Characterizing risk of Ebola transmission based on frequency and type of case-contact exposures

Philos Trans R Soc Lond B Biol Sci. 2017 May 26;372(1721):20160301. doi: 10.1098/rstb.2016.0301.

Abstract

During the initial months of the 2013-2016 Ebola epidemic, rapid geographical dissemination and intense transmission challenged response efforts across West Africa. Contextual behaviours associated with increased risk of exposure included travel to high-transmission settings, caring for sick and preparing the deceased for traditional funerals. Although such behaviours are widespread in West Africa, high-transmission pockets were observed. Superspreading and clustering are typical phenomena in infectious disease outbreaks, as a relatively small number of transmission chains are often responsible for the majority of events. Determining the characteristics of contacts at greatest risk of developing disease and of cases with greatest transmission potential could therefore help curb propagation of infection. Our analysis of contact tracing data from Montserrado County, Liberia, suggested that the probability of transmission was 4.5 times higher for individuals who were reported as having contact with multiple cases. The probability of individuals developing disease was not significantly associated with age or sex of their source case but was higher when they were in the same household as the infectious case. Surveillance efforts for rapidly identifying symptomatic individuals and effectively messaged campaigns encouraging household members to bring the sick to designated treatment centres without administration of home care could mitigate transmission.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Keywords: Ebola virus disease; West Africa; contact tracing; infectious disease transmission; targeted intervention.

MeSH terms

  • Contact Tracing*
  • Hemorrhagic Fever, Ebola / transmission*
  • Hemorrhagic Fever, Ebola / virology
  • Humans
  • Liberia
  • Models, Theoretical
  • Risk