The impact of climate variability on infectious disease epidemic risks

For a range of diseases, changes in climate variables such as temperature, precipitation, and humidity are altering the geographical distribution of disease prevalence and the risk of outbreaks. Previous studies have forecast future trends of vector-borne diseases based on climate projections under anthropogenic climate change. However, future disease risks depend on the effects of both anthropogenic climate change and natural (or internal) climate variability. Natural climate variability is even important for intervals as long as the next 100 years.

The key goal of this project is to develop flexible open-source software for estimating future epidemic risks in different locations while accounting for anthropogenic climate change and natural climate variability. This involves pairing climate models and epidemic risk models. While we focus initially on vector-borne diseases, the computational framework will be built with a modular structure, enabling adaptation for other types of pathogen (for example, respiratory viruses) straightforwardly: this will simply involve replacing the "epidemiological model" module with computing code for an appropriate transmission model. Similarly, using different climate models will involve replacing the "climate data" module. To ensure usability by other scientists and policy advisors, we will run a workshop to train potential users to generate results with the software tool.