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A Hierarchical Network Approach for Modeling Rift Valley Fever Epidemics with Applications in North America

Overview of attention for article published in PLOS ONE, May 2013
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Title
A Hierarchical Network Approach for Modeling Rift Valley Fever Epidemics with Applications in North America
Published in
PLOS ONE, May 2013
DOI 10.1371/journal.pone.0062049
Pubmed ID
Authors

Ling Xue, Lee W. Cohnstaedt, H. Morgan Scott, Caterina Scoglio

Abstract

Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread.

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Geographical breakdown

Country Count As %
United States 3 3%
United Kingdom 1 1%
Kenya 1 1%
Denmark 1 1%
Madagascar 1 1%
Unknown 80 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 24%
Researcher 20 23%
Student > Master 9 10%
Student > Bachelor 6 7%
Other 4 5%
Other 14 16%
Unknown 13 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 26%
Veterinary Science and Veterinary Medicine 8 9%
Medicine and Dentistry 7 8%
Mathematics 6 7%
Engineering 5 6%
Other 20 23%
Unknown 18 21%