A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

Abstract

West Nile virus (WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input.

Riding the Wave: Reactive Vector-Borne Disease Policy Renders the United States Vulnerable to Outbreaks and Insecticide Resistance

“…Similarly, to their Midwest affiliate, PACVEC has also published novel control and risk prediction modeling ( Barker 2019 , Holcomb et al 2021 ). Lastly, these COEs do no work in silos, and often collaborate to produce high-impact applied entomology articles ( Fernandez et al 2019 , Keyel et al 2021 ). As the COEs share best practices and protocols through their integrated research, informal peer mentoring, and formal trainings, this allows for greater exchange of ideas while standardizing practices and data throughout each region.…”

Development of a Community-Driven Mosquito Surveillance Program for Vectors of La Crosse Virus to Educate, Inform, and Empower a Community

“…Additionally, effective science communication on these important issues can build, maintain, and/or restore trust, but efforts must be planned and intentional to be effective [33,34]. To our knowledge, there are no extant public health campaigns against LACV, and most U.S.-based mosquito campaigns target West Nile virus transmitted by Culex mosquitoes [35,36] or Ae. aegypti-associated diseases such as Zika [37].…”

Integrated Forecasts Based on Public Health Surveillance and Meteorological Data Predict West Nile Virus in a High-Risk Region of North America

“…Various approaches have been used to develop predictive models for WNV ( Barker 2019 ; Keyel et al. 2021 ).…”

“…Recent reviews have highlighted several significant gaps in the development and implementation of forecasting models for WNV. Although multiple models have been created using a variety of data sources at a wide range of spatial and temporal scales, few have been applied to make real-time forecasts and connect the predictions with public health decision-making ( Keyel et al. 2021 ).…”