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Data and code from: Vector demography, dispersal, and the spread of disease: Experimental epidemics under elevated resource supply

Citation

Strauss, Alexander et al. (2020), Data and code from: Vector demography, dispersal, and the spread of disease: Experimental epidemics under elevated resource supply, Dryad, Dataset, https://doi.org/10.5061/dryad.5x69p8d1g

Abstract

1. The spread of many diseases depends on the demography and dispersal of arthropod vectors. Classic epidemiological theory typically ignores vector dynamics and instead makes the simplifying assumption of frequency-dependent transmission. Yet vector ecology may be critical for understanding the spread of disease over space and time and how disease dynamics respond to environmental change. 2. Here, we ask how environmental change shapes vector demography and dispersal, and how these traits of vectors govern the spatiotemporal spread of disease. 3. We developed disease models parameterized by traits of vectors and fit them to experimental epidemics. The experiment featured a viral pathogen (CYDV-RPV) vectored by aphids (Rhopalosiphum padi) among populations of grass hosts (Avena sativa) under two rates of environmental resource supply (i.e., fertilization of the host). We compared a non-spatial model that ignores vector movement, a lagged dispersal model that emphasizes the delay between vector reproduction and dispersal, and a travelling wave model that generates waves of infections across space and time. 4. Resource supply altered both vector demography and dispersal. The lagged dispersal model fit best, indicating that vectors first reproduced and then dispersed among hosts in the experiment. Elevated resources decreased vector population growth rates, nearly doubled their carrying capacity per host, increased dispersal rates when vectors carried the virus, and homogenized disease risk across space. 5. Together, the models and experiment show how environmental eutrophication can shape spatial disease dynamics – for example, homogenizing disease risk across space – by altering the demography and behavior of vectors.

Usage Notes

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Funding

NSF DEB , Award: 1556649

NSF IOS , Award: 1556674

NSF DEB, Award: 1556649

NSF IOS, Award: 1556674