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

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.

Figure 1.

Contact networks of Ebola cases. Secondary transmission was more probable among contacts who were reported by multiple sources. (a) The odds of transmission were higher for within-household contacts between an individual and an infectious case. The probability of transmission was not found to vary significantly between (b) male and female source cases or across (c) age categories. However, transmission within households tended to be more probable when infectious cases were children (less than 15 years) and adults (15–45 years) than when they were older adults (more than 45 years).

Figure 2.

Temporal changes in the geographical proximity relationships between cases and their contacts. (a) Contact-tracing data were used to categorize case–contact relationships according to residential proximity (same household, same community but different household, same zone but different community, or different zone). Over three months of the second phase (starting June 2014) of Liberia's outbreak, cases reported increasing contact with individuals in their same households and communities and decreasing contact with people in different communities. There were 611 contacts of incident cases investigated in July, 2509 in August and 2935 in September. Incidence, as the proportion of reported contacts developing disease, decreased over time, probably due to heightened contact-tracing efforts and higher numbers of contacts being reported. Error bars represent the upper limits of the 95% confidence intervals calculated using the normal approximation for the binomial proportion. (b) Overall, the probability of a case–contact interaction resulting in transmission was not significantly related to the sex or age of the symptomatic source, although the transmission probabilities associated with children (less than 15 years) and adult cases (15–45 years) were higher than that associated with older adults (more than 45 years). In particular, when considering the residential proximity between the case and contact, it was observed that the probability of transmission from symptomatic children (under 15 years) and adults (15–45 years) in households was over twice (35/789, 4.4%) that of transmission from older adults (more than 45 years) (6/352, 1.7%). *p-values calculated using χ² or Fisher's exact tests.