Prof. Dr. Peter Haddawy 

Diseases spread by insects are emerging at a growing rate and bearing a disproportionate segment of all new infectious diseases. Mosquitoes transmit 36% of all such diseases, including malaria, dengue, and Zika. With climate change the habitat of disease-carrying mosquitoes is now expanding even into temperate regions, bringing along the risk of disease emergence. The research proposed for this fellowship will focus on developing techniques to assist in effectively targeting control efforts to prevent the spread of emerging mosquito-borne diseases. Effective targeting requires knowledge of the areas most at risk from the spread of transmission, the rate at which this might occur, and the key factors affecting vulnerability. Such information can be provided by predictive models. But the challenge here is that predictive models require data, which is typically scarce, uncertain, and evolving in early stages of an emerging disease. A modeling framework will thus be developed that can produce initial estimates with limited and uncertain data, and more refined estimates as more data becomes available. An essential component in such models is an estimate of mosquito populations. But existing mosquito population monitoring approaches are either too inaccurate or too labor intensive. As an alternative solution, we will develop electronic sensors that are able to count and to classify mosquitoes into species based on their wingbeat sounds during flight.