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United States Department of Agriculture

Agricultural Research Service

Research Project: Network Based Modeling of Arthropods, Humans, and Animals to Better Understand Vector-Borne Disease Transmission

Location: Arthropod-Borne Animal Diseases Research

2013 Annual Report


1a.Objectives (from AD-416):
Develop stochastic and predictive models for arthropod-borne diseases of medical and veterinary importance. Build a stochastic network based model of Rift Valley fever transmission that involves mosquitoes, humans and animals. The model will be used to evaluate mitigation strategies to reduce mortality and morbidity during disease outbreaks and possible Rift Valley Fever epidemics.


1b.Approach (from AD-416):
Mathematical models that incorporate disease vector transmission parameters will be used to determine the mortality and morbidity during disease epidemics. Specifically, a stochastic Rift Valley fever model will be developed that incorporates humans, livestock, and mosquito species. The model will consider mosquito and cattle population fluctuations based on movement and environmental factors. After establishing and validating the model, mitigation strategies will be evaluated for feasibility.


3.Progress Report:

Mathematical modeling is needed to study disease epidemiology in an area in the absence of the disease. Kansas State and ABADRU researchers designed a deterministic network-based model of Rift Valley fever virus propagation in the southern United States. The deterministic network-based model that adds environmental conditions (temperature and precipitation) examines human, livestock and mosquito populations to estimate disease spread and number of infections based on mathematical models that account for the spatial distribution of all three populations throughout the landscape. This model was created to predict the geographic area at risk and the severity of an RVFV introduction into the cattle producing areas of the United States. Humans, cattle, and Aedes and Culex mosquito populations are modeled independently and their interactions recorded to identify the effects of various spatial distributions, climate scenarios, and contact ratios on possible RVFV mitigation strategies.


Last Modified: 10/1/2014
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