies communities formed by more than two species should be dominated by deterministic or contingent exclusion. Here, we take a fully parameterised model of an empirical competitive system between invasive annual and native perennial plant species to explain both the emergence and sources of competitive exclusion in multispecies communities. Using a structural approach to understand the range of parameters promoting deterministic and contingent exclusions, we then find heuristic theoretical support for the following three general conclusions. First, we find that the life-history of perennial species increases the probability of observing contingent exclusion by increasing their effective intrinsic growth rates. Second, we find that the probability of observing contingent exclusion increases with weaker intraspecific competition, and not with the level of hierarchical competition. Third, we find a shift from contingent exclusion to deterministic exclusion with increasing numbers of competing species. Our work provides a heuristic framework to increase our understanding about the predictability of species persistence within multispecies communities.
View details for DOI 10.1111/ele.13846
View details for Web of Science ID 000674502900001
View details for PubMedID 34288350
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Effects of changes in temperature on Zika dynamics and control.
Journal of the Royal Society, Interface
2021; 18 (178): 20210165
Abstract
When a rare pathogen emerges to cause a pandemic, it is critical to understand its dynamics and the impact of mitigation measures. We use experimental data to parametrize a temperature-dependent model of Zika virus (ZIKV) transmission dynamics and analyse the effects of temperature variability and control-related parameters on the basic reproduction number (R0) and the final epidemic size of ZIKV. Sensitivity analyses show that these two metrics are largely driven by different parameters, with the exception of temperature, which is the dominant driver of epidemic dynamics in the models. Our R0 estimate has a single optimum temperature (30°C), comparable to other published results (29°C). However, the final epidemic size is maximized across a wider temperature range, from 24 to 36°C. The models indicate that ZIKV is highly sensitive to seasonal temperature variation. For example, although the model predicts that ZIKV transmission cannot occur at a constant temperature below 23°C ( average annual temperature of Rio de Janeiro, Brazil), the model predicts substantial epidemics for areas with a mean temperature of 20°C if there is seasonal variation of 10°C ( average annual temperature of Tampa, Florida). This suggests that the geographical range of ZIKV is wider than indicated from static R0 models, underscoring the importance of climate dynamics and variation in the context of broader climate change on emerging infectious diseases.
View details for DOI 10.1098/rsif.2021.0165
View details for PubMedID 33947225
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The interplay of policy, behavior, and socioeconomic conditions in early COVID-19 epidemiology in Georgia.
medRxiv : the preprint server for health sciences
2021
Abstract
To investigate the impact of local public health orders, behavior, and population factors on early epidemic dynamics, we investigated variation among counties in the U.S. state of Georgia. We conducted regressions to identify predictors of (1) local public health orders, (2) mobility as a proxy for behavior, and (3) epidemiological outcomes (i.e., cases and deaths). We used an event study to determine whether social distancing and shelter-in-place orders caused a change in mobility. Counties at greater risk for large early outbreaks (i.e., larger populations and earlier first cases) were more likely to introduce local public health orders. Social distancing orders gradually reduced mobility by 19% ten days after their introduction, and lower mobility was associated with fewer cases and deaths. Air pollution and population size were predictors of cases and deaths, while larger elderly or Black population were predictors of lower mobility and greater cases, suggesting self-protective behavior in vulnerable populations. Early epidemiological outcomes reflected responses to policy orders and existing health and socioeconomic disparities related to disease vulnerability and ability to socially distance. Teasing apart the impact of behavior changes and population factors is difficult because the epidemic is embedded in a complex social system with multiple potential feedbacks.
View details for DOI 10.1101/2021.03.24.21254256
View details for PubMedID 33791739
View details for PubMedCentralID PMC8010771
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Native perennial and non-native annual grasses shape pathogen community composition and disease severity in a California grassland.
The Journal of ecology
2021; 109 (2): 900-912
Abstract
The densities of highly competent plant hosts (i.e. those that are susceptible to and successfully transmit a pathogen) may shape pathogen community composition and disease severity, altering disease risk and impacts. Life history and evolutionary history can influence host competence; longer lived species tend to be better defended than shorter lived species and pathogens adapt to infect species with which they have longer evolutionary histories. It is unclear, however, how the densities of species that differ in competence due to life and evolutionary histories affect plant pathogen community composition and disease severity.We examined foliar fungal pathogens of two host groups in a California grassland: native perennial and non-native annual grasses. We first characterized pathogen community composition and disease severity of the two host groups to approximate differences in competence. We then used observational and manipulated gradients of native perennial and non-native annual grass densities to assess the effects of each host group on pathogen community composition and disease severity in 1-m2 plots.Native perennial and non-native annual grasses hosted distinct pathogen communities but shared generalist pathogens. Native perennial grasses experienced 26% higher disease severity than non-native annuals. Only the observational gradient of native perennial grass density affected disease severity; there were no other significant relationships between host group density and either disease severity or pathogen community composition.Synthesis. The life and evolutionary histories of grasses likely influence their competence for different pathogen species, exemplified by distinct pathogen communities and differences in disease severity. However, there was limited evidence that the density of either host group affected pathogen community composition or disease severity. Therefore, competence for different pathogens likely shapes pathogen community composition and disease severity but may not interact with host density to alter disease risk and impacts at small scales.
View details for DOI 10.1111/1365-2745.13515
View details for PubMedID 34158675
View details for PubMedCentralID PMC8215988
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The influence of vector-borne disease on human history: socio-ecological mechanisms.
Ecology letters
2021
Abstract
Vector-borne diseases (VBDs) are embedded within complex socio-ecological systems. While research has traditionally focused on the direct effects of VBDs on human morbidity and mortality, it is increasingly clear that their impacts are much more pervasive. VBDs are dynamically linked to feedbacks between environmental conditions, vector ecology, disease burden, and societal responses that drive transmission. As a result, VBDs have had profound influence on human history. Mechanisms include: (1) killing or debilitating large numbers of people, with demographic and population-level impacts; (2) differentially affecting populations based on prior history of disease exposure, immunity, and resistance; (3) being weaponised to promote or justify hierarchies of power, colonialism, racism, classism and sexism; (4) catalysing changes in ideas, institutions, infrastructure, technologies and social practices in efforts to control disease outbreaks; and (5) changing human relationships with the land and environment. We use historical and archaeological evidence interpreted through an ecological lens to illustrate how VBDs have shaped society and culture, focusing on case studies from four pertinent VBDs: plague, malaria, yellow fever and trypanosomiasis. By comparing across diseases, time periods and geographies, we highlight the enormous scope and variety of mechanisms by which VBDs have influenced human history.
View details for DOI 10.1111/ele.13675
View details for PubMedID 33501751
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Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents.
Nature communications
2021; 12 (1): 1233
Abstract
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.
View details for DOI 10.1038/s41467-021-21496-7
View details for PubMedID 33623008
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Household and climate factors influence Aedes aegypti presence in the arid city of Huaquillas, Ecuador.
PLoS neglected tropical diseases
2021; 15 (11): e0009931
Abstract
Arboviruses transmitted by Aedes aegypti (e.g., dengue, chikungunya, Zika) are of major public health concern on the arid coastal border of Ecuador and Peru. This high transit border is a critical disease surveillance site due to human movement-associated risk of transmission. Local level studies are thus integral to capturing the dynamics and distribution of vector populations and social-ecological drivers of risk, to inform targeted public health interventions. Our study examines factors associated with household-level Ae. aegypti presence in Huaquillas, Ecuador, while accounting for spatial and temporal effects. From January to May of 2017, adult mosquitoes were collected from a cohort of households (n = 63) in clusters (n = 10), across the city of Huaquillas, using aspirator backpacks. Household surveys describing housing conditions, demographics, economics, travel, disease prevention, and city services were conducted by local enumerators. This study was conducted during the normal arbovirus transmission season (January-May), but during an exceptionally dry year. Household level Ae. aegypti presence peaked in February, and counts were highest in weeks with high temperatures and a week after increased rainfall. Univariate analyses with proportional odds logistic regression were used to explore household social-ecological variables and female Ae. aegypti presence. We found that homes were more likely to have Ae. aegypti when households had interruptions in piped water service. Ae. aegypti presence was less likely in households with septic systems. Based on our findings, infrastructure access and seasonal climate are important considerations for vector control in this city, and even in dry years, the arid environment of Huaquillas supports Ae. aegypti breeding habitat.
View details for DOI 10.1371/journal.pntd.0009931
View details for PubMedID 34784348
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The impact of long-term non-pharmaceutical interventions on COVID-19 epidemic dynamics and control: the value and limitations of early models.
Proceedings. Biological sciences
2021; 288 (1957): 20210811
Abstract
Mathematical models of epidemics are important tools for predicting epidemic dynamics and evaluating interventions. Yet, because early models are built on limited information, it is unclear how long they will accurately capture epidemic dynamics. Using a stochastic SEIR model of COVID-19 fitted to reported deaths, we estimated transmission parameters at different time points during the first wave of the epidemic (March-June, 2020) in Santa Clara County, California. Although our estimated basic reproduction number ([Formula: see text]) remained stable from early April to late June (with an overall median of 3.76), our estimated effective reproduction number ([Formula: see text]) varied from 0.18 to 1.02 in April before stabilizing at 0.64 on 27 May. Between 22 April and 27 May, our model accurately predicted dynamics through June; however, the model did not predict rising summer cases after shelter-in-place orders were relaxed in June, which, in early July, was reflected in cases but not yet in deaths. While models are critical for informing intervention policy early in an epidemic, their performance will be limited as epidemic dynamics evolve. This paper is one of the first to evaluate the accuracy of an early epidemiological compartment model over time to understand the value and limitations of models during unfolding epidemics.
View details for DOI 10.1098/rspb.2021.0811
View details for PubMedID 34428971
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Response to Valle and Zorello Laporta: Clarifying the Use of Instrumental Variable Methods to Understand the Effects of Environmental Change on Infectious Disease Transmission.
The American journal of tropical medicine and hygiene
2021
Abstract
Identifying the effects of environmental change on the transmission of vectorborne and zoonotic diseases is of fundamental importance in the face of rapid global change. Causal inference approaches, including instrumental variable (IV) estimation, hold promise in disentangling plausibly causal relationships from observational data in these complex systems. Valle and Zorello Laporta recently critiqued the application of such approaches in our recent study of the effects of deforestation on malaria transmission in the Brazilian Amazon on the grounds that key statistical assumptions were not met. Here, we respond to this critique by 1) deriving the IV estimator to clarify the assumptions that Valle and Zorello Laporta conflate and misrepresent in their critique, 2) discussing these key assumptions as they relate to our original study and how our original approach reasonably satisfies the assumptions, and 3) presenting model results using alternative instrumental variables that can be argued more strongly satisfy key assumptions, illustrating that our results and original conclusion-that deforestation drives malaria transmission-remain unchanged.
View details for DOI 10.4269/ajtmh.21-0218
View details for PubMedID 34583331
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Environmental Drivers of Vector-Borne Diseases
POPULATION BIOLOGY OF VECTOR-BORNE DISEASES
2021: 85-118
View details for DOI 10.1093/oso/9780198853244.003.0006
View details for Web of Science ID 000679904700006
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Human-mediated impacts on biodiversity and the consequences for zoonotic disease spillover.
Current biology : CB
2021; 31 (19): R1342-R1361
Abstract
Human-mediated changes to natural ecosystems have consequences for both ecosystem and human health. Historically, efforts to preserve or restore 'biodiversity' can seem to be in opposition to human interests. However, the integration of biodiversity conservation and public health has gained significant traction in recent years, and new efforts to identify solutions that benefit both environmental and human health are ongoing. At the forefront of these efforts is an attempt to clarify ways in which biodiversity conservation can help reduce the risk of zoonotic spillover of pathogens from wild animals, sparking epidemics and pandemics in humans and livestock. However, our understanding of the mechanisms by which biodiversity change influences the spillover process is incomplete, limiting the application of integrated strategies aimed at achieving positive outcomes for both conservation and disease management. Here, we review the literature, considering a broad scope of biodiversity dimensions, to identify cases where zoonotic pathogen spillover is mechanistically linked to changes in biodiversity. By reframing the discussion around biodiversity and disease using mechanistic evidence - while encompassing multiple aspects of biodiversity including functional diversity, landscape diversity, phenological diversity, and interaction diversity - we work toward general principles that can guide future research and more effectively integrate the related goals of biodiversity conservation and spillover prevention. We conclude by summarizing how these principles could be used to integrate the goal of spillover prevention into ongoing biodiversity conservation initiatives.
View details for DOI 10.1016/j.cub.2021.08.070
View details for PubMedID 34637744
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Chopping the tail: How preventing superspreading can help to maintain COVID-19 control.
Epidemics
2020; 34: 100430
Abstract
Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates. Here, we present a stochastic compartmental (SEIR) epidemiological model framework for estimating transmission parameters from multiple imperfectly observed data streams, including reported cases, deaths, and mobile phone-based mobility that incorporates individual-level heterogeneity in transmission using previous estimates for SARS-CoV-1 and SARS-CoV-2. We parameterize the model for COVID-19 epidemic dynamics by estimating a time-varying transmission rate that incorporates the impact of non-pharmaceutical intervention strategies that change over time, in five epidemiologically distinct settings-Los Angeles and Santa Clara Counties, California; Seattle (King County), Washington; Atlanta (Dekalb and Fulton Counties), Georgia; and Miami (Miami-Dade County), Florida. We find that the effective reproduction number (RE) dropped below 1 rapidly in all five locations following social distancing orders in mid-March, 2020, but that gradually increasing mobility starting around mid-April led to an RE once again above 1 in late May (Los Angeles, Miami, and Atlanta) or early June (Santa Clara County and Seattle). However, we find that increased social distancing starting in mid-July in response to epidemic resurgence once again dropped RE below 1 in all locations by August 14. We next used the fitted model to ask: how does truncating the individual-level transmission rate distribution (which removes periods of time with especially high individual transmission rates and thus models superspreading events) affect epidemic dynamics and control? We find that interventions that truncate the transmission rate distribution while partially relaxing social distancing are broadly effective, with impacts on epidemic growth on par with the strongest population-wide social distancing observed in April, 2020. Given that social distancing interventions will be needed to maintain epidemic control until a vaccine becomes widely available, "chopping off the tail" to reduce the probability of superspreading events presents a promising option to alleviate the need for extreme general social distancing.
View details for DOI 10.1016/j.epidem.2020.100430
View details for PubMedID 33360871
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Susceptible host availability modulates climate effects on dengue dynamics.
Ecology letters
2020
Abstract
Experiments and models suggest that climate affects mosquito-borne disease transmission. However, disease transmission involves complex nonlinear interactions between climate and population dynamics, which makes detecting climate drivers at the population level challenging. By analysing incidence data, estimated susceptible population size, and climate data with methods based on nonlinear time series analysis (collectively referred to as empirical dynamic modelling), we identified drivers and their interactive effects on dengue dynamics in San Juan, Puerto Rico. Climatic forcing arose only when susceptible availability was high: temperature and rainfall had net positive and negative effects respectively. By capturing mechanistic, nonlinear and context-dependent effects of population susceptibility, temperature and rainfall on dengue transmission empirically, our model improves forecast skill over recent, state-of-the-art models for dengue incidence. Together, these results provide empirical evidence that the interdependence of host population susceptibility and climate drives dengue dynamics in a nonlinear and complex, yet predictable way.
View details for DOI 10.1111/ele.13652
View details for PubMedID 33300663
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Habitat type and interannual variation shape unique fungal pathogen communities on a California native bunchgrass
FUNGAL ECOLOGY
2020; 48
View details for DOI 10.1016/j.funeco.2020.100983
View details for Web of Science ID 000583820500002
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Habitat type and interannual variation shape unique fungal pathogen communities on a California native bunchgrass.
Fungal ecology
2020; 48
Abstract
The role of infectious disease in regulating host populations is increasingly recognized, but how environmental conditions affect pathogen communities and infection levels remains poorly understood. Over 3 y, we compared foliar disease burden, fungal pathogen community composition, and foliar chemistry in the perennial bunchgrass Stipa pulchra occurring in adjacent serpentine and nonserpentine grassland habitats with distinct soil types and plant communities. We found that serpentine and nonserpentine S. pulchra experienced consistent, low disease pressure associated with distinct fungal pathogen communities with high interannual species turnover. Additionally, plant chemistry differed with habitat type. The results indicate that this species experiences minimal foliar disease associated with diverse fungal communities that are structured across landscapes by spatially and temporally variable conditions. Distinct fungal communities associated with different growing conditions may shield S. pulchra from large disease outbreaks, contributing to the low disease burden observed on this and other Mediterranean grassland species.
View details for DOI 10.1016/j.funeco.2020.100983
View details for PubMedID 33408755
View details for PubMedCentralID PMC7781277
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Impact of prior and projected climate change on US Lyme disease incidence.
Global change biology
2020
Abstract
Lyme disease is the most common vector-borne disease in temperate zones and a growing public health threat in the United States (US). The life cycles of the tick vectors and spirochete pathogen are highly sensitive to climate, but determining the impact of climate change on Lyme disease burden has been challenging due to the complex ecology of the disease and the presence of multiple, interacting drivers of transmission. Here we incorporated 18 years of annual, county-level Lyme disease case data in a panel data statistical model to investigate prior effects of climate variation on disease incidence while controlling for other putative drivers. We then used these climate-disease relationships to project Lyme disease cases using CMIP5 global climate models and two potential climate scenarios (RCP4.5 and RCP8.5). We find that interannual variation in Lyme disease incidence is associated with climate variation in all US regions encompassing the range of the primary vector species. In all regions, the climate predictors explained less of the variation in Lyme disease incidence than unobserved county-level heterogeneity, but the strongest climate-disease association detected was between warming annual temperatures and increasing incidence in the Northeast. Lyme disease projections indicate that cases in the Northeast will increase significantly by 2050 (23,619 ± 21,607 additional cases), but only under RCP8.5, and with large uncertainty around this projected increase. Significant case changes are not projected for any other region under either climate scenario. The results demonstrate a regionally variable and nuanced relationship between climate change and Lyme disease, indicating possible nonlinear responses of vector ticks and transmission dynamics to projected climate change. Moreover, our results highlight the need for improved preparedness and public health interventions in endemic regions to minimize the impact of further climate change-induced increases in Lyme disease burden.
View details for DOI 10.1111/gcb.15435
View details for PubMedID 33150704
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Native perennial and non-native annual grasses shape pathogen community composition and disease severity in a California grassland
JOURNAL OF ECOLOGY
2020
View details for DOI 10.1111/1365-2745.13515
View details for Web of Science ID 000579740800001
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Climate change could shift disease burden from malaria to arboviruses in Africa
LANCET PLANETARY HEALTH
2020; 4 (9): E416–E423
View details for Web of Science ID 000569270300013
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Spatial and Temporal Changes in Nesting Behavior by Black Skimmers (Rynchops niger) in New Jersey, USA, from 1976-2019
WATERBIRDS
2020; 43 (3-4): 307-313
View details for DOI 10.1675/063.043.0309
View details for Web of Science ID 000696458400009
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Age influences the thermal suitability ofPlasmodium falciparumtransmission in the Asian malaria vectorAnopheles stephensi
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
2020; 287 (1931): 20201093
Abstract
Models predicting disease transmission are vital tools for long-term planning of malaria reduction efforts, particularly for mitigating impacts of climate change. We compared temperature-dependent malaria transmission models when mosquito life-history traits were estimated from a truncated portion of the lifespan (a common practice) versus traits measured across the full lifespan. We conducted an experiment on adult female Anopheles stephensi, the Asian urban malaria mosquito, to generate daily per capita values for mortality, egg production and biting rate at six constant temperatures. Both temperature and age significantly affected trait values. Further, we found quantitative and qualitative differences between temperature-trait relationships estimated from truncated data versus observed lifetime values. Incorporating these temperature-trait relationships into an expression governing the thermal suitability of transmission, relative R0(T), resulted in minor differences in the breadth of suitable temperatures for Plasmodium falciparum transmission between the two models constructed from only An. stephensi trait data. However, we found a substantial increase in thermal niche breadth compared with a previously published model consisting of trait data from multiple Anopheles mosquito species. Overall, this work highlights the importance of considering how mosquito trait values vary with mosquito age and mosquito species when generating temperature-based suitability predictions of transmission.
View details for DOI 10.1098/rspb.2020.1093
View details for Web of Science ID 000554927100002
View details for PubMedID 32693720
View details for PubMedCentralID PMC7423674
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AeDES: a next-generation monitoring and forecasting system for environmental suitability of Aedes-borne disease transmission
SCIENTIFIC REPORTS
2020; 10 (1): 12640
Abstract
Aedes-borne diseases, such as dengue and chikungunya, are responsible for more than 50 million infections worldwide every year, with an overall increase of 30-fold in the last 50 years, mainly due to city population growth, more frequent travels and ecological changes. In the United States of America, the vast majority of Aedes-borne infections are imported from endemic regions by travelers, who can become new sources of mosquito infection upon their return home if the exposed population is susceptible to the disease, and if suitable environmental conditions for the mosquitoes and the virus are present. Since the susceptibility of the human population can be determined via periodic monitoring campaigns, the environmental suitability for the presence of mosquitoes and viruses becomes one of the most important pieces of information for decision makers in the health sector. We present a next-generation monitoring and forecasting system for [Formula: see text]-borne diseases' environmental suitability (AeDES) of transmission in the conterminous United States and transboundary regions, using calibrated ento-epidemiological models, climate models and temperature observations. After analyzing the seasonal predictive skill of AeDES, we briefly consider the recent Zika epidemic, and the compound effects of the current Central American dengue outbreak happening during the SARS-CoV-2 pandemic, to illustrate how a combination of tailored deterministic and probabilistic forecasts can inform key prevention and control strategies .
View details for DOI 10.1038/s41598-020-69625-4
View details for Web of Science ID 000556400100030
View details for PubMedID 32724218
View details for PubMedCentralID PMC7387552
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The Role of Vector Trait Variation in Vector-Borne Disease Dynamics.
Frontiers in ecology and evolution
2020; 8
Abstract
Many important endemic and emerging diseases are transmitted by vectors that are biting arthropods. The functional traits of vectors can affect pathogen transmission rates directly and also through their effect on vector population dynamics. Increasing empirical evidence shows that vector traits vary significantly across individuals, populations, and environmental conditions, and at time scales relevant to disease transmission dynamics. Here, we review empirical evidence for variation in vector traits and how this trait variation is currently incorporated into mathematical models of vector-borne disease transmission. We argue that mechanistically incorporating trait variation into these models, by explicitly capturing its effects on vector fitness and abundance, can improve the reliability of their predictions in a changing world. We provide a conceptual framework for incorporating trait variation into vector-borne disease transmission models, and highlight key empirical and theoretical challenges. This framework provides a means to conceptualize how traits can be incorporated in vector borne disease systems, and identifies key areas in which trait variation can be explored. Determining when and to what extent it is important to incorporate trait variation into vector borne disease models remains an important, outstanding question.
View details for DOI 10.3389/fevo.2020.00189
View details for PubMedID 32775339
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Climate change could shift disease burden from malaria to arboviruses in Africa.
The Lancet. Planetary health
2020; 4 (9): e416–e423
Abstract
Malaria is a long-standing public health problem in sub-Saharan Africa, whereas arthropod-borne viruses (arboviruses) such as dengue and chikungunya cause an under-recognised burden of disease. Many human and environmental drivers affect the dynamics of vector-borne diseases. In this Personal View, we argue that the direct effects of warming temperatures are likely to promote greater environmental suitability for dengue and other arbovirus transmission by Aedes aegypti and reduce suitability for malaria transmission by Anopheles gambiae. Environmentally driven changes in disease dynamics will be complex and multifaceted, but given that current public efforts are targeted to malaria control, we highlight Ae aegypti and dengue, chikungunya, and other arboviruses as potential emerging public health threats in sub-Saharan Africa.
View details for DOI 10.1016/S2542-5196(20)30178-9
View details for PubMedID 32918887
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Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23°C and 26°C.
eLife
2020; 9
Abstract
The temperature-dependence of many important mosquito-borne diseases has never been quantified. These relationships are critical for understanding current distributions and predicting future shifts from climate change. We used trait-based models to characterize temperature-dependent transmission of 10 vector-pathogen pairs of mosquitoes (Culex pipiens, Cx. quinquefascsiatus, Cx. tarsalis, and others) and viruses (West Nile, Eastern and Western Equine Encephalitis, St. Louis Encephalitis, Sindbis, and Rift Valley Fever viruses), most with substantial transmission in temperate regions. Transmission is optimized at intermediate temperatures (23-26°C) and often has wider thermal breadths (due to cooler lower thermal limits) compared to pathogens with predominately tropical distributions (in previous studies). The incidence of human West Nile virus cases across US counties responded unimodally to average summer temperature and peaked at 24°C, matching model-predicted optima (24-25°C). Climate warming will likely shift transmission of these diseases, increasing it in cooler locations while decreasing it in warmer locations.
View details for DOI 10.7554/eLife.58511
View details for PubMedID 32930091
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Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050.
Global change biology
2020
Abstract
In the aftermath of the 2015 pandemic of Zika virus, concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature-dependent transmission model for Zika virus (ZIKV) to project climate change impacts on transmission suitability risk by mid-century (a generation into the future). Based on these model predictions, in the worst-case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.
View details for DOI 10.1111/gcb.15384
View details for PubMedID 33037740
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Chopping the tail: how preventing superspreading can help to maintain COVID-19 control.
medRxiv : the preprint server for health sciences
2020
Abstract
Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A skewed distribution where few individuals or events are responsible for the majority of transmission can result in explosive, superspreading events, which produce rapid and volatile epidemic dynamics, especially early or late in epidemics. Anticipating and preventing superspreading events can produce large reductions in overall transmission rates. Here, we present a compartmental (SEIR) epidemiological model framework for estimating transmission parameters from multiple imperfectly observed data streams, including reported cases, deaths, and mobile phone-based mobility that incorporates individual-level heterogeneity in transmission using previous estimates for SARS-CoV-1 and SARS-CoV-2. We parameterize the model for COVID-19 epidemic dynamics by estimating a time-varying transmission rate that incorporates the impact of non-pharmaceutical intervention strategies that change over time, in five epidemiologically distinct settings---Los Angeles and Santa Clara Counties, California; Seattle (King County), Washington; Atlanta (Dekalb and Fulton Counties), Georgia; and Miami (Miami-Dade County), Florida. We find the effective reproduction number R E dropped below 1 rapidly following social distancing orders in mid-March, 2020 and remained there into June in Santa Clara County and Seattle, but climbed above 1 in late May in Los Angeles, Miami, and Atlanta, and has trended upward in all locations since April. With the fitted model, we ask: how does truncating the tail of the individual-level transmission rate distribution affect epidemic dynamics and control? We find interventions that truncate the transmission rate distribution while partially relaxing social distancing are broadly effective, with impacts on epidemic growth on par with the strongest population-wide social distancing observed in April, 2020. Given that social distancing interventions will be needed to maintain epidemic control until a vaccine becomes widely available, "chopping off the tail" to reduce the probability of superspreading events presents a promising option to alleviate the need for extreme general social distancing.
View details for DOI 10.1101/2020.06.30.20143115
View details for PubMedID 32637966
View details for PubMedCentralID PMC7340192
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An open challenge to advance probabilistic forecasting for dengue epidemics (vol 116, pg 24268, 2019)
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2019; 116 (51): 26087–88
View details for DOI 10.1073/pnas.1920071116
View details for Web of Science ID 000503281500097
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Towards common ground in the biodiversity-disease debate.
Nature ecology & evolution
2019
Abstract
The disease ecology community has struggled to come to consensus on whether biodiversity reduces or increases infectious disease risk, a question that directly affects policy decisions for biodiversity conservation and public health. Here, we summarize the primary points of contention regarding biodiversity-disease relationships and suggest that vector-borne, generalist wildlife and zoonotic pathogens are the types of parasites most likely to be affected by changes to biodiversity. One synthesis on this topic revealed a positive correlation between biodiversity and human disease burden across countries, but as biodiversity changed over time within these countries, this correlation became weaker and more variable. Another synthesis-a meta-analysis of generally smaller-scale experimental and field studies-revealed a negative correlation between biodiversity and infectious diseases (a dilution effect) in various host taxa. These results raise the question of whether biodiversity-disease relationships are more negative at smaller spatial scales. If so, biodiversity conservation at the appropriate scales might prevent wildlife and zoonotic diseases from increasing in prevalence or becoming problematic (general proactive approaches). Further, protecting natural areas from human incursion should reduce zoonotic disease spillover. By contrast, for some infectious diseases, managing particular species or habitats and targeted biomedical approaches (targeted reactive approaches) might outperform biodiversity conservation as a tool for disease control. Importantly, biodiversity conservation and management need to be considered alongside other disease management options. These suggested guiding principles should provide common ground that can enhance scientific and policy clarity for those interested in simultaneously improving wildlife and human health.
View details for DOI 10.1038/s41559-019-1060-6
View details for PubMedID 31819238
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An open challenge to advance probabilistic forecasting for dengue epidemics.
Proceedings of the National Academy of Sciences of the United States of America
2019
Abstract
A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue.
View details for DOI 10.1073/pnas.1909865116
View details for PubMedID 31712420
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Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing.
Proceedings of the National Academy of Sciences of the United States of America
2019
Abstract
Deforestation and land use change are among the most pressing anthropogenic environmental impacts. In Brazil, a resurgence of malaria in recent decades paralleled rapid deforestation and settlement in the Amazon basin, yet evidence of a deforestation-driven increase in malaria remains equivocal. We hypothesize an underlying cause of this ambiguity is that deforestation and malaria influence each other in bidirectional causal relationships-deforestation increases malaria through ecological mechanisms and malaria reduces deforestation through socioeconomic mechanisms-and that the strength of these relationships depends on the stage of land use transformation. We test these hypotheses with a large geospatial dataset encompassing 795 municipalities across 13 y (2003 to 2015) and show deforestation has a strong positive effect on malaria incidence. Our results suggest a 10% increase in deforestation leads to a 3.3% increase in malaria incidence (9,980 additional cases associated with 1,567 additional km2 lost in 2008, the study midpoint, Amazon-wide). The effect is larger in the interior and absent in outer Amazonian states where little forest remains. However, this strong effect is only detectable after controlling for a feedback of malaria burden on forest loss, whereby increased malaria burden significantly reduces forest clearing, possibly mediated by human behavior or economic development. We estimate a 1% increase in malaria incidence results in a 1.4% decrease in forest area cleared (219 fewer km2 cleared associated with 3,024 additional cases in 2008). This bidirectional socioecological feedback between deforestation and malaria, which attenuates as land use intensifies, illustrates the intimate ties between environmental change and human health.
View details for DOI 10.1073/pnas.1905315116
View details for PubMedID 31611369
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The problem of scale in the prediction and management of pathogen spillover.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
2019; 374 (1782): 20190224
Abstract
Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
View details for DOI 10.1098/rstb.2019.0224
View details for PubMedID 31401958
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Mosquito and primate ecology predict human risk of yellow fever virus spillover in Brazil.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
2019; 374 (1782): 20180335
Abstract
Many (re)emerging infectious diseases in humans arise from pathogen spillover from wildlife or livestock, and accurately predicting pathogen spillover is an important public health goal. In the Americas, yellow fever in humans primarily occurs following spillover from non-human primates via mosquitoes. Predicting yellow fever spillover can improve public health responses through vector control and mass vaccination. Here, we develop and test a mechanistic model of pathogen spillover to predict human risk for yellow fever in Brazil. This environmental risk model, based on the ecology of mosquito vectors and non-human primate hosts, distinguished municipality-months with yellow fever spillover from 2001 to 2016 with high accuracy (AUC = 0.72). Incorporating hypothesized cyclical dynamics of infected primates improved accuracy (AUC = 0.79). Using boosted regression trees to identify gaps in the mechanistic model, we found that important predictors include current and one-month lagged environmental risk, vaccine coverage, population density, temperature and precipitation. More broadly, we show that for a widespread human viral pathogen, the ecological interactions between environment, vectors, reservoir hosts and humans can predict spillover with surprising accuracy, suggesting the potential to improve preventive action to reduce yellow fever spillover and avert onward epidemics in humans. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
View details for DOI 10.1098/rstb.2018.0335
View details for PubMedID 31401964
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Dynamic and integrative approaches to understanding pathogen spillover.
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
2019; 374 (1782): 20190014
View details for DOI 10.1098/rstb.2019.0014
View details for PubMedID 31401959
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Thermal biology of mosquito-borne disease.
Ecology letters
2019
Abstract
Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species - including globally important diseases like malaria, dengue, and Zika - synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23-29C and declining to zero below 9-23C and above 32-38C. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25-26C) while dengue and Zika viruses had the highest (29C)thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration.
View details for DOI 10.1111/ele.13335
View details for PubMedID 31286630
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A global test of ecoregions (vol 2, pg 1889, 2018)
NATURE ECOLOGY & EVOLUTION
2019; 3 (4): 708
View details for DOI 10.1038/s41559-019-0858-6
View details for Web of Science ID 000462542100034
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Author Correction: A global test of ecoregions.
Nature ecology & evolution
2019
Abstract
The original paper was published without unique DOIs for GBIF occurrence downloads. These have now been inserted as references 70-76, and the error has been corrected in the PDF and HTML versions of the article.
View details for PubMedID 30858593
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Global expansion and redistribution of Aedes-borne virus transmission risk with climate change
PLOS NEGLECTED TROPICAL DISEASES
2019; 13 (3)
View details for DOI 10.1371/journal.pntd.0007213
View details for Web of Science ID 000463799300030
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Priority Effects and Nonhierarchical Competition Shape Species Composition in a Complex Grassland Community
AMERICAN NATURALIST
2019; 193 (2): 213–26
Abstract
Niche and fitness differences control the outcome of competition, but determining their relative importance in invaded communities-which may be far from equilibrium-remains a pressing concern. Moreover, it is unclear whether classic approaches for studying competition, which were developed predominantly for pairs of interacting species, will fully capture dynamics in complex species assemblages. We parameterized a population-dynamic model using competition experiments of two native and three exotic species from a grassland community. We found evidence for minimal fitness differences or niche differences between the native species, leading to slow replacement dynamics and priority effects, but large fitness advantages allowed exotics to unconditionally invade natives. Priority effects driven by strong interspecific competition between exotic species drove single-species dominance by one of two exotic species in 80% of model outcomes, while a complex mixture of nonhierarchical competition and coexistence between native and exotic species occurred in the remaining 20%. Fungal infection, a commonly hypothesized coexistence mechanism, had weak fitness effects and is unlikely to substantially affect coexistence. In contrast to previous work on pairwise outcomes in largely native-dominated communities, our work supports a role for nearly neutral dynamics and priority effects as drivers of species composition in invaded communities.
View details for DOI 10.1086/701434
View details for Web of Science ID 000458360600007
View details for PubMedID 30720356
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ENVIRONMENTAL AND DEMOGRAPHIC RISK FACTORS FOR AEDES AEGYPTI VECTOR PERSISTENCE IN URBAN AND RURAL KENYA
AMER SOC TROP MED & HYGIENE. 2019: 445
View details for Web of Science ID 000507364504159
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Global expansion and redistribution of Aedes-borne virus transmission risk with climate change.
PLoS neglected tropical diseases
2019; 13 (3): e0007213
Abstract
Forecasting the impacts of climate change on Aedes-borne viruses-especially dengue, chikungunya, and Zika-is a key component of public health preparedness. We apply an empirically parameterized model of viral transmission by the vectors Aedes aegypti and Ae. albopictus, as a function of temperature, to predict cumulative monthly global transmission risk in current climates, and compare them with projected risk in 2050 and 2080 based on general circulation models (GCMs). Our results show that if mosquito range shifts track optimal temperature ranges for transmission (21.3-34.0°C for Ae. aegypti; 19.9-29.4°C for Ae. albopictus), we can expect poleward shifts in Aedes-borne virus distributions. However, the differing thermal niches of the two vectors produce different patterns of shifts under climate change. More severe climate change scenarios produce larger population exposures to transmission by Ae. aegypti, but not by Ae. albopictus in the most extreme cases. Climate-driven risk of transmission from both mosquitoes will increase substantially, even in the short term, for most of Europe. In contrast, significant reductions in climate suitability are expected for Ae. albopictus, most noticeably in southeast Asia and west Africa. Within the next century, nearly a billion people are threatened with new exposure to virus transmission by both Aedes spp. in the worst-case scenario. As major net losses in year-round transmission risk are predicted for Ae. albopictus, we project a global shift towards more seasonal risk across regions. Many other complicating factors (like mosquito range limits and viral evolution) exist, but overall our results indicate that while climate change will lead to increased net and new exposures to Aedes-borne viruses, the most extreme increases in Ae. albopictus transmission are predicted to occur at intermediate climate change scenarios.
View details for PubMedID 30921321
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PREDICTING SPILLOVER OF YELLOW FEVER VIRUS TO HUMANS USING VECTOR AND PRIMATE ECOLOGY
AMER SOC TROP MED & HYGIENE. 2019: 411
View details for Web of Science ID 000507364504049
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CLIMATE CHANGE COULD EXPOSE 1.3 BILLION NEW PEOPLE TO ZIKA VIRUS TRANSMISSION RISK BY 2050
AMER SOC TROP MED & HYGIENE. 2019: 439
View details for Web of Science ID 000507364504138
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Climate drives spatial variation in Zika epidemics in Latin America.
Proceedings. Biological sciences
2019; 286 (1909): 20191578
Abstract
Between 2015 and 2017, Zika virus spread rapidly through populations in the Americas with no prior exposure to the disease. Although climate is a known determinant of many Aedes-transmitted diseases, it is currently unclear whether climate was a major driver of the Zika epidemic and how climate might have differentially impacted outbreak intensity across locations within Latin America. Here, we estimated force of infection for Zika over time and across provinces in Latin America using a time-varying susceptible-infectious-recovered model. Climate factors explained less than 5% of the variation in weekly transmission intensity in a spatio-temporal model of force of infection by province over time, suggesting that week to week transmission within provinces may be too stochastic to predict. By contrast, climate and population factors were highly predictive of spatial variation in the presence and intensity of Zika transmission among provinces, with pseudo-R2 values between 0.33 and 0.60. Temperature, temperature range, rainfall and population size were the most important predictors of where Zika transmission occurred, while rainfall, relative humidity and a nonlinear effect of temperature were the best predictors of Zika intensity and burden. Surprisingly, force of infection was greatest in locations with temperatures near 24°C, much lower than previous estimates from mechanistic models, potentially suggesting that existing vector control programmes and/or prior exposure to other mosquito-borne diseases may have limited transmission in locations most suitable for Aedes aegypti, the main vector of Zika, dengue and chikungunya viruses in Latin America.
View details for DOI 10.1098/rspb.2019.1578
View details for PubMedID 31455188
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Malaria smear positivity among Kenyan children peaks at intermediate temperatures as predicted by ecological models.
Parasites & vectors
2019; 12 (1): 288
Abstract
Ambient temperature is an important determinant of malaria transmission and suitability, affecting the life-cycle of the Plasmodium parasite and Anopheles vector. Early models predicted a thermal malaria transmission optimum of 31 °C, later revised to 25 °C using experimental data from mosquito and parasite biology. However, the link between ambient temperature and human malaria incidence remains poorly resolved.To evaluate the relationship between ambient temperature and malaria risk, 5833 febrile children (<18 years-old) with an acute, non-localizing febrile illness were enrolled from four heterogenous outpatient clinic sites in Kenya (Chulaimbo, Kisumu, Msambweni and Ukunda). Thick and thin blood smears were evaluated for the presence of malaria parasites. Daily temperature estimates were obtained from land logger data, and rainfall from National Oceanic and Atmospheric Administration (NOAA)'s Africa Rainfall Climatology (ARC) data. Thirty-day mean temperature and 30-day cumulative rainfall were estimated and each lagged by 30 days, relative to the febrile visit. A generalized linear mixed model was used to assess relationships between malaria smear positivity and predictors including temperature, rainfall, age, sex, mosquito exposure and socioeconomic status.Malaria smear positivity varied between 42-83% across four clinic sites in western and coastal Kenya, with highest smear positivity in the rural, western site. The temperature ranges were cooler in the western sites and warmer in the coastal sites. In multivariate analysis controlling for socioeconomic status, age, sex, rainfall and bednet use, malaria smear positivity peaked near 25 °C at all four sites, as predicted a priori from an ecological model.This study provides direct field evidence of a unimodal relationship between ambient temperature and human malaria incidence with a peak in malaria transmission occurring at lower temperatures than previously recognized clinically. This nonlinear relationship with an intermediate optimal temperature implies that future climate warming could expand malaria incidence in cooler, highland regions while decreasing incidence in already warm regions with average temperatures above 25 °C. These findings support efforts to further understand the nonlinear association between ambient temperature and vector-borne diseases to better allocate resources and respond to disease threats in a future, warmer world.
View details for DOI 10.1186/s13071-019-3547-z
View details for PubMedID 31171037
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TEMPERATURE DRIVES MALARIA TRANSMISSION: IMPLICATIONS FOR DISEASE CONTROL
AMER SOC TROP MED & HYGIENE. 2019: 472
View details for Web of Science ID 000507364504251
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IMPACT OF HOUSEHOLD CHARACTERISTICS ON AEDES AEGYPTI ABUNDANCE IN RURAL ECUADOR
AMER SOC TROP MED & HYGIENE. 2019: 50
View details for Web of Science ID 000507364502165
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A global test of ecoregions
NATURE ECOLOGY & EVOLUTION
2018; 2 (12): 1889–96
View details for DOI 10.1038/s41559-018-0709-x
View details for Web of Science ID 000450904100016
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A global test of ecoregions.
Nature ecology & evolution
2018
Abstract
A foundational paradigm in biological and Earth sciences is that our planet is divided into distinct ecoregions and biomes demarking unique assemblages of species. This notion has profoundly influenced scientific research and environmental policy. Given recent advances in technology and data availability, however, we are now poised to ask whether ecoregions meaningfully delimit biological communities. Using over 200 million observations of plants, animals and fungi we show compelling evidence that ecoregions delineate terrestrial biodiversity patterns. We achieve this by testing two competing hypotheses: the sharp-transition hypothesis, positing that ecoregion borders divide differentiated biotic communities; and the gradual-transition hypothesis, proposing instead that species turnover is continuous and largely independent of ecoregion borders. We find strong support for the sharp-transition hypothesis across all taxa, although adherence to ecoregion boundaries varies across taxa. Although plant and vertebrate species are tightly linked to sharp ecoregion boundaries, arthropods and fungi show weaker affiliations to this set of ecoregion borders. Our results highlight the essential value of ecological data for setting conservation priorities and reinforce the importance of protecting habitats across as many ecoregions as possible. Specifically, we conclude that ecoregion-based conservation planning can guide investments that simultaneously protect species-, community- and ecosystem-level biodiversity, key for securing Earth's life support systems into the future.
View details for PubMedID 30397301
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Foliar pathogens are unlikely to stabilize coexistence of competing species in a California grassland
ECOLOGY
2018; 99 (10): 2250–59
View details for DOI 10.1002/ecy.2427
View details for Web of Science ID 000446270400013
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Foliar pathogens are unlikely to stabilize coexistence of competing species in a California grassland.
Ecology
2018
Abstract
Pathogen infection is common in wild plants and animals, and may regulate their populations. If pathogens have narrow host ranges and increase with the density of their favored hosts, they may promote host species diversity by suppressing common species to the benefit of rare species. Yet, because many pathogens infect multiple co-occurring hosts, they may not strongly respond to the relative abundance of a single host species. Are natural communities dominated by specialized pathogens that respond to the relative abundance of a specific host or by pathogens with broad host ranges and limited responses to the relative abundance of single host? The answer determines the potential for pathogens to promote host coexistence, as often hypothesized, or to have negligible or even negative effects on host coexistence. We lack a systematic understanding of the impacts, identities, and host ranges of pathogens in natural communities. Here we characterize a community of foliar fungal pathogens and evaluate their host specificity and fitness impacts in a California grassland community of native and exotic species. We found that most of the commonly isolated fungal pathogens were multi-host, with intermediate to low specialization. The amount of pathogen damage each host experienced was independent of host species local relative abundance. Despite pathogen sharing among the host species, fungal communities slightly differed in composition across host species. Plants with high pathogen damage tended to have lower seed production but the relationship was weak, suggesting limited fitness impacts. Moreover, seed production was not dependent on the local relative abundance of each plant species, suggesting that stabilizing coexistence mechanisms may operate at larger spatial scales in this community. Because foliar pathogens in this grassland community are multi-host and have small fitness impacts, they are unlikely to promote negative frequency dependence or plant species coexistence in this system. Still, given that pathogen community composition differentiates across host species, some more subtle feedbacks between host relative abundance and pathogen community composition, damage, and fitness impacts are possible, which could, in turn, promote either coexistence or competitive exclusion.
View details for PubMedID 30179251
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Temperature explains broad patterns of Ross River virus transmission.
eLife
2018; 7
Abstract
Thermal biology predicts that vector-borne disease transmission peaks at intermediate temperatures and declines at high and low temperatures. However, thermal optima and limits remain unknown for most vector-borne pathogens. We built a mechanistic model for the thermal response of Ross River virus, an important mosquito-borne pathogen in Australia, Pacific Islands, and potentially at risk of emerging worldwide. Transmission peaks at moderate temperatures (26.4°C) and declines to zero at thermal limits (17.0 and 31.5°C). The model accurately predicts that transmission is year-round endemic in the tropics but seasonal in temperate areas, resulting in the nationwide seasonal peak in human cases. Climate warming will likely increase transmission in temperate areas (where most Australians live) but decrease transmission in tropical areas where mean temperatures are already near the thermal optimum. These results illustrate the importance of nonlinear models for inferring the role of temperature in disease dynamics and predicting responses to climate change.
View details for PubMedID 30152328
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Temperature explains broad patterns of Ross River virus transmission
ELIFE
2018; 7
View details for DOI 10.7554/eLife.37762
View details for Web of Science ID 000442847300001
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Temperature drives Zika virus transmission: evidence from empirical and mathematical models
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
2018; 285 (2884)
Abstract
Temperature is a strong driver of vector-borne disease transmission. Yet, for emerging arboviruses we lack fundamental knowledge on the relationship between transmission and temperature. Current models rely on the untested assumption that Zika virus responds similarly to dengue virus, potentially limiting our ability to accurately predict the spread of Zika. We conducted experiments to estimate the thermal performance of Zika virus (ZIKV) in field-derived Aedes aegypti across eight constant temperatures. We observed strong, unimodal effects of temperature on vector competence, extrinsic incubation period and mosquito survival. We used thermal responses of these traits to update an existing temperature-dependent model to infer temperature effects on ZIKV transmission. ZIKV transmission was optimized at 29°C, and had a thermal range of 22.7°C-34.7°C. Thus, as temperatures move towards the predicted thermal optimum (29°C) owing to climate change, urbanization or seasonality, Zika could expand north and into longer seasons. By contrast, areas that are near the thermal optimum were predicted to experience a decrease in overall environmental suitability. We also demonstrate that the predicted thermal minimum for Zika transmission is 5°C warmer than that of dengue, and current global estimates on the environmental suitability for Zika are greatly over-predicting its possible range.
View details for PubMedID 30111605
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Estimating the effects of variation in viremia on mosquito susceptibility, infectiousness, and R-0 of Zika in Aedes aegypti
PLOS NEGLECTED TROPICAL DISEASES
2018; 12 (8): e0006733
Abstract
Zika virus (ZIKV) is an arbovirus primarily transmitted by Aedes mosquitoes. Like most viral infections, ZIKV viremia varies over several orders of magnitude, with unknown consequences for transmission. To determine the effect of viral concentration on ZIKV transmission risk, we exposed field-derived Ae. aegypti mosquitoes to four doses (103, 104, 105, 106 PFU/mL) representative of potential variation in the field. We demonstrate that increasing ZIKV dose in the blood-meal significantly increases the probability of mosquitoes becoming infected, and consequently disseminating virus and becoming infectious. Additionally, we observed significant interactions between dose and days post-infection on dissemination and overall transmission efficiency, suggesting that variation in ZIKV dose affects the rates of midgut escape and salivary gland invasion. We did not find significant effects of dose on mosquito mortality. We also demonstrate that detecting virus using RT-qPCR approaches rather than plaque assays potentially over-estimates key transmission parameters, including the time at which mosquitoes become infectious and viral burden. Finally, using these data to parameterize an R0 model, we showed that increasing viremia from 104 to 106 PFU/mL increased relative R0 3.8-fold, demonstrating that variation in viremia substantially affects transmission risk.
View details for PubMedID 30133450
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Seasonal temperature variation influences climate suitability for dengue, chikungunya, and Zika transmission
PLOS NEGLECTED TROPICAL DISEASES
2018; 12 (5): e0006451
Abstract
Dengue, chikungunya, and Zika virus epidemics transmitted by Aedes aegypti mosquitoes have recently (re)emerged and spread throughout the Americas, Southeast Asia, the Pacific Islands, and elsewhere. Understanding how environmental conditions affect epidemic dynamics is critical for predicting and responding to the geographic and seasonal spread of disease. Specifically, we lack a mechanistic understanding of how seasonal variation in temperature affects epidemic magnitude and duration. Here, we develop a dynamic disease transmission model for dengue virus and Aedes aegypti mosquitoes that integrates mechanistic, empirically parameterized, and independently validated mosquito and virus trait thermal responses under seasonally varying temperatures. We examine the influence of seasonal temperature mean, variation, and temperature at the start of the epidemic on disease dynamics. We find that at both constant and seasonally varying temperatures, warmer temperatures at the start of epidemics promote more rapid epidemics due to faster burnout of the susceptible population. By contrast, intermediate temperatures (24-25°C) at epidemic onset produced the largest epidemics in both constant and seasonally varying temperature regimes. When seasonal temperature variation was low, 25-35°C annual average temperatures produced the largest epidemics, but this range shifted to cooler temperatures as seasonal temperature variation increased (analogous to previous results for diurnal temperature variation). Tropical and sub-tropical cities such as Rio de Janeiro, Fortaleza, and Salvador, Brazil; Cali, Cartagena, and Barranquilla, Colombia; Delhi, India; Guangzhou, China; and Manila, Philippines have mean annual temperatures and seasonal temperature ranges that produced the largest epidemics. However, more temperate cities like Shanghai, China had high epidemic suitability because large seasonal variation offset moderate annual average temperatures. By accounting for seasonal variation in temperature, the model provides a baseline for mechanistically understanding environmental suitability for virus transmission by Aedes aegypti. Overlaying the impact of human activities and socioeconomic factors onto this mechanistic temperature-dependent framework is critical for understanding likelihood and magnitude of outbreaks.
View details for PubMedID 29746468
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PHENOMENOLOGICAL FORECASTING OF DISEASE INCIDENCE USING HETEROSKEDASTIC GAUSSIAN PROCESSES: A DENGUE CASE STUDY
ANNALS OF APPLIED STATISTICS
2018; 12 (1): 27–66
View details for DOI 10.1214/17-AOAS1090
View details for Web of Science ID 000429908100002
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PHENOMENOLOGICAL FORECASTING OF DISEASE INCIDENCE USING HETEROSKEDASTIC GAUSSIAN PROCESSES: A DENGUE CASE STUDY.
The annals of applied statistics
2018; 12 (1): 27-66
Abstract
In 2015 the US federal government sponsored a dengue forecasting competition using historical case data from Iquitos, Peru and San Juan, Puerto Rico. Competitors were evaluated on several aspects of out-of-sample forecasts including the targets of peak week, peak incidence during that week, and total season incidence across each of several seasons. our team was one of the winners of that competition, outperforming other teams in multiple targets/locales. In this paper we report on our methodology, a large component of which, surprisingly, ignores the known biology of epidemics at large-for example, relationships between dengue transmission and environmental factors-and instead relies on flexible nonparametric nonlinear Gaussian process (GP) regression fits that "memorize" the trajectories of past seasons, and then "match" the dynamics of the unfolding season to past ones in real-time. Our phenomenological approach has advantages in situations where disease dynamics are less well understood, or where measurements and forecasts of ancillary covariates like precipitation are unavailable, and/or where the strength of association with cases are as yet unknown. In particular, we show that the GP approach generally outperforms a more classical generalized linear (autoregressive) model (GLM) that we developed to utilize abundant covariate information. We illustrate variations of our method(s) on the two benchmark locales alongside a full summary of results submitted by other contest competitors.
View details for DOI 10.1214/17-aoas1090
View details for PubMedID 38623158
View details for PubMedCentralID PMC11017302
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BUILDING ECOLOGY INTO MODELS TO PREDICT ARBOVIRUS DYNAMICS
AMER SOC TROP MED & HYGIENE. 2018: 63
View details for Web of Science ID 000461386602203
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IMPACTS OF TEMPERATURE ON ZIKA VIRUS TRANSMISSION POTENTIAL
AMER SOC TROP MED & HYGIENE. 2018: 502
View details for Web of Science ID 000461386604294
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TEMPERATURE DRIVES ZIKA VIRUS TRANSMISSION: EVIDENCE FROM EMPIRICAL AND MATHEMATICAL MODELS
AMER SOC TROP MED & HYGIENE. 2018: 23
View details for Web of Science ID 000461386602070
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EFFECTS OF TEMPERATURE ON ZIKA, DENGUE AND CHIKUNGUNYA TRANSMISSION BY AEDES AEGYPTI AND AE-ALBOPICTUS
AMER SOC TROP MED & HYGIENE. 2017: 433–34
View details for Web of Science ID 000412851502902
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Disease ecology, health and the environment: a framework to account for ecological and socio-economic drivers in the control of neglected tropical diseases
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
2017; 372 (1722)
Abstract
Reducing the burden of neglected tropical diseases (NTDs) is one of the key strategic targets advanced by the Sustainable Development Goals. Despite the unprecedented effort deployed for NTD elimination in the past decade, their control, mainly through drug administration, remains particularly challenging: persistent poverty and repeated exposure to pathogens embedded in the environment limit the efficacy of strategies focused exclusively on human treatment or medical care. Here, we present a simple modelling framework to illustrate the relative role of ecological and socio-economic drivers of environmentally transmitted parasites and pathogens. Through the analysis of system dynamics, we show that periodic drug treatments that lead to the elimination of directly transmitted diseases may fail to do so in the case of human pathogens with an environmental reservoir. Control of environmentally transmitted diseases can be more effective when human treatment is complemented with interventions targeting the environmental reservoir of the pathogen. We present mechanisms through which the environment can influence the dynamics of poverty via disease feedbacks. For illustration, we present the case studies of Buruli ulcer and schistosomiasis, two devastating waterborne NTDs for which control is particularly challenging.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.
View details for DOI 10.1098/rstb.2016.0128
View details for PubMedID 28438917
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A novel framework to account for ecological drivers in the control and elimination of environmentally transmitted disease: a modelling study
ELSEVIER SCIENCE INC. 2017: 5
View details for Web of Science ID 000406739900006
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Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models.
PLoS neglected tropical diseases
2017; 11 (4)
Abstract
Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.
View details for DOI 10.1371/journal.pntd.0005568
View details for PubMedID 28448507
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Environmental and Social Change Drive the Explosive Emergence of Zika Virus in the Americas.
PLoS neglected tropical diseases
2017; 11 (2)
Abstract
Since Zika virus (ZIKV) was detected in Brazil in 2015, it has spread explosively across the Americas and has been linked to increased incidence of microcephaly and Guillain-Barré syndrome (GBS). In one year, it has infected over 500,000 people (suspected and confirmed cases) in 40 countries and territories in the Americas. Along with recent epidemics of dengue (DENV) and chikungunya virus (CHIKV), which are also transmitted by Aedes aegypti and Ae. albopictus mosquitoes, the emergence of ZIKV suggests an ongoing intensification of environmental and social factors that have given rise to a new regime of arbovirus transmission. Here, we review hypotheses and preliminary evidence for the environmental and social changes that have fueled the ZIKV epidemic. Potential drivers include climate variation, land use change, poverty, and human movement. Beyond the direct impact of microcephaly and GBS, the ZIKV epidemic will likely have social ramifications for women's health and economic consequences for tourism and beyond.
View details for DOI 10.1371/journal.pntd.0005135
View details for PubMedID 28182667
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Mathematical models are a powerful method to understand and control the spread of Huanglongbing
PEERJ
2016; 4
Abstract
Huanglongbing (HLB), or citrus greening, is a global citrus disease occurring in almost all citrus growing regions. It causes substantial economic burdens to individual growers, citrus industries and governments. Successful management strategies to reduce disease burden are desperately needed but with so many possible interventions and combinations thereof it is difficult to know which are worthwhile or cost-effective. We review how mathematical models have yielded useful insights into controlling disease spread for other vector-borne plant diseases, and the small number of mathematical models of HLB. We adapt a malaria model to HLB, by including temperature-dependent psyllid traits, "flushing" of trees, and economic costs, to show how models can be used to highlight the parameters that require more data collection or that should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We find that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. Also, the best strategy for insecticide intervention is to spray for more days rather than pay extra for a more efficient spray. We conclude that mathematical models are able to provide useful recommendations for managing HLB spread.
View details for DOI 10.7717/peerj.2642
View details for PubMedID 27833809
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A framework for priority effects
JOURNAL OF VEGETATION SCIENCE
2016; 27 (4): 655–57
View details for DOI 10.1111/jvs.12434
View details for Web of Science ID 000379038500001
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The role of competition - colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence
ECOLOGY
2016; 97 (6): 1484-1496
Abstract
Competition - colonization tradeoffs occur in many systems, and theory predicts that they can strongly promote species coexistence. However, there is little empirical evidence that observed competition - colonization tradeoffs are strong enough to maintain diversity in natural systems. This is due in part to a mismatch between theoretical assumptions and biological reality in some systems. We tested whether a competition - colonization tradeoff explains how a diverse trematode guild coexists in California horn snail populations, a system that meets the requisite criteria for the tradeoff to promote coexistence. A field experiment showed that subordinate trematode species tended to have higher colonization rates than dominant species. This tradeoff promoted coexistence in parameterized models but did not fully explain trematode diversity and abundance, suggesting a role of additional diversity maintenance mechanisms. Spatial heterogeneity is an alternative way to promote coexistence if it isolates competing species. We used scale transition theory to expand the competition - colonization tradeoff model to include spatial variation. The parameterized model showed that spatial variation in trematode prevalence did not isolate most species sufficiently to explain the overall high diversity, but could benefit some rare species. Together, the results suggest that several mechanisms combine to maintain diversity, even when a competition - colonization tradeoff occurs.
View details for DOI 10.1890/15-0753.1
View details for Web of Science ID 000377219900012
View details for PubMedID 27459779
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The role of competition - colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence.
Ecology
2016; 97 (6): 1484-1496
Abstract
Competition - colonization tradeoffs occur in many systems, and theory predicts that they can strongly promote species coexistence. However, there is little empirical evidence that observed competition- colonization tradeoffs are strong enough to maintain diversity in natural systems. This is due in part to a mismatch between theoretical assumptions and biological reality in some systems. We tested whether a competition - colonization tradeoff explains how a diverse trematode guild coexists in California horn snail populations, a system that meets the requisite criteria for the tradeoff to promote coexistence. A field experiment showed that subordinate trematode species tended to have higher colonization rates than dominant species. This tradeoff promoted coexistence in parameterized models but did not fully explain trematode diversity and abundance, suggesting a role of additional diversity maintenance mechanisms. Spatial heterogeneity is an alternative way to promote coexistence if it isolates competing species. We used scale transition theory to expand the competition - colonization tradeoff model to include spatial variation. The parameterized model showed that spatial variation in trematode prevalence did not isolate most species sufficiently to explain the overall high diversity, but could benefit some rare species. Together, the results suggest that several mechanisms combine to maintain diversity, even when a competition - colonization tradeoff occurs.
View details for DOI 10.1890/15-0753.1
View details for PubMedID 27859218
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The role of drought- and disturbance-mediated competition in shaping community responses to varied environments
OECOLOGIA
2016; 181 (2): 621-632
Abstract
By altering the strength of intra- and interspecific competition, droughts may reshape plant communities. Furthermore, species may respond differently to drought when other influences, such as herbivory, are considered. To explore this relationship, we conducted a greenhouse experiment measuring responses to inter- and intraspecific competition for two grasses, Schedonorus arundinaceus and Paspalum dilatatum, while varying water availability and simulating herbivory via clipping. We then parameterized population growth models to examine the long-term outcome of competition under these conditions. Under drought, S. arundinaceus was less water stressed than P. dilatatum, which exhibited severe water stress; clipping alleviated this stress, increasing the competitive ability of P. dilatatum relative to S. arundinaceus. Although P. dilatatum competed weakly under drought, clipping reduced water stress in P. dilatatum, thereby enhancing its ability to compete with S. arundinaceus under drought. Supporting these observations, population growth models predicted that P. dilatatum would exclude S. arundinaceus when clipped under drought, while S. arundinaceus would exclude P. dilatatum when unclipped under drought. When the modeled environment varied temporally, environmental variation promoted niche differences that, though insufficient to maintain stable coexistence, prevented unconditional competitive exclusion by promoting priority effects. Our results suggest that it is important to consider how species respond not just to stable, but also to variable, environments. When species differ in their responses to drought, competition, and simulated herbivory, stable environments may promote competitive exclusion, while fluctuating environments may promote coexistence. These interactions are critical to understanding how species will respond to global change.
View details for DOI 10.1007/s00442-016-3582-9
View details for PubMedID 26893230
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The rise and fall of infectious disease in a warmer world.
F1000Research
2016; 5
Abstract
Now-outdated estimates proposed that climate change should have increased the number of people at risk of malaria, yet malaria and several other infectious diseases have declined. Although some diseases have increased as the climate has warmed, evidence for widespread climate-driven disease expansion has not materialized, despite increased research attention. Biological responses to warming depend on the non-linear relationships between physiological performance and temperature, called the thermal response curve. This leads performance to rise and fall with temperature. Under climate change, host species and their associated parasites face extinction if they cannot either thermoregulate or adapt by shifting phenology or geographic range. Climate change might also affect disease transmission through increases or decreases in host susceptibility and infective stage (and vector) production, longevity, and pathology. Many other factors drive disease transmission, especially economics, and some change in time along with temperature, making it hard to distinguish whether temperature drives disease or just correlates with disease drivers. Although it is difficult to predict how climate change will affect infectious disease, an ecological approach can help meet the challenge.
View details for DOI 10.12688/f1000research.8766.1
View details for PubMedID 27610227
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Within-Host Niche Differences and Fitness Trade-offs Promote Coexistence of Plant Viruses
AMERICAN NATURALIST
2016; 187 (1): E13-E26
Abstract
Pathogens live in diverse, competitive communities, yet the processes that maintain pathogen diversity remain elusive. Here, we use a species-rich, well-studied plant virus system, the barley yellow dwarf viruses, to examine the mechanisms that regulate pathogen diversity. We empirically parameterized models of three viruses, their two aphid vectors, and one perennial grass host. We found that high densities of both aphids maximized virus diversity and that competition limited the coexistence of two closely related viruses. Even limited ability to simultaneously infect (coinfect) host individuals strongly promoted virus coexistence; preventing coinfection led to priority effects. Coinfection generated stabilizing niche differences by allowing viruses to share hosts. However, coexistence also required trade-offs between vector generalist and specialist life-history strategies. Our predicted outcomes broadly concur with previous field observations. These results show how competition within individual hosts and vectors may lead to unexpected population-level outcomes between pathogens, including coexistence, competitive exclusion, and priority effects, and how contemporary coexistence theory can help to predict these outcomes.
View details for DOI 10.1086/684114
View details for Web of Science ID 000368559300002
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Mapping Physiological Suitability Limits for Malaria in Africa Under Climate Change
VECTOR-BORNE AND ZOONOTIC DISEASES
2015; 15 (12): 718-725
Abstract
We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control.
View details for DOI 10.1089/vbz.2015.1822
View details for PubMedID 26579951
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Controls over native perennial grass exclusion and persistence in California grasslands invaded by annuals
ECOLOGY
2015; 96 (10): 2643-2652
Abstract
Despite obvious impacts of nonnative species in many ecosystems, the long-term outcome of competition between native and exotic species often remains unclear. Demographic models can resolve the outcome of competition between native and exotic species and provide insight into conditions favoring exclusion vs. coexistence. California grasslands are one of the most heavily invaded ecosystems in North America. Although California native perennial bunchgrasses are thought to be restricted to a fraction of their original abundance, the eventual outcome of competition with invasive European annual grasses at a local scale (competitive exclusion, stable persistence, or priority effects) remains unresolved. Here, we used a two-species discrete time population growth model to predict the outcome of competition between exotic annual and native perennial grasses in California, and to determine the demographic traits responsible for the outcome. The model is parameterized with empirical data from several field experiments. We found that, once introduced, annual grasses persist stably with little uncertainty. Although perennial grasses are competitively excluded on average, the most likely range of model predictions also includes stable coexistence with annual grasses. As for many other perennial plants, native bunchgrass population growth is highly sensitive to the survival of adults. Management interventions that improve perennial adult survival are likely to be more effective than those that reduce exotic annual seed production or establishment, reduce competition, or increase perennial seedling establishment. Further empirical data on summer survival of bunchgrass adults and competitive effects of annuals on perennials would most improve model predictions because they contribute most to the uncertainty in the predicted outcome for the perennial grass. This work demonstrates how demographic approaches can clarify the outcome of competition between native and exotic species, identify key targets for future empirical work, and predict the effectiveness of management interventions. Such studies are critical both for understanding the impacts of invasion and for targeting management responses that maximize the benefit to native species.
View details for DOI 10.1890/14-2023.1.sm
View details for Web of Science ID 000362853600009
View details for PubMedID 26649386
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Differential Impacts of Virus Diversity on Biomass Production of a Native and an Exotic Grass Host
PLOS ONE
2015; 10 (7)
Abstract
Pathogens are common and diverse in natural communities and have been implicated in the success of host invasions. Yet few studies have experimentally measured how pathogens impact native versus exotic hosts, particularly when individual hosts are simultaneously coinfected by diverse pathogens. To estimate effects of interactions among multiple pathogens within host individuals on both transmission of pathogens and fitness consequences for hosts, we conducted a greenhouse experiment using California grassland species: the native perennial grass Nassella (Stipa) pulchra, the exotic annual grass Bromus hordeaceus, and three virus species, Barley yellow dwarf virus-PAV, Barley yellow dwarf virus-MAV, and Cereal yellow dwarf virus-RPV. In terms of virus transmission, the native host was less susceptible than the exotic host to MAV. Coinfection of PAV and MAV did not occur in any of the 157 co-inoculated native host plants. In the exotic host, PAV infection most strongly reduced root and shoot biomass, and coinfections that included PAV severely reduced biomass. Infection with single or multiple viruses did not affect biomass in the native host. However, in this species the most potentially pathogenic coinfections (PAV + MAV and PAV + MAV + RPV) did not occur. Together, these results suggest that interactions among multiple pathogens can have important consequences for host health, which may not be predictable from interactions between hosts and individual pathogens. This work addresses a key empirical gap in understanding the impact of multiple generalist pathogens on competing host species, with potential implications for population and community dynamics of native and exotic species. It also demonstrates how pathogens with relatively mild impacts independently can more substantially reduce host performance in coinfection.
View details for DOI 10.1371/journal.pone.0134355
View details for PubMedID 26230720
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Pathogen impacts on plant diversity in variable environments
OIKOS
2015; 124 (4): 414-420
View details for DOI 10.1111/oik.01328
View details for Web of Science ID 000352240500004
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The community ecology of pathogens: coinfection, coexistence and community composition
ECOLOGY LETTERS
2015; 18 (4): 401-415
Abstract
Disease and community ecology share conceptual and theoretical lineages, and there has been a resurgence of interest in strengthening links between these fields. Building on recent syntheses focused on the effects of host community composition on single pathogen systems, we examine pathogen (microparasite) communities using a stochastic metacommunity model as a starting point to bridge community and disease ecology perspectives. Such models incorporate the effects of core community processes, such as ecological drift, selection and dispersal, but have not been extended to incorporate host-pathogen interactions, such as immunosuppression or synergistic mortality, that are central to disease ecology. We use a two-pathogen susceptible-infected (SI) model to fill these gaps in the metacommunity approach; however, SI models can be intractable for examining species-diverse, spatially structured systems. By placing disease into a framework developed for community ecology, our synthesis highlights areas ripe for progress, including a theoretical framework that incorporates host dynamics, spatial structuring and evolutionary processes, as well as the data needed to test the predictions of such a model. Our synthesis points the way for this framework and demonstrates that a deeper understanding of pathogen community dynamics will emerge from approaches working at the interface of disease and community ecology.
View details for DOI 10.1111/ele.12418
View details for Web of Science ID 000351619500009
View details for PubMedID 25728488
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Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach
ECOLOGY
2015; 96 (1): 203-213
Abstract
Extrinsic environmental factors influence the distribution and population dynamics of many organisms, including insects that are of concern for human health and agriculture. This is particularly true for vector-borne infectious diseases like malaria, which is a major source of morbidity and mortality in humans. Understanding the mechanistic links between environment and population processes for these diseases is key to predicting the consequences of climate change on transmission and for developing effective interventions. An important measure of the intensity of disease transmission is the reproductive number R0. However, understanding the mechanisms linking R0 and temperature, an environmental factor driving disease risk, can be challenging because the data available for parameterization are often poor. To address this, we show how a Bayesian approach can help identify critical uncertainties in components of R0 and how this uncertainty is propagated into the estimate of R0. Most notably, we find that different parameters dominate the uncertainty at different temperature regimes: bite rate from 15 degrees C to 25 degrees C; fecundity across all temperatures, but especially approximately 25-32 degrees C; mortality from 20 degrees C to 30 degrees C; parasite development rate at degrees 15-16 degrees C and again at approximately 33-35 degrees C. Focusing empirical studies on these parameters and corresponding temperature ranges would be the most efficient way to improve estimates of R0. While we focus on malaria, our methods apply to improving process-based models more generally, including epidemiological, physiological niche, and species distribution models.
View details for DOI 10.1890/13-1964.1
View details for Web of Science ID 000349198900023
View details for PubMedID 26236905
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Despite spillover, a shared pathogen promotes native plant persistence in a cheatgrass-invaded grassland
ECOLOGY
2013; 94 (12): 2744-2753
Abstract
How pathogen spillover influences host community diversity and composition is poorly understood. Spillover occurs when transmission from a reservoir host species drives infection in another host species. In cheatgrass-invaded grasslands in the western United States, a fungal seed pathogen, black fingers of death (Pyrenophora semeniperda), spills over from exotic cheatgrass (Bromus tectorum) to native perennial bunchgrasses such as squirreltail (Elymus elymoides). Previous theoretical work based on this system predicts that pathogens that spill over can favor either host coexistence, the exclusion of either host species, or priority effects, depending on species-specific transmission rates and pathogen tolerance. Here, these model predictions were tested by parameterizing a population growth model with field data from Skull Valley, Utah, USA. The model suggests that, across the observed range of demographic variation, the pathogen is most likely to provide a net benefit to squirreltail and a net cost to cheatgrass, though both effects are relatively weak. Although cheatgrass (the reservoir host) is more tolerant, squirreltail is far less susceptible to infection, and its long-lived adult stage buffers population growth against seed losses to the pathogen. This work shows that, despite pathogen spillover, the shared pathogen promotes native grass persistence by reducing exotic grass competition. Counterintuitively, the reservoir host does not necessarily benefit from the presence of the pathogen, and may even suffer greater costs than the nonreservoir host. Understanding the consequences of shared pathogens for host communities requires weighing species differences in susceptibility, transmission, and tolerance using quantitative models.
View details for DOI 10.1890/13-0086.1
View details for Web of Science ID 000328928300009
View details for PubMedID 24597221
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Consequences of Pathogen Spillover for Cheatgrass-Invaded Grasslands: Coexistence, Competitive Exclusion, or Priority Effects
AMERICAN NATURALIST
2013; 181 (6): 737-747
Abstract
With the rise in species invasions and emerging infectious diseases, pathogen spillover from abundant reservoir hosts to their competitors is increasingly common. Although the potential for pathogen spillover is widespread, its consequences for host community composition remain poorly understood. To address this gap, I examine the consequences of fungal seed pathogen spillover from an exotic annual grass (cheatgrass) to a native perennial bunchgrass in the Intermountain West, United States, using a model. Integrating generalist pathogens with broader coexistence theory, the model measures the pathogen's effect on host niche differences and fitness differences, which determine the outcome of competition. The model demonstrates that the consequences of pathogen spillover depend on host differences in species-specific transmission and disease tolerance. Counterintuitively, spillover can lead to coexistence, native grass exclusion, or priority effects, in which either species can exclude the other when initially more dominant. Cheatgrass has higher tolerance for infection, which could lead to competitive dominance or to coexistence if the native grass has a fecundity or survival advantage. In sum, multihost pathogens can affect host communities in a range of ways, depending on the specific mechanism of spillover.
View details for DOI 10.1086/670190
View details for Web of Science ID 000318996500004
View details for PubMedID 23669537
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Optimal temperature for malaria transmission is dramatically lower than previously predicted
ECOLOGY LETTERS
2013; 16 (1): 22-30
Abstract
The ecology of mosquito vectors and malaria parasites affect the incidence, seasonal transmission and geographical range of malaria. Most malaria models to date assume constant or linear responses of mosquito and parasite life-history traits to temperature, predicting optimal transmission at 31 °C. These models are at odds with field observations of transmission dating back nearly a century. We build a model with more realistic ecological assumptions about the thermal physiology of insects. Our model, which includes empirically derived nonlinear thermal responses, predicts optimal malaria transmission at 25 °C (6 °C lower than previous models). Moreover, the model predicts that transmission decreases dramatically at temperatures > 28 °C, altering predictions about how climate change will affect malaria. A large data set on malaria transmission risk in Africa validates both the 25 °C optimum and the decline above 28 °C. Using these more accurate nonlinear thermal-response models will aid in understanding the effects of current and future temperature regimes on disease transmission.
View details for DOI 10.1111/ele.12015
View details for Web of Science ID 000312301300003
View details for PubMedID 23050931
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Soil Moisture and Fungi Affect Seed Survival in California Grassland Annual Plants
PLOS ONE
2012; 7 (6)
Abstract
Survival of seeds in the seed bank is important for the population dynamics of many plant species, yet the environmental factors that control seed survival at a landscape level remain poorly understood. These factors may include soil moisture, vegetation cover, soil type, and soil pathogens. Because many soil fungi respond to moisture and host species, fungi may mediate environmental drivers of seed survival. Here, I measure patterns of seed survival in California annual grassland plants across 15 species in three experiments. First, I surveyed seed survival for eight species at 18 grasslands and coastal sage scrub sites ranging across coastal and inland Santa Barbara County, California. Species differed in seed survival, and soil moisture and geographic location had the strongest influence on survival. Grasslands had higher survival than coastal sage scrub sites for some species. Second, I used a fungicide addition and exotic grass thatch removal experiment in the field to tease apart the relative impact of fungi, thatch, and their interaction in an invaded grassland. Seed survival was lower in the winter (wet season) than in the summer (dry season), but fungicide improved winter survival. Seed survival varied between species but did not depend on thatch. Third, I manipulated water and fungicide in the laboratory to directly examine the relationship between water, fungi, and survival. Seed survival declined from dry to single watered to continuously watered treatments. Fungicide slightly improved seed survival when seeds were watered once but not continually. Together, these experiments demonstrate an important role of soil moisture, potentially mediated by fungal pathogens, in driving seed survival.
View details for DOI 10.1371/journal.pone.0039083
View details for Web of Science ID 000305340000065
View details for PubMedID 22720037
View details for PubMedCentralID PMC3373626
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Pathogen impacts on plant communities: unifying theory, concepts, and empirical work
ECOLOGICAL MONOGRAPHS
2011; 81 (3): 429-441
View details for Web of Science ID 000293457300003
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Competition-defense tradeoffs and the maintenance of plant diversity
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2010; 107 (40): 17217-17222
Abstract
Ecologists have long observed that consumers can maintain species diversity in communities of their prey. Many theories of how consumers mediate diversity invoke a tradeoff between species' competitive ability and their ability to withstand predation. Under this constraint, the best competitors are also most susceptible to consumers, preventing them from excluding other species. However, empirical evidence for competition-defense tradeoffs is limited and, as such, the mechanisms by which consumers regulate diversity remain uncertain. We performed a meta-analysis of 36 studies to evaluate the prevalence of the competition-defense tradeoff and its role in maintaining diversity in plant communities. We quantified species' responses to experimental resource addition and consumer removal as estimates of competitive ability and resistance to consumers, respectively. With this analysis, we found mixed empirical evidence for a competition-defense tradeoff; in fact, competitive ability tended to be weakly positively correlated with defense overall. However, when present, negative relationships between competitive ability and defense influenced species diversity in the manner predicted by theory. In the minority of communities for which a tradeoff was detected, species evenness was higher, and resource addition and consumer removal reduced diversity. Our analysis reframes the commonly held notion that consumers structure plant communities through a competition-defense tradeoff. Such a tradeoff can maintain diversity when present, but negative correlations between competitive ability and defense were less common than is often assumed. In this respect, this study supports an emerging theoretical paradigm in which predation interacts with competition to both enhance and reduce species diversity.
View details for DOI 10.1073/pnas.1007745107
View details for Web of Science ID 000282512000032
View details for PubMedID 20855605
View details for PubMedCentralID PMC2951440
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Soil moisture mediated interaction between Polygonatum biflorum and leaf spot disease
PLANT ECOLOGY
2010; 209 (1): 1-9
View details for DOI 10.1007/s11258-009-9713-1
View details for Web of Science ID 000278411400001
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Parasites in food webs: the ultimate missing links
ECOLOGY LETTERS
2008; 11 (6): 533-546
Abstract
Parasitism is the most common consumer strategy among organisms, yet only recently has there been a call for the inclusion of infectious disease agents in food webs. The value of this effort hinges on whether parasites affect food-web properties. Increasing evidence suggests that parasites have the potential to uniquely alter food-web topology in terms of chain length, connectance and robustness. In addition, parasites might affect food-web stability, interaction strength and energy flow. Food-web structure also affects infectious disease dynamics because parasites depend on the ecological networks in which they live. Empirically, incorporating parasites into food webs is straightforward. We may start with existing food webs and add parasites as nodes, or we may try to build food webs around systems for which we already have a good understanding of infectious processes. In the future, perhaps researchers will add parasites while they construct food webs. Less clear is how food-web theory can accommodate parasites. This is a deep and central problem in theoretical biology and applied mathematics. For instance, is representing parasites with complex life cycles as a single node equivalent to representing other species with ontogenetic niche shifts as a single node? Can parasitism fit into fundamental frameworks such as the niche model? Can we integrate infectious disease models into the emerging field of dynamic food-web modelling? Future progress will benefit from interdisciplinary collaborations between ecologists and infectious disease biologists.
View details for DOI 10.1111/j.1461-0248.2008.01174.x
View details for Web of Science ID 000255552100001
View details for PubMedID 18462196
View details for PubMedCentralID PMC2408649