West Nile virus is predicted to be more geographically widespread in New York State and Connecticut under future climate change. (29th August 2021)

• Record Type: Journal Article
• Authors: Keyel, Alexander C.; Raghavendra, Ajay; Ciota, Alexander T.; Elison Timm, Oliver
• Is Part Of: Global change biology. Volume 27:Number 21(2021)
• Page Start: 5430
• Page End: 5445
• Publication Date: 2021-08-29
• Subjects: arbovirus -- climate change -- global warming -- neuroinvasive -- Weather Research Forecast -- West Nile virus; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.15842
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: The effects of climate change on infectious diseases are a topic of considerable interest and discussion. We studied West Nile virus (WNV) in New York (NY) and Connecticut (CT) using a Weather Research and Forecasting (WRF) model climate change scenario, which allows us to examine the effects of climate change and variability on WNV risk at county level. We chose WNV because it is well studied, has caused over 50, 000 reported human cases, and over 2200 deaths in the United States. The ecological impacts have been substantial (e.g., millions of avian deaths), and economic impacts include livestock deaths, morbidity, and healthcare‐related expenses. We trained two Random Forest models with observational climate data and human cases to predict future levels of WNV based on future weather conditions. The Regional Model used present‐day data from NY and CT, whereas the Analog Model was fit for states most closely matching the predicted future conditions in the region. Separately, we predicted changes to mosquito‐based WNV risk using a trait‐based thermal biology approach (Mosquito Model). The WRF model produced control simulations (present day) and pseudo‐global warming simulations (future). The Regional and Analog Models predicted an overall increase in human cases of WNV under future warming. However, the Analog Model did not predict as strong of an increase in the number of human cases as the Regional Model, and predicted a decrease in cases in some counties that currently experience high numbers of WNV cases. The Mosquito Model also predicted a decrease in risk in current high‐risk areas, with an overall reduction in the population‐weighted relative risk (but an increase in area‐weighted risk). The Mosquito Model supports the Analog Model as making more realistic predictions than the Regional Model. All three models predicted a geographic increase in WNV cases across NY and CT. Abstract : West Nile virus (WNV) is a mosquito‐borne virus that has caused over 2200 deaths in the United States since 1999. Our modeling results estimate that warmer temperatures will result in more geographically widespread human disease cases in New York and Connecticut by the end of the century under future climate change (Representative Concentration Pathway 8.5). While total human case numbers are predicted to increase in these states, some areas, especially those which are currently experiencing high numbers of cases or high mosquito‐based risk, are predicted to have fewer cases and lower mosquito‐based WNV risk.