January 13, 2017 Dataset Open Access

Paull, Sara H.; Horton, Daniel E.; Ashfaq, Moetasim; Rastogi, Deeksha; Kramer, Laura D.; Diffenbaugh, Noah S.; Kilpatrick, A. Marm

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    <subfield code="a">&lt;div class="o-metadata__file-usage-entry"&gt;COMosqDroughtData&lt;div class="o-metadata__file-description"&gt;Data were collected from the field. The species column indicates whether the mosquitoes were Culex pipiens (PIP) or Culex tarsalis (TAR). Prevalence gives the maximum likelihood prevalence of West Nile virus in mosquitoes of that species in that year for all collections from June through August. SEprev gives the standard error of the prevalence from June through August. The PDSI column gives the average value of the Palmer Drought Severity Index from May through August.  The Abun column gives the total number of mosquitoes collected from June through August, and SEAbun gives the standard error of the number of mosquitoes across counties.&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;&lt;div class="o-metadata__file-usage-entry"&gt;COMosqImmunityData&lt;div class="o-metadata__file-description"&gt;These are field collected data.  The vector index is the square root of the maximum likelihood prevalence in a given county and week multiplied by the total abundance of Culex pipiens and Culex tarsalis mosquitoes in a given county and week. The human cases data is the square root of the number of human WNV cases in a county and week.  The Year1 column indicates whether the data were collected in 2003 (1) or not (0).&lt;/div&gt;&lt;div class="o-metadata__file-name"&gt;&lt;/div&gt;&lt;/div&gt;&lt;p&gt;Funding provided by: National Science Foundation&lt;br&gt;Crossref Funder Registry ID: http://dx.doi.org/10.13039/100000001&lt;br&gt;Award Number: EF-0914866&lt;/p&gt;</subfield>
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    <subfield code="u">University of California, Santa Cruz</subfield>
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    <subfield code="a">Paull, Sara H.</subfield>
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    <subfield code="a">Data from: Drought and immunity determine the intensity of West Nile virus epidemics and climate change impacts</subfield>
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    <subfield code="a">The effect of global climate change on infectious disease remains hotly debated because multiple extrinsic and intrinsic drivers interact to influence transmission dynamics in nonlinear ways. The dominant drivers of widespread pathogens, like West Nile virus, can be challenging to identify due to regional variability in vector and host ecology, with past studies producing disparate findings. Here, we used analyses at national and state scales to examine a suite of climatic and intrinsic drivers of continental-scale West Nile virus epidemics, including an empirically derived mechanistic relationship between temperature and transmission potential that accounts for spatial variability in vectors. We found that drought was the primary climatic driver of increased West Nile virus epidemics, rather than within-season or winter temperatures, or precipitation independently. Local-scale data from one region suggested drought increased epidemics via changes in mosquito infection prevalence rather than mosquito abundance. In addition, human acquired immunity following regional epidemics limited subsequent transmission in many states. We show that over the next 30 years, increased drought severity from climate change could triple West Nile virus cases, but only in regions with low human immunity. These results illustrate how changes in drought severity can alter the transmission dynamics of vector-borne diseases.</subfield>
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