Bringing West Nile Virus Forecasting Approaches Together to Better Serve Stakeholders in a Changing Environment

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Principal Investigator: 
Alexander Keyel, New York State Department of Health and University of Albany
Rebecca Smith, University of Illinois College of Veterinary Medicine
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Global changes affect disease distribution and dynamics. Quantitative tools may provide risk information and guide interventions to improve human and ecological health outcomes. However, a variety of tools exist, and formally comparing methods could allow researchers and stakeholders, such as public health workers, to quickly identify the most appropriate model(s) or modeling approach for a given situation. For vector-borne diseases, it has not been possible to systematically evaluate and compare forecasting methods because forecasts are often based on different data sources, spatiotemporal scales, and measurement precision. Assessments also use different evaluation metrics, making meta-analysis impossible. Therefore, it is essential that a formal approach to disease forecast comparison be developed. At the same time, stakeholders often apply these models without understanding their strengths, weaknesses, and assumptions. This could lead to sub-optimal public health and vector control decision-making. Therefore, it is crucial to rigorously explore the models using simulated data sets. We propose a workshop in which data managers and model forecasters cooperatively develop a collection of common data sets and evaluation metrics to compare model performance from their various approaches to improve the capacity to forecast when and where West Nile virus may occur. We believe this integrative workshop approach will prove an effective template for disease forecast improvement and application across a wide range of systems.

Oliver Elison Timm, University at Albany, SUNY
Johnny Uelmen, University of Illinois Urbana-Champaign
Charlotte Rhodes, Texas A&M University
Nicholas DeFelice, Icahn School of Medicine at Mount Sinai
Eliza Little, State of Connecticut
Morgan Gorris, Los Alamos National Laboratory, New Mexico
Michael Wimberly, University of Oklahoma
Justin Davis, University of Oklahoma
Philip Armstrong, State of Connecticut
Gabriel Hamer, Texas A&M University
Christopher Barker, University of California Davis
Karen Holcomb, University of California Davis
Kelly Helm Smith, University of Nebraska Lincoln
A. Marm Kilpatrick, University of California Santa Cruz
Luis Chaves, Ministry of Health, Costa Rica
Imelda Moise, University of Miami
Nicole Nova, Stanford University
Ilia Rochlin, Suffolk County, NY
Andrew Tyre, University of Nebraska–Lincoln
Marissa Childs, Stanford University
Stephanie Mundis, University of Florida
Catherine Lippi, University of Florida
Danielle Sass, University of Illinois
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