The 2014 Ebola virus disease outbreak in Pujehun, Sierra Leone: epidemiology and impact of interventions

Abstract

BackgroundIn July 2014, an outbreak of Ebola virus disease (EVD) started in Pujehun district, Sierra Leone. On January 10th, 2015, the district was the first to be declared Ebola-free by local authorities after 49 cases and a case fatality rate of 85.7 %. The Pujehun outbreak represents a precious opportunity for improving the body of work on the transmission characteristics and effects of control interventions during the 2014–2015 EVD epidemic in West Africa.MethodsBy integrating hospital registers and contact tracing form data with healthcare worker and local population interviews, we reconstructed the transmission chain and investigated the key time periods of EVD transmission. The impact of intervention measures has been assessed using a microsimulation transmission model calibrated with the collected data.ResultsThe mean incubation period was 9.7 days (range, 6–15). Hospitalization rate was 89 %. The mean time from the onset of symptoms to hospitalization was 4.5 days (range, 1–9). The mean serial interval was 13.7 days (range, 2–18). The distribution of the number of secondary cases (R0 = 1.63) was well fitted by a negative binomial distribution with dispersion parameter k = 0.45 (95 % CI, 0.19–1.32). Overall, 74.3 % of transmission events occurred between members of the same family or extended family, 17.9 % in the community, mainly between friends, and 7.7 % in hospital. The mean number of contacts investigated per EVD case raised from 11.5 in July to 25 in September 2014. In total, 43.0 % of cases were detected through contact investigation. Model simulations suggest that the most important factors determining the probability of disease elimination are the number of EVD beds, the mean time from symptom onset to isolation, and the mean number of contacts traced per case. By assuming levels and timing of interventions performed in Pujehun, the estimated probability of eliminating an otherwise large EVD outbreak is close to 100 %.ConclusionsContainment of EVD in Pujehun district is ascribable to both the natural history of the disease (mainly transmitted through physical contacts, long generation time, overdispersed distribution of secondary cases per single primary case) and intervention measures (isolation of cases and contact tracing), which in turn strongly depend on preparedness, population awareness, and compliance. Our findings are also essential to determine a successful ring vaccination strategy.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-015-0524-z) contains supplementary material, which is available to authorized users.

Spatiotemporal dynamics of the Ebola epidemic in Guinea and implications for vaccination and disease elimination: a computational modeling analysis

“…While the early stage of the epidemic is probably not overly affected by asymptomatic infections, acquired immunity may play a role in speeding up the elimination of the disease. Notwithstanding the mentioned limitations, the model is able to adequately describe the dynamics of the epidemic in Guinea, provide estimates of transmission by setting in agreement with reported data [6], and capture the highly heterogeneous pattern of transmission reported in previous studies [6, 7]. These findings support our choice of using an individual-based modeling approach, capturing the observed high heterogeneity in the number of secondary infections and the clustering effect due to the low number of effective contacts in the different settings.…”

“…From data reported to WHO, the age-specific incidence of Ebola is notably higher among adults versus children in Guinea, Liberia, and Sierra Leone [7, 14–16]. Therefore, the model allows children aged 0–14 years to have a different risk of infection compared to individuals aged 15 years or older [17].…”

Containing Ebola at the Source with Ring Vaccination

“…Individuals are assigned to specific households, and households are linked to create “extended households” as are typical in rural Africa. The model is an extension of a model used to simulate interventions during the 2014 outbreak [9]. We used microsimulations to explicitly model Ebola transmission within households and extended households (35.9% and 38.5% of transmission in Pujehun district, respectively; 74.4% of transmission combined) and in the general community, including non-household and health care-related contacts (25.6% of transmission) [9].…”

“…We also consider a more optimistic scenario where we assume that 90% of contacts can be identified through contact tracing. This assumption stems from the observation that most of non-family transmission events in Pujehun district were observed among friends [9] and thus they could be potentially traceable, at least to some extent. The relative proportions of transmissions are consistent with findings from other West African regions [8, 15, 16].…”

“…We use a spatially explicit agent-based model of EVD transmission based on a detailed synthetic population of Sierra Leone (see Methods and SI) [8, 9]. The model is calibrated to reproduce the most important features of the EVD outbreak in Pujehun district, that can be considered typical in terms of both transmissibility and key time periods.…”