Collaborative Research: A new multiscale framework for integrating socio-economic processes, vector-borne disease control, and the impact of transient events

Mathematical models for infectious diseases are critical tools for informing effective disease interventions. The disease management strategies informed by models of vector-borne diseases (such as diseases spread by mosquitoes) led to the elimination of malaria from the United States and other countries. However, malaria continues to have an enormous impact on resource-challenged regions of the world, while other existing and emerging vector-borne diseases such as West Nile Virus, Dengue Virus, and Zika Virus continue to impact both advanced and resource-challenged economies. A shortcoming of many existing modeling approaches is the absence of an explicit connection between economic factors and disease transmission – two factors that influence each other. In an increasingly connected and complex world, accounting for the synergistic effects of these factors is essential for effective disease control. For example, the COVID-19 pandemic caused sudden economic shifts that affected the progress of malaria control programs, resulting in increases in malaria-related deaths. In collaboration with an ecologist/economist and with an entomologist and a biostatistician from Africa, the investigators will build mathematical tools to bridge this gap, which will be used to inform public health and economic growth policies. The project will train graduate students through involvement in the research. Workshops on feedback between economic and disease systems will train a new generation of undergraduate students from diverse backgrounds on this important topic. This work will also involve students from Africa, a continent that is highly affected by vector-borne diseases. Incorporating socio-economic factors into vector-borne disease (VBD) systems is key to identifying new interventions, by unraveling the intertwined relationship between VBD, socio-economic conditions, and transient events. Factors including heterogeneous mosquito-biting and insecticide-treated-net (ITN) replacement times, demographic structure, and human behavior in relation to ITN use will be included. For even the simplest economic-VBD model, standard methods for computing basic epidemiological metrics and performing structural identifiability analysis break down. Hence, the investigators also plan to build the mathematical toolbox required to analyze and simulate these coupled systems. Although the framework will be applied to malaria as a prototype VBD using socio-economic and epidemiological data from Kenya, Madagascar, and West Africa to calibrate the parameters and validate the outcomes of the models, it is intended to be robust enough to be applicable to other VBDs. Furthermore, the framework will allow the investigators to realistically answer important public health and economic growth questions, including how to distribute ITNs across connected populations, and how to respond to spontaneous events affecting the economic landscape. This award reflects NSF’s statutory mission and has been deemed worthy of support through evaluation using the Foundation’s intellectual merit and broader impacts review criteria.

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Capacity Building
Combination of Interventions
Modeling
Product Development
Social Science

Jul 2022 — Jun 2025

$359,393

United States