Browsing by Author "Lafferty, Kevin D."

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    A global parasite conservation plan
    Carlson, Colin J.; Hopkins, Skylar R.; Bell, Kayce C.; Dona, Jorge; Godfrey, Stephanie S.; Kwak, Mackenzie L.; Lafferty, Kevin D.; Moir, Melinda L.; Speer, Kelly A.; Strona, Giovanni; Torchin, Mark; Wood, Chelsea L. (2020-10)
    Found throughout the tree of life and in every ecosystem, parasites are some of the most diverse, ecologically important animals on Earth-but in almost all cases, the least protected by wildlife or ecosystem conservation efforts. For decades, ecologists have been calling for research to understand parasites' important ecological role, and increasingly, to protect as many species from extinction as possible. However, most conservationists still work within priority systems for funding and effort that exclude or ignore parasites, or treat parasites as an obstacle to be overcome. Our working group identified 12 goals for the next decade that could advance parasite biodiversity conservation through an ambitious mix of research, advocacy, and management.
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    Precision mapping of snail habitat provides a powerful indicator of human schistosomiasis transmission
    Wood, Chelsea L.; Sokolow, Susanne H.; Jones, Isabel J.; Chamberlin, Andrew J.; Lafferty, Kevin D.; Kuris, Armand M.; Jocque, Merlijn; Hopkins, Skylar R.; Adams, Grant; Buck, Julia C.; Lund, Andrea J.; Garcia-Vedrenne, Ana E.; Fiorenza, Evan; Rohr, Jason R.; Allan, Fiona; Webster, Bonnie; Rabone, Muriel; Webster, Joanne P.; Bandagny, Lydie; Ndione, Raphael; Senghor, Simon; Schacht, Anne-Marie; Jouanard, Nicolas; Riveau, Gilles; De Leo, Giulio A. (2019-11-12)
    Recently, the World Health Organization recognized that efforts to interrupt schistosomiasis transmission through mass drug administration have been ineffective in some regions; one of their new recommended strategies for global schistosomiasis control emphasizes targeting the freshwater snails that transmit schistosome parasites. We sought to identify robust indicators that would enable precision targeting of these snails. At the site of the world's largest recorded schistosomiasis epidemic-the Lower Senegal River Basin in Senegal-intensive sampling revealed positive relationships between intermediate host snails (abundance, density, and prevalence) and human urogenital schistosomiasis reinfection (prevalence and intensity in schoolchildren after drug administration). However, we also found that snail distributions were so patchy in space and time that obtaining useful data required effort that exceeds what is feasible in standard monitoring and control campaigns. Instead, we identified several environmental proxies that were more effective than snail variables for predicting human infection: the area covered by suitable snail habitat (i.e., floating, nonemergent vegetation), the percent cover by suitable snail habitat, and size of the water contact area. Unlike snail surveys, which require hundreds of person-hours per site to conduct, habitat coverage and site area can be quickly estimated with drone or satellite imagery. This, in turn, makes possible large-scale, high-resolution estimation of human urogenital schistosomiasis risk to support targeting of both mass drug administration and snail control efforts.
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    Understanding uncertainty in temperature effects on vector-borne disease: a Bayesian approach
    Johnson, Leah R.; Ben-Horin, Tal; Lafferty, Kevin D.; McNally, Amy; Mordecai, Erin A.; Paaijmans, Krijn P.; Pawar, Samraat; Ryan, Sadie J. (Ecological Society of America, 2015)
    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°C to 25°C; fecundity across all temperatures, but especially ~25–32°C; mortality from 20°C to 30°C; parasite development rate at ~15–16°C and again at ~33–35°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.