Taking a Swat at the Dengue Mosquito

Team Location: Jet Propulsion Laboratory, Pasadena, California

These four graphs illustrate the total number of individual mosquitoes (Aedes aegypti) at each cohort level: eggs (top), larval (upper-middle), pupae (lower-middle), and adults (bottom). Image Credit: Brazil Health and Air Quality Team, NASA DEVELOP National Program.

These four graphs illustrate the total number of individual mosquitoes (Aedes aegypti) at each cohort level: eggs (top), larval (upper-middle), pupae (lower-middle), and adults (bottom). Image Credit: Brazil Health and Air Quality Team, NASA DEVELOP National Program.



Authors:
Diane A. Garcia-Gonzales (University of California at Berkeley), Project Lead
Lorena Lopez (California State University at Northridge)
Scott Barron (University of California at Los Angeles)

Mentors/Advisers:
Erika Podest (Jet Propulsion Laboratory)
Darren Drewry (Jet Propulsion Laboratory)

Abstract:
The aim of this project was to provide an understanding of the interplay of environmental factors involved at locations prone to the spread, presence and persistence of mosquito populations of Aedes aegypti, the primary dengue vector. The team utilized multi-temporal satellite remote-sensing data to obtain information regarding temperature, precipitation and humidity, as well as census data on population density for Brazil. We utilized a version of the weather-driven entomological life-table simulation model by Focks & Haile (1993) in order to simulate the biological cycle of Aedes aegypti. This model provides an understanding of mosquito abundance as a function of different environmental variables that play a role in each stage of the mosquito’s biological cycle. In collaboration with the California Department of Public Health (CDPH) for access to data on reported dengue fever cases, we investigated the correlation between remote-sensing environmental data and dengue disease incidence.

The objectives of this project were to 1) establish a framework to accurately and efficiently collect and analyze satellite datasets and develop a methodological strategy for replicating the current project results, 2) model the population dynamics of the primary urban vector to identify areas where current knowledge about the system is lacking, and 3) use the model to predict the dynamics of epidemics and the risk of dengue outbreaks. The ultimate project goals are to create risk maps of dengue outbreaks, which will allow end-users to prepare and deploy resources without performing costly and time-consuming field surveys.



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