Document Detail


Efficient mitigation strategies for epidemics in rural regions.
MedLine Citation:
PMID:  20644715     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Containing an epidemic at its origin is the most desirable mitigation. Epidemics have often originated in rural areas, with rural communities among the first affected. Disease dynamics in rural regions have received limited attention, and results of general studies cannot be directly applied since population densities and human mobility factors are very different in rural regions from those in cities. We create a network model of a rural community in Kansas, USA, by collecting data on the contact patterns and computing rates of contact among a sampled population. We model the impact of different mitigation strategies detecting closely connected groups of people and frequently visited locations. Within those groups and locations, we compare the effectiveness of random and targeted vaccinations using a Susceptible-Exposed-Infected-Recovered compartmental model on the contact network. Our simulations show that the targeted vaccinations of only 10% of the sampled population reduced the size of the epidemic by 34.5%. Additionally, if 10% of the population visiting one of the most popular locations is randomly vaccinated, the epidemic size is reduced by 19%. Our results suggest a new implementation of a highly effective strategy for targeted vaccinations through the use of popular locations in rural communities.
Authors:
Caterina Scoglio; Walter Schumm; Phillip Schumm; Todd Easton; Sohini Roy Chowdhury; Ali Sydney; Mina Youssef
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2010-07-13
Journal Detail:
Title:  PloS one     Volume:  5     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2010  
Date Detail:
Created Date:  2010-07-20     Completed Date:  2010-10-28     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101285081     Medline TA:  PLoS One     Country:  United States    
Other Details:
Languages:  eng     Pagination:  e11569     Citation Subset:  IM    
Affiliation:
K-State EpiCenter, Department of Electrical and Computer Engineering, Kansas State University, Manhattan, Kansas, USA. caterina@ksu.edu
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MeSH Terms
Descriptor/Qualifier:
Disease Outbreaks / prevention & control*
Emigration and Immigration
Humans
Kansas
Models, Theoretical
Rural Population
Comments/Corrections

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