J5.5 Use of Seasonal Climate Forecasts to Develop an Early-Warning System for Dengue Fever Risk in Central America and the Caribbean

Wednesday, 9 January 2019: 9:30 AM
North 228AB (Phoenix Convention Center - West and North Buildings)
Cory W. Morin, Univ. of Washington, Seattle, WA; and K. L. Ebi and S. Sellers

Mosquito-borne diseases remain an ongoing health challenge in tropical and sub-tropical regions. Weather and climate factors impact mosquito population dynamics and pathogen replication and/or development, in turn affecting the range, seasonality, and severity of the disease burden. This presents a challenge for planning, resource allocation, and research. However, improvements in seasonal forecasting provide an opportunity to assess disease risk months in advance. This could facilitate more rapid and efficient response strategies to pending epidemics. Our study will use seasonal climate forecasts to generate risk maps for dengue fever with 1- to 3-month lead times for Central America and the Caribbean. Risk will be assessed by combining climate-based rates of Aedes aegypti mosquito mortality and the dengue virus incubation period to calculate the potential for the mosquito to transmit the virus. Using this risk metric, risk under forecasted climate conditions will be compared to historic conditions to provide a relative measure of the effect of climate on pathogen transmission. A more detailed approach will also be conducted for individual cities and provinces that collect dengue surveillance data. Surveillance data will be incorporated into each new forecast so that risk can be assessed using both environmental conditions and the most recent health data. This allows for continuous model reparameterization so that nonenvironmental factors, such as virus strain, are considered in the disease forecasts. These disease forecasts will be conducted and evaluated in collaboration with public health professionals in the region. Their input will be vital in creating a forecasting system that is both useful and sustainable. While this system will focus primarily on dengue and other Aedes-transmitted pathogens, our methods could be tailored to model other climate-related health risks.
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