Abstract
Ecologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the usually-undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.
Highlights
In the urgent setting of pandemic response, ecologists have begun to play an increasingly important role[1]
The rapid spread of Zika virus from Brazil throughout the Americas has posed a particular problem for ecologists involved in pandemic response, as several different ecological niche models (ENMs)[12,16,17] and a handful of mechanistic forecasts[10] have been developed to project the potential full spread of the pathogen
We suggest that the lack of a consensus among different models of spatial risk renders the literature less credible or navigable to policymakers, as predictions under certain conditions span a range from 13 counties at risk[12] to the entire United States (Fig. 1)[10,21]
Summary
In the urgent setting of pandemic response, ecologists have begun to play an increasingly important role[1]. Ecological variables like temperature and precipitation often play just as important a role as socioeconomic risk factors in the vector-borne transmission cycle, governing key parameters including transmission rates, vector lifespan, and extrinsic incubation period[2]; the statistical relationships among these variables can be exploited to develop predictive frameworks for vector-borne disease outbreaks. The rapid spread of Zika virus from Brazil throughout the Americas has posed a particular problem for ecologists involved in pandemic response, as several different ecological niche models (ENMs)[12,16,17] and a handful of mechanistic forecasts[10] have been developed to project the potential full spread of the pathogen. Though no autochthonous transmission in the United States has been reported in 2018, the challenge of prediction is ongoing, and little work has been done to track and synthesize the kinds of evidence that were most influential during the peak of the outbreak
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