Date Published: March 7, 2019
Publisher: Public Library of Science
Author(s): J. Daniel Kelly, Lee Worden, S. Rae Wannier, Nicole A. Hoff, Patrick Mukadi, Cyrus Sinai, Sarah Ackley, Xianyun Chen, Daozhou Gao, Bernice Selo, Mathais Mossoko, Emile Okitolonda-Wemakoy, Eugene T. Richardson, George W. Rutherford, Thomas M. Lietman, Jean Jacques Muyembe-Tamfum, Anne W. Rimoin, Travis C. Porco, John Schieffelin.
As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration.
On May 8, 2018, the World Health Organization (WHO) announced the occurrence of an outbreak of Ebola virus disease (EVD) in the Democratic Republic of Congo (DRC). From April 4 through May 7, 21 suspected EVD cases were reported in Iboko and Bikoro, Équateur Province. On May 7, blood samples from five hospitalized patients had been sent to Kinshasa for Ebola-PCR testing, and two were confirmed PCR-positive. On May 21, vaccination of healthcare workers started. By May 27, the ring vaccination campaign was being rolled out as 906 contacts and contacts of contacts were being actively monitored. Six suspected, 13 probable and 35 confirmed EVD cases had been reported, and 25 (52%) of 48 probable and confirmed EVD cases had died.
As of May 27, 2018, there were 6 suspected, 13 probable and 35 confirmed EVD cases. Bikoko had ten confirmed cases, 11 probable cases, and one suspected case. Iboko had 21 confirmed cases, two probable cases, and one suspected case. Mbandaka had four confirmed cases and one suspected case (Fig 1).
When we were conducting our projections in late May, this outbreak still had the potential to become the largest outbreak in DRC since 2007. Vaccine use, regardless of coverage levels, was projected to prevent more than half of the total outbreak size. Vaccines, however, were only part of concurrent prevention, control, and care strategies.[8,49–51] We also found that the stochastic model with vaccine use projected that rare, large outbreaks (tail of the distribution of the model without vaccinations) were prevented, suggesting that repeat epidemics such as the 2013–2016 West African outbreak may have been highly unlikely once vaccines were rolled out.