Temporal Variations in the Effective Reproduction Number of the 2014 West Africa Ebola Outbreak

Abstract

Background The rapidly evolving 2014 Ebola virus disease (EVD) outbreak in West Africa is the largest documented in history, both in terms of the number of people infected and in the geographic spread. The high morbidity and mortality have inspired response strategies to the outbreak at the individual, regional, and national levels. Methods to provide real-time assessment of changing transmission dynamics are critical to the understanding of how these adaptive intervention measures have affected the spread of the outbreak. Methods In this analysis, we use the time series of EVD cases in Guinea, Sierra Leone, and Liberia up to September 8, 2014, and employ novel methodology to estimate how the rate of exponential rise of new cases has changed over the outbreak using piecewise fits of exponential curves to the outbreak data. Results We find that for Liberia and Guinea, the effective reproduction number rose, rather than fell, around the time that the outbreak spread to densely populated cities, and enforced quarantine was imposed on several regions in the countries; this may indicate that enforced quarantine may not be an effective control measure. Conclusions If effective control measures are not put in place, and the current rate of exponential rise of new cases continues, we predict 4400 new Ebola cases in West Africa during the last half of the month of September, with an upper 95% confidence level of 6800 new cases.

Transmission dynamics of Ebola virus disease and intervention effectiveness in Sierra Leone

“…The growing concern over the repeated emergence of EVD (7,8) has stimulated many studies on these outbreaks, in particular on the most recent one in West Africa, trying to understand the transmission mechanisms and the effectiveness of containment strategies (9)(10)(11)(12)(13)(14)(15)(16)(17)(18). These studies, however, either used limited data at an early stage of the epidemic or assessed a single influential factor.…”

Retrospective Analysis of the 2014–2015 Ebola Epidemic in Liberia

“…For example, the effectiveness of some control programs, such as the cordon sanitaire implemented in Monrovia, Montserrado County, have been questioned, due to lack of public support, infeasibility, and little evidence of incidence reduction. 6,18 By partitioning the epidemic into a primary and a secondary phase, each with its own reproductive number, our model predicts that the transition points-synonymous with decreases in transmission intensity-occurred around September 6 for the earliest epidemic in Lofa County and around December 4 for the latest epidemic in Grand Cape Mount County. For The county-level transition points calculated in this study are generally consistent with a previous country-level phenomenological analysis in Liberia that found an initial reduction in the reproductive number around the week of September 6 and a secondary drop around the week of October 1.…”

Modeling metapopulation dynamics of HIV epidemic on a linear lattice with nearest neighbour coupling

“…Intervention strategies like vaccination, isolation or quarantine, treatment, public health educational campaign, use of contraceptives just to mention but a few, will be effective when the disease dynamics is known. Individual strategy may not be successful as observed by Sherry, et al, [19]. In their study, they used the timeseries data for the Ebola virus disease cases to estimate how the rate of exponential rise of new cases had changed over the outbreak and found that in the effective reproduction, number rose when the outbreak spread to densely populated cities, and the enforced quarantine measures were not effective control measures.…”