Understanding the dynamics of Ebola epidemics

Abstract

Ebola is a highly lethal virus, which has caused at least 14 confirmed outbreaks in Africa between 1976 and 2006. Using data from two epidemics [in Democratic Republic of Congo (DRC) in 1995 and in Uganda in 2000], we built a mathematical model for the spread of Ebola haemorrhagic fever epidemics taking into account transmission in different epidemiological settings. We estimated the basic reproduction number (R0) to be 2.7 (95% CI 1.9-2.8) for the 1995 epidemic in DRC, and 2.7 (95% CI 2.5-4.1) for the 2000 epidemic in Uganda. For each epidemic, we quantified transmission in different settings (illness in the community, hospitalization, and traditional burial) and simulated various epidemic scenarios to explore the impact of control interventions on a potential epidemic. A key parameter was the rapid institution of control measures. For both epidemic profiles identified, increasing hospitalization rate reduced the predicted epidemic size.

Fig. 1

Observed data (□) and fitting curves (—) for (a) the 1995 DRC epidemic and (b) 2000 Uganda epidemic.

Fig. 2

Distribution of the peak of the weekly incidences (left panels) and the final size (right panels) of the epidemic obtained with 1000 runs. The histograms represent the distribution of the peak and the final size of the simulated epidemics when parameters are set to their maximum-likelihood estimates. Black crosses represent observed data.

Fig. 3

Partial rank correlation coefficients (PRCCs) between the cumulative incidences and the five studied intervention parameters. Epidemics were simulated in a population of 100 000 inhabitants with one index case and with values of parameters (except the five intervention parameters) estimated with data from (a) the 1995 DRC epidemic and (b) data from the 2000 Uganda epidemic. These figures represent the PRCC between each varying parameter and the epidemic size x weeks after the onset of symptoms of the index case (x varying between 1 and 51).