Modeling Japanese Encephalitis using interconnected networks for a hypothetical outbreak in the USA

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Show simple item record Riad, Md Mahbubul Huq 2017-04-12T20:04:15Z 2017-04-12T20:04:15Z 2017-05-01 en_US
dc.description.abstract Japanese Encephalitis (JE) is a vector-borne disease transmitted by mosquitoes and maintained in birds and pigs. An interconnected network model is proposed to examine the possible epidemiology of JE in the USA. Proposed JE model is an individual-level network model that explicitly considers the feral pig population and implicitly considers mosquitoes and birds in specific areas of Florida, North Carolina, and South Carolina. The virus transmission among feral pigs within a small geographic area (<60 sq mi areas) are modeled using two network topologies— fully connected and Erdos-Renyi networks. Connections between locations situated in different states (interstate links) are created with limited probability and based on fall and spring bird migration patterns. Simulation results obtained from the network models support the use of the Erdos-Renyi network because maximum incidence occurs during the fall migration period which is similar to the peak incidence of the closely related West Nile virus (WNV), another virus in the Japanese Encephalitis group (Flaviviridae) that is transmitted by both birds and mosquitoes. Simulation analysis suggested two important mitigation strategies: for low mosquito vectorial capacity, insecticidal spraying of infected areas reduces transmission and limits the outbreak to a single geographic area. Alternatively, in high mosquito vectorial capacity areas, birds rather than mosquitoes need to be removed/controlled. en_US
dc.description.sponsorship United States Department of Agriculture en_US
dc.language.iso en en_US
dc.publisher Kansas State University en
dc.subject Epidemic modeling en_US
dc.subject Individual-level model en_US
dc.subject Network model en_US
dc.title Modeling Japanese Encephalitis using interconnected networks for a hypothetical outbreak in the USA en_US
dc.type Report en_US Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Electrical and Computer Engineering en_US
dc.description.advisor Caterina Maria Scoglio en_US 2017 en_US May en_US

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