Honors & Awards


  • Samuel Karlin Prize in Mathematical Biology, Stanford University (2021)
  • ARCS Fellowship, Stanford University (2020-2021)
  • Stanford Graduate Fellowship, Stanford University (2016-2019)

Professional Education


  • Bachelor of Science, University of Kentucky, Biology, Math, Chemistry (2016)
  • Doctor of Philosophy, Stanford University, BIO-PHD (2022)
  • B.S. Hons, University of Kentucky, Chemistry (2016)
  • B.S. Hons, University of Kentucky, Mathematics (2016)
  • B.S. Hons, University of Kentucky, Biology (2016)

Stanford Advisors


All Publications


  • Modeling the efficacy of CRISPR gene drive for snail immunity on schistosomiasis control. PLoS neglected tropical diseases Grewelle, R. E., Perez-Saez, J., Tycko, J., Namigai, E. K., Rickards, C. G., De Leo, G. A. 2022; 16 (10): e0010894

    Abstract

    CRISPR gene drives could revolutionize the control of infectious diseases by accelerating the spread of engineered traits that limit parasite transmission in wild populations. Gene drive technology in mollusks has received little attention despite the role of freshwater snails as hosts of parasitic flukes causing 200 million annual cases of schistosomiasis. A successful drive in snails must overcome self-fertilization, a common feature of host snails which could prevents a drive's spread. Here we developed a novel population genetic model accounting for snails' mixed mating and population dynamics, susceptibility to parasite infection regulated by multiple alleles, fitness differences between genotypes, and a range of drive characteristics. We integrated this model with an epidemiological model of schistosomiasis transmission to show that a snail population modification drive targeting immunity to infection can be hindered by a variety of biological and ecological factors; yet under a range of conditions, disease reduction achieved by chemotherapy treatment of the human population can be maintained with a drive. Alone a drive modifying snail immunity could achieve significant disease reduction in humans several years after release. These results indicate that gene drives, in coordination with existing public health measures, may become a useful tool to reduce schistosomiasis burden in selected transmission settings with effective CRISPR construct design and evaluation of the genetic and ecological landscape.

    View details for DOI 10.1371/journal.pntd.0010894

    View details for PubMedID 36315503

  • Statistical Bliss: A novel framework for statistical assessment of drug synergy. Grewelle, R. E., Wilson, K. L., Brantley-Sieders, D. M. AMER ASSOC CANCER RESEARCH. 2021
  • Redefining risk in data-poor fisheries FISH AND FISHERIES Grewelle, R. E., Mansfield, E., Micheli, F., De Leo, G. 2021

    View details for DOI 10.1111/faf.12561

    View details for Web of Science ID 000648025600001

  • Data-Poor Ecological Risk Assessment of Multiple Stressors Grewelle, R. E., Mansfield, E., Micheli, F., De Leo, G. A. BioRxiv. 2021
  • Models with environmental drivers offer a plausible mechanism for the rapid spread of infectious disease outbreaks in marine organisms. Scientific reports Aalto, E. A., Lafferty, K. D., Sokolow, S. H., Grewelle, R. E., Ben-Horin, T., Boch, C. A., Raimondi, P. T., Bograd, S. J., Hazen, E. L., Jacox, M. G., Micheli, F., De Leo, G. A. 2020; 10 (1): 5975

    Abstract

    The first signs of sea star wasting disease (SSWD) epidemic occurred in just few months in 2013 along the entire North American Pacific coast. Disease dynamics did not manifest as the typical travelling wave of reaction-diffusion epidemiological model, suggesting that other environmental factors might have played some role. To help explore how external factors might trigger disease, we built a coupled oceanographic-epidemiological model and contrasted three hypotheses on the influence of temperature on disease transmission and pathogenicity. Models that linked mortality to sea surface temperature gave patterns more consistent with observed data on sea star wasting disease, which suggests that environmental stress could explain why some marine diseases seem to spread so fast and have region-wide impacts on host populations.

    View details for DOI 10.1038/s41598-020-62118-4

    View details for PubMedID 32249775

  • Estimating the Global Infection Fatality Rate of COVID-19 Grewelle, R. E., De Leo, G. A. MedRxiv. 2020

    Abstract

    COVID-19 has become a global pandemic, resulting in nearly three hundred thousand deaths distributed heterogeneously across countries. Estimating the infection fatality rate (IFR) has been elusive due to the presence of asymptomatic or mildly symptomatic infections and lack of testing capacity. We analyze global data to derive the IFR of COVID-19. Estimates of COVID-19 IFR in each country or locality differ due to variable sampling regimes, demographics, and healthcare resources. We present a novel statistical approach based on sampling effort and the reported case fatality rate of each country. The asymptote of this function gives the global IFR. Applying this asymptotic estimator to cumulative COVID-19 data from 139 countries reveals a global IFR of 1.04% (CI: 0.77%,1.38%). Deviation of countries' reported CFR from the estimator does not correlate with demography or per capita GDP, suggesting variation is due to differing testing regimes or reporting guidelines by country. Estimates of IFR through seroprevalence studies and point estimates from case studies or sub-sampled populations are limited by sample coverage and cannot inform a global IFR, as mortality is known to vary dramatically by age and treatment availability. Our estimated IFR aligns with many previous estimates and is the first attempt at a global estimate of COVID-19 IFR.

  • Larger viral genome size facilitates emergence of zoonotic diseases Grewelle, R. E. BioRxiv. 2020
  • Gene drives for schistosomiasis transmission control. PLoS neglected tropical diseases Maier, T. n., Wheeler, N. J., Namigai, E. K., Tycko, J. n., Grewelle, R. E., Woldeamanuel, Y. n., Klohe, K. n., Perez-Saez, J. n., Sokolow, S. H., De Leo, G. A., Yoshino, T. P., Zamanian, M. n., Reinhard-Rupp, J. n. 2019; 13 (12): e0007833

    Abstract

    Schistosomiasis is one of the most important and widespread neglected tropical diseases (NTD), with over 200 million people infected in more than 70 countries; the disease has nearly 800 million people at risk in endemic areas. Although mass drug administration is a cost-effective approach to reduce occurrence, extent, and severity of the disease, it does not provide protection to subsequent reinfection. Interventions that target the parasites' intermediate snail hosts are a crucial part of the integrated strategy required to move toward disease elimination. The recent revolution in gene drive technology naturally leads to questions about whether gene drives could be used to efficiently spread schistosome resistance traits in a population of snails and whether gene drives have the potential to contribute to reduced disease transmission in the long run. Responsible implementation of gene drives will require solutions to complex challenges spanning multiple disciplines, from biology to policy. This Review Article presents collected perspectives from practitioners of global health, genome engineering, epidemiology, and snail/schistosome biology and outlines strategies for responsible gene drive technology development, impact measurements of gene drives for schistosomiasis control, and gene drive governance. Success in this arena is a function of many factors, including gene-editing specificity and efficiency, the level of resistance conferred by the gene drive, how fast gene drives may spread in a metapopulation over a complex landscape, ecological sustainability, social equity, and, ultimately, the reduction of infection prevalence in humans. With combined efforts from across the broad global health community, gene drives for schistosomiasis control could fortify our defenses against this devastating disease in the future.

    View details for DOI 10.1371/journal.pntd.0007833

    View details for PubMedID 31856157

  • COMPUTER VISION AND MACHINE LEARNING ENABLE ENVIRONMENTAL DIAGNOSTICS FOR TARGETING SCHISTOSOMIASIS CONTROL Sokolow, S., Liu, Z., Chamberlin, A., Le Boa, C., Wood, C., Jones, I., Grewelle, R., De Leo, G. AMER SOC TROP MED & HYGIENE. 2018: 418
  • The influence of locus number and information content on species delimitation: an empirical test case in an endangered Mexican salamander Molecular Ecology Hime, P. M., Hotaling, S., Grewelle, R. E., O'Neill, E. M., Voss, S. R., Shaffer, H. B., Weisrock, D. W. 2016

    View details for DOI 10.1111/mec.13883