This project investigates the social and environmental conditions in cities that contribute to mosquito-borne diseases such as dengue. This work is motivated by the dramatic rates of urbanization seen across the world, and the complex role that urban environments play in maintaining mosquito populations and driving disease transmission. Despite the public health importance of dengue, there is little known about how factors such as city structure, human population density, and human behaviors come together to affect disease risk. To examine these factors, these scientists will gather information from diverse sources such as public health records, household mosquito collections, satellite imagery, and community-based conversations. On-the-ground work will be conducted in an urban environment that has a high incidence of dengue. This work is part of a collaboration with the local health department, so that findings will support ongoing disease prevention strategies. As a Doctoral Dissertation Research Improvement award, this project will provide support to enable a promising student to establish an independent research career.

There are no widely-available vaccines or effective treatment options for dengue. Therefore, disease prevention is centered around controlling mosquito populations. The scientists propose that to effectively control mosquito populations and disease transmission, there must be a greater understanding of the social and environmental dynamics in cities that affect mosquito ecology, human exposure to mosquitoes, and virus transmission. This project asks (1) what factors drive differences in rates of dengue across cities; (2) how does dengue risk vary within a city, based on the interactions between every-day human behaviors and social and environmental conditions; and (3) how will improvements to public services and environmental conditions affect rates of dengue in a city? These efforts will contribute to an inter-disciplinary framework for studying urban mosquito-borne diseases, grounded in spatial sciences. The work will also result in disease modeling tools that can be used to plan public health interventions in growing cities around the world.

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.

Agency
National Science Foundation (NSF)
Institute
Division of Behavioral and Cognitive Sciences (BCS)
Type
Standard Grant (Standard)
Application #
2020853
Program Officer
Scott Freundschuh
Project Start
Project End
Budget Start
2020-08-15
Budget End
2022-05-31
Support Year
Fiscal Year
2020
Total Cost
$17,999
Indirect Cost
Name
Columbia University
Department
Type
DUNS #
City
New York
State
NY
Country
United States
Zip Code
10027