ARBO-PREVENT

Lead PI: Angel Munoz Solorzano

Unit Affiliation: International Research Institute for Climate and Society (IRI)

January 2020 - December 2021
Inactive
Global
Project Type: Research

DESCRIPTION: We will forecast vector activity and epidemic thresholds based on the dynamic process-based models developed by the larger team. The forecasts will be calibrated to a setting and context and rigorously validated based on empirical data of vectors and disease. We will utilize the subseasonal climate forecasts derived from the S2S Prediction Project (http://s2sprediction.net) and the European Centre for Medium-Range Weather Forecasts (ECMWF) to forecast vector abundance, as well as associated variables. Dynamic models will be run on an ensemble of different climate models to assess and forecast uncertainty. Outbreak prediction will be measured in sensitivity and specificity and the lead times will range from sub-seasonal (20 days-3 months) to seasonal timeframes (3-9 months).

SPONSOR:

Umea University

ORIGINATING SPONSOR:

Formas - The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning

FUNDED AMOUNT:

$128,169

KEYWORDS

climate models vector-borne disease

THEMES

Modeling and Adapting to Future Climate