Transmission dynamics of Ebola virus disease

Stochastic realizations of outbreak trajectories for Ebola virus disease (from ref. 3).

Stochastic realizations of outbreak trajectories for Ebola virus disease (from ref. 4).

On 8 August 2014, the World Health Organization (WHO) declared the Ebola outbreak in West Africa a Public Health Emergency of International Concern (PHEIC). Only a few weeks later, our research group published the first estimates of the basic reproduction number R0 of Ebola: 1.51 for Guinea, 2.53 for Sierra Leone and 1.59 for Liberia (1). Our study has been of paramount importance in highlighting the lack in controlling the outbreak in Liberia, and was later confirmed by the WHO and several other research groups. The work has also received considerable attention in international media (see Media).

In another study, we investigated the heterogeneity in district-level transmission of Ebola during the epidemic in West Africa (2). We found that socio-demographic variables related to urbanisation, such as high population density and high wealth index, were found positively associated with R0, suggesting that the consequences of fast urban growth in West Africa may have contributed to the increased spread of Ebola. We also found that superspreading events for Ebola are an expected feature of the individual variation in infectiousness (3). This means that although the probability of extinction is high, new index cases also have the potential for explosive regrowth of the epidemic.

We quantified the impact of control interventions during the outbreak in Nigeria, and estimated the time window for successful containment of Ebola outbreaks caused by infected air travelers (4). We also inferred the transmission dynamics of the 2014 Ebola outbreak in the Democratic Republic of Congo (DRC) using previously published data (5).

Recent reports suggest the potential for sexual transmission of Ebola virus from convalescent survivors. We conducted the first mathematical modeling study to investigate the epidemiological consequences of this possible transmission route, and found that sexual transmission could extend the Ebola epidemic in Sierra Leone by several months (6).

Data and R code files that were used in the analyses can be found on GitHub.

  1. Althaus CL. (2014) Estimating the reproduction number of Ebola virus (EVOB) during the 2014 outbreak in West Africa. PLoS Curr, 6.
  2. Krauer F, Gsteiger S, Low N, Hansen CH, Althaus CL. (2016) Heterogeneity in district-level transmission of Ebola virus disease during the 2013-2015 epidemic in West Africa. PLOS Negl Trop Dis, 10:e0004867.
  3. Althaus CL. (2015) Ebola superspreading. Lancet Infect Dis, 15:507-8.
  4. Althaus CL, Low N, Musa EO, Shuaib F, Gsteiger S. (2015) Ebola virus disease outbreak in Nigeria: Transmission dynamics and rapid control. Epidemics, 11:80-4.
  5. Althaus CL. (2015) Rapid drop in the reproduction number during the Ebola outbreak in the Democratic Republic of Congo. PeerJ, 3:e1418.
  6. Abbate JL, Murall CL, Richner H, Althaus CL. (2016) Potential impact of sexual transmission on Ebola virus epidemiology: Sierra Leone as a case study. PLOS Negl Trop Dis, 10:e0004676.