Article thumbnail

Efficient Mitigation Strategies for Epidemics in Rural Regions

By Caterina Scoglio, Walter Schumm, Phillip Schumm, Todd Easton, Sohini Roy Chowdhury, Ali Sydney and Mina Youssef

Abstract

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

Topics: Research Article
Publisher: Public Library of Science
OAI identifier: oai:pubmedcentral.nih.gov:2903608
Provided by: PubMed Central

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.

Suggested articles

Citations

  1. (1927). A contribution to the mathematical theory of epidemics. Proc Roy Soc Lond 115: 700–721.
  2. (2001). Are rural residents less likely to obtain recommended preventive healthcare services?
  3. Disease Control and Prevention (2009) H1N1 Flu: International Situation Update.
  4. (2003). Efficient Immunization Strategies for Computer Networks and Populations.
  5. (2007). Epidemic spreading on weighted contact networks,
  6. (2004). Finding and evaluating community structure in networks.
  7. (2007). Generalizations of the clustering coefficient to weighted complex networks.
  8. (2009). Global Epidemic and Mobility Modeler.
  9. (2007). Improving immunization strategies.
  10. (2007). Individual-based model for simulation of urban epidemic.
  11. (2004). Modelling disease outbreaks in realistic urban social networks.
  12. (2006). Modularity and community structure in networks,
  13. (2009). Pandemic Potential of a Strain of Influenza A (H1N1): Early Findings.
  14. (1979). The Epidemiology of Influenza B in a rural setting in
  15. (2002). The spread of epidemic disease on networks.
  16. (2008). Vespignani A
  17. (2003). What affects influenza vaccination rates among older patients? An analysis from inner-city, suburban, rural, and veterans affairs practices.