Dengue is a mosquito vectored viral disease of humans that is now considered the most important arthropod-borne human viral disease. An estimated 50-100 million cases of dengue fever (break-bone fever) and about 500,000 cases of the more life-threatening dengue hemorrhagic fever occur annually. Beyond direct impact on afflicted individuals, urban dengue epidemics overwhelm public health systems of tropical countries. The principal vector of dengue virus is the mosquito, Aedes aegypti, that lives in close association with humans and feed on human blood. The only currently effective way to suppress dengue epidemics involves household insecticide sprays. These sprays can be effective if used efficiently, but this is commonly not the case. Research efforts are underway to develop vaccines against dengue and to create genetically engineered strains of the mosquitoes with genes that block transmission of the dengue from the mosquito to humans. Although there is great hope for these new approaches as well as for improving conventional chemical control of the mosquito, there are many unknowns about the epidemiology of dengue that make it difficult to determine how one would deploy a new vaccine, engineered mosquito, or novel insecticide. We also don't know if it would be most beneficial to use the single most effective new tactic alone, or to use a combination of tactics. Because experimental studies of the efficacy of a new intervention must typically be conducted at a city-wide level, such experiments are generally not feasible or ethical to conduct. Computer simulation studies have often offered an alternative to direct experimentation in scientific fields ranging from space travel to global climate change. Simulations of mathematical models have been a key factor in studying directly transmitted diseases such as measles, but have been used less in studies of insect-vectored diseases. Our overall goal is to create and test the most comprehensive and robust simulation model of Aedes aegypti/dengue dynamics in order to provide research, regulatory, and management communities with a modeling tool for effectively guiding mosquito vector management and vaccine deployment programs. The final model we develop will provide empirical researchers and public health practitioners with credible answers to questions such as: 1) Are dengue epidemics most likely to start by transmission within small neighborhoods or through daily human movement to public places, and how does that determine appropriate response to urban outbreaks? 2) What are the most efficient options for release of transgenic Ae. aegypti strains with anti-dengue constructs? 3) Would it be more efficient and sustainable to combine deployment of dengue vaccines and Ae. aegypti management, or to invest in the single tactic that is most effective and economical on its own?

Public Health Relevance

We will build a detailed computer model that simulates the biology of the mosquito that transmits dengue fever in order to provide research, regulatory, and management communities with a tool that can help them to determine the most effective ways to develop and implement mosquito vector management and vaccine deployment programs aimed at suppressing dengue fever and dengue shock syndrome epidemics.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI091980-03
Application #
8515921
Study Section
Vector Biology Study Section (VB)
Program Officer
Costero, Adriana
Project Start
2011-08-15
Project End
2015-07-31
Budget Start
2013-08-01
Budget End
2014-07-31
Support Year
3
Fiscal Year
2013
Total Cost
$313,129
Indirect Cost
$78,129
Name
North Carolina State University Raleigh
Department
Zoology
Type
Schools of Earth Sciences/Natur
DUNS #
042092122
City
Raleigh
State
NC
Country
United States
Zip Code
27695
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Reiner Jr, Robert C; Stoddard, Steven T; Scott, Thomas W (2014) Socially structured human movement shapes dengue transmission despite the diffusive effect of mosquito dispersal. Epidemics 6:30-6
Reiner Jr, Robert C; Stoddard, Steven T; Forshey, Brett M et al. (2014) Time-varying, serotype-specific force of infection of dengue virus. Proc Natl Acad Sci U S A 111:E2694-702
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