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ARS Home » Plains Area » Manhattan, Kansas » Center for Grain and Animal Health Research » ABADRU » Research » Publications at this Location » Publication #284074
Title: A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America

Author
item XUE, LING - Kansas State University
item Cohnstaedt, Lee
item SCOTT, MORGAN - Kansas State University
item SCOGLIO, CATERINA - Kansas State University

Submitted to: PLOS Neglected Tropical Diseases
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/18/2013
Publication Date: 5/7/2013
Citation: Xue, L., Cohnstaedt, L.W., Scott, M.H., Scoglio, C. 2013. A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America. PLOS Neglected Tropical Diseases. 8(5): e62049.

Interpretive Summary: Rift Valley fever is a viral disease common in southern and eastern Africa. It is transmitted by mosquitoes and amplified in domestic cattle and wild animals. Regions affected by this disease keep expanding. Rift Valley fever virus causes severe disease in humans and livestock during periods closely linked to extraordinarily heavy rainfall. The heavy rainfall provides favorable habitats, such as surface water pools known as dambos, for mosquitoes which are the main vectors needed to propagate an epidemic. Many mosquito genera and species have the potential to transmit Rift Valley fever virus. The fact that many species of mosquitoes act as vectors adds more possibility of Rift Valley fever virus being introduced to unexpected regions. Rift Valley fever causes economic losses due to livestock death and further exacerbated by animal movement restrictions and trade bans. Proposed is a mathematical model to mimic RVF outbreak with application to specific study areas of Texas. The model is tested with various initial conditions (introductions of a few or many infected eggs, adult mosquitoes, or cattle) and under realistic climatic conditions for the region in order to evaluate their effects on Rift Valley fever virus spread. Although Texas is not in a tropical region, the climate and environment are favorable for competent mosquito varieties to propagate and spread the virus and the region is one heavily involved with cattle production. The findings from simulations can help to guide and design mitigation strategies in the future.

Technical Abstract: Rift Valley fever (RVF) 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 RVF. Given a lack of empirical data on disease vector species and their vector competence, this difference equation 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 the Uvalde-area and panhandle counties of Texas, an important cattle 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. Humans, cattle, mosquitoes (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). Previous studies have demonstrated that the initial conditions of the introduction play an important role in the simulation results. The general epidemiological trend despite different initial numbers of infected hosts and vectors is a smaller initial infection results 1) a larger total number of infected farms and animals, 2) a longer delay after introduction until the peak of the epidemic, and 3) a more prolonged epidemic. The infection remains small for a long duration while it geographically expands before the epidemic explodes involving many farms and animals almost simultaneously. Therefore, an introduction initiated by infected Aedes eggs or mosquitoes results in a surprisingly larger epidemic than the introduction of many infected cattle.