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.
Assistant Professor, Biology
Center Fellow (By courtesy), Stanford Woods Institute for the Environment
Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
Honors & Awards
Leading Interdisciplinary Collaborations Fellow, Woods Institute for the Environment, Stanford University (2018-2019)
Early Career Fellow, Ecological Society of America (2019)
Walter J. Gores Award for Teaching, Stanford University (2019)
Boards, Advisory Committees, Professional Organizations
Affiliate, Woods Institute for the Environment (2018 - Present)
Editorial Advisory Board Member, Lancet Planetary Health (2019 - Present)
Member, Jasper Ridge Faculty Advisory Committee (2015 - Present)
Associate Editor, Ecology Letters (2019 - Present)
Faculty Fellow, Center for Innovation in Global Health (2015 - Present)
Faculty Fellow, King Center on Global Development (2019 - Present)
B.S., University of Georgia, Honors Interdisciplinary Studies in Mathematical Biology (2007)
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.
- Ecology and Evolution of Infectious Disease in a Changing World
BIO 2N (Spr)
Independent Studies (8)
- Advanced Research Laboratory in Experimental Biology
BIO 199 (Aut, Win, Spr, Sum)
- Directed Reading in Biology
BIO 198 (Aut, Win, Spr)
- Directed Reading in Environment and Resources
ENVRES 398 (Win, Spr, Sum)
- Directed Research in Environment and Resources
ENVRES 399 (Aut, Win, Spr, Sum)
- Graduate Research
BIO 300 (Aut, Win, Spr, Sum)
- Honors Program in Earth Systems
EARTHSYS 199 (Win)
- Out-of-Department Graduate Research
BIO 300X (Sum)
- Teaching Practicum in Biology
BIO 290 (Win)
- Advanced Research Laboratory in Experimental Biology
Prior Year Courses
- Ecology and Evolution of Infectious Disease in a Changing World
BIO 2N (Spr)
- Introduction to Ecology
BIO 81 (Aut)
- Introduction to Ecology
BIO 81 (Aut)
- Ecology and Evolution of Infectious Disease in a Changing World
Doctoral Dissertation Reader (AC)
Glade Dlott, Jessica Martin, Magdalena Warren
Postdoctoral Faculty Sponsor
Alexander Becker, Caroline Glidden, Morgan Kain, Eloise Skinner
Doctoral Dissertation Advisor (AC)
Lisa Couper, Isabel Delwel, Mallory Harris, Nicole Nova
Marissa Childs, Mallory Harris, Nicole Nova
Graduate and Fellowship Programs
Biology (School of Humanities and Sciences) (Phd Program)
The influence of vector-borne disease on human history: socio-ecological mechanisms.
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
Climate predicts geographic and temporal variation in mosquito-borne disease dynamics on two continents.
2021; 12 (1): 1233
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
Chopping the tail: How preventing superspreading can help to maintain COVID-19 control.
2020; 34: 100430
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
Susceptible host availability modulates climate effects on dengue dynamics.
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
- Habitat type and interannual variation shape unique fungal pathogen communities on a California native bunchgrass FUNGAL ECOLOGY 2020; 48
Impact of prior and projected climate change on US Lyme disease incidence.
Global change biology
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
- Native perennial and non-native annual grasses shape pathogen community composition and disease severity in a California grassland JOURNAL OF ECOLOGY 2020
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
The Role of Vector Trait Variation in Vector-Borne Disease Dynamics.
Frontiers in ecology and evolution
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
Habitat type and interannual variation shape unique fungal pathogen communities on a California native bunchgrass.
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
Climate change could shift disease burden from malaria to arboviruses in Africa.
The Lancet. Planetary health
2020; 4 (9): e416–e423
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
Transmission of West Nile and five other temperate mosquito-borne viruses peaks at temperatures between 23°C and 26°C.
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
Warming temperatures could expose more than 1.3 billion new people to Zika virus risk by 2050.
Global change biology
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
Chopping the tail: how preventing superspreading can help to maintain COVID-19 control.
medRxiv : the preprint server for health sciences
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
- 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
Towards common ground in the biodiversity-disease debate.
Nature ecology & evolution
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
An open challenge to advance probabilistic forecasting for dengue epidemics.
Proceedings of the National Academy of Sciences of the United States of America
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
Amazon deforestation drives malaria transmission, and malaria burden reduces forest clearing.
Proceedings of the National Academy of Sciences of the United States of America
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
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
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
- Dynamic and integrative approaches to understanding pathogen spillover. Philosophical transactions of the Royal Society of London. Series B, Biological sciences 2019; 374 (1782): 20190014
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
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
Thermal biology of mosquito-borne disease.
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
- A global test of ecoregions (vol 2, pg 1889, 2018) NATURE ECOLOGY & EVOLUTION 2019; 3 (4): 708
Author Correction: A global test of ecoregions.
Nature ecology & evolution
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
- Global expansion and redistribution of Aedes-borne virus transmission risk with climate change PLOS NEGLECTED TROPICAL DISEASES 2019; 13 (3)
Priority Effects and Nonhierarchical Competition Shape Species Composition in a Complex Grassland Community
2019; 193 (2): 213–26
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
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
Climate drives spatial variation in Zika epidemics in Latin America.
Proceedings. Biological sciences
2019; 286 (1909): 20191578
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
Global expansion and redistribution of Aedes-borne virus transmission risk with climate change.
PLoS neglected tropical diseases
2019; 13 (3): e0007213
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
Malaria smear positivity among Kenyan children peaks at intermediate temperatures as predicted by ecological models.
Parasites & vectors
2019; 12 (1): 288
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
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
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
TEMPERATURE DRIVES MALARIA TRANSMISSION: IMPLICATIONS FOR DISEASE CONTROL
AMER SOC TROP MED & HYGIENE. 2019: 472
View details for Web of Science ID 000507364504251
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
- A global test of ecoregions NATURE ECOLOGY & EVOLUTION 2018; 2 (12): 1889–96
A global test of ecoregions.
Nature ecology & evolution
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
- Foliar pathogens are unlikely to stabilize coexistence of competing species in a California grassland ECOLOGY 2018; 99 (10): 2250–59
Foliar pathogens are unlikely to stabilize coexistence of competing species in a California grassland.
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
Temperature explains broad patterns of Ross River virus transmission.
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
- Temperature explains broad patterns of Ross River virus transmission ELIFE 2018; 7
Temperature drives Zika virus transmission: evidence from empirical and mathematical models
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
2018; 285 (2884)
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
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
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
Seasonal temperature variation influences climate suitability for dengue, chikungunya, and Zika transmission
PLOS NEGLECTED TROPICAL DISEASES
2018; 12 (5): e0006451
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
- PHENOMENOLOGICAL FORECASTING OF DISEASE INCIDENCE USING HETEROSKEDASTIC GAUSSIAN PROCESSES: A DENGUE CASE STUDY ANNALS OF APPLIED STATISTICS 2018; 12 (1): 27–66
BUILDING ECOLOGY INTO MODELS TO PREDICT ARBOVIRUS DYNAMICS
AMER SOC TROP MED & HYGIENE. 2018: 63
View details for Web of Science ID 000461386602203
IMPACTS OF TEMPERATURE ON ZIKA VIRUS TRANSMISSION POTENTIAL
AMER SOC TROP MED & HYGIENE. 2018: 502
View details for Web of Science ID 000461386604294
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
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
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)
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
Detecting the impact of temperature on transmission of Zika, dengue, and chikungunya using mechanistic models.
PLoS neglected tropical diseases
2017; 11 (4)
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
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
Environmental and Social Change Drive the Explosive Emergence of Zika Virus in the Americas.
PLoS neglected tropical diseases
2017; 11 (2)
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
Mathematical models are a powerful method to understand and control the spread of Huanglongbing
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
- A framework for priority effects JOURNAL OF VEGETATION SCIENCE 2016; 27 (4): 655–57
The role of competition - colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence
2016; 97 (6): 1484-1496
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
The role of drought- and disturbance-mediated competition in shaping community responses to varied environments
2016; 181 (2): 621-632
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
The rise and fall of infectious disease in a warmer world.
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
The role of competition - colonization tradeoffs and spatial heterogeneity in promoting trematode coexistence.
2016; 97 (6): 1484–96
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 PubMedID 27859218
Within-Host Niche Differences and Fitness Trade-offs Promote Coexistence of Plant Viruses
2016; 187 (1): E13-E26
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
Mapping Physiological Suitability Limits for Malaria in Africa Under Climate Change
VECTOR-BORNE AND ZOONOTIC DISEASES
2015; 15 (12): 718-725
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
Controls over native perennial grass exclusion and persistence in California grasslands invaded by annuals
2015; 96 (10): 2643-2652
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
Differential Impacts of Virus Diversity on Biomass Production of a Native and an Exotic Grass Host
2015; 10 (7)
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
- Pathogen impacts on plant diversity in variable environments OIKOS 2015; 124 (4): 414-420
The community ecology of pathogens: coinfection, coexistence and community composition
2015; 18 (4): 401-415
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
Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach
2015; 96 (1): 203-213
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
Despite spillover, a shared pathogen promotes native plant persistence in a cheatgrass-invaded grassland
2013; 94 (12): 2744-2753
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
Consequences of Pathogen Spillover for Cheatgrass-Invaded Grasslands: Coexistence, Competitive Exclusion, or Priority Effects
2013; 181 (6): 737-747
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
Optimal temperature for malaria transmission is dramatically lower than previously predicted
2013; 16 (1): 22-30
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
Soil Moisture and Fungi Affect Seed Survival in California Grassland Annual Plants
2012; 7 (6)
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
Pathogen impacts on plant communities: unifying theory, concepts, and empirical work
2011; 81 (3): 429-441
View details for Web of Science ID 000293457300003
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
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
- Soil moisture mediated interaction between Polygonatum biflorum and leaf spot disease PLANT ECOLOGY 2010; 209 (1): 1-9
Parasites in food webs: the ultimate missing links
2008; 11 (6): 533-546
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