Impact of insecticide control measures and temperature on Dengue Virus transmission by Aedes aegypti mosquitoes
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 1F31AI183638-01
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Key facts
Disease
DengueStart & end year
20242026Known Financial Commitments (USD)
$48,974Funder
National Institutes of Health (NIH)Principal Investigator
GRADUATE STUDENT RESEACHER Patrick HeffernanResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF NOTRE DAMEResearch Priority Alignment
N/A
Research Category
Animal and environmental research and research on diseases vectors
Research Subcategory
Vector control strategies
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
Abstract
Project Summary Dengue is a human disease caused by the dengue virus (DENV) and transmitted by Aedes aegypti and Aedes albopictus mosquitoes that afflicts hundreds of millions of humans, causes 20,000 confirmed human deaths annually, and puts >3.6 billion people at risk. Temperature is well-documented to influence the traits of both mosquitoes and DENV, exhibiting unimodal responses known as thermal performance curves (TPCs), thus also altering R0 an important proxy of the population growth rate of pathogens and thus transmission. Consequently, global climate change is expected to alter incidence and seasonal dynamics of dengue, and ecologically relevant predictive models are essential to mitigate these changes to disease risk. In recent years, my sponsor, co-sponsor, and colleagues have developed temperature-dependent, trait-based transmission models for mosquito-borne diseases (including dengue), using a generalized R0 equation derived from the classic Ross-Macdonald model. This predictive equation, however, is limited by the fact that temperature is the sole abiotic factor considered, despite other widespread abiotic factors, such as insecticides, being well known to impact traits of mosquitoes that affect transmission. My objective for this application is to develop and parameterize this model for DENV transmission by A. aegypti with commonly deployed insecticides with an overall goal of reducing dengue. My central hypothesis is that insecticides and temperature interact synergistically or antagonistically, rather than additively, to affect the R0 of DENV. To test this hypothesis, I will conduct response surface experiments crossing 5 insecticide doses of both the larvicide temephos and the adulticide deltamethrin and 7 temperatures on juvenile and adult A. aegypti and DENV, and I will measure all eight temperature-dependent parameters in the generalized R0 equation. Using Bayesian inference, I will fit thermal performance curves to each trait across insecticide doses and implement these into the R0 equation. Once these aims have been completed, I will have developed the first fully parameterized insecticide- and temperature-dependent R0 model for dengue. The aim of this R0 model is to more accurately predict disease incidence, identify the extent to which temperature impacts the efficacy of common insecticides, determine the ideal climatic and seasonal conditions to deploy insecticides in, determine concentration levels required for insecticides to control dengue in different regions, and determine how to respond to and leverage climate change in the face of range shifts and expansions.