Potential for large outbreaks of Ebola virus disease.
Bottom Line: By fitting a mathematical model to time series stratified by disease onset, outcome and source of infection, we were able to estimate several epidemiological quantities that have previously proved challenging to measure, including the contribution of hospital and community infection to transmission.Our analysis suggests that the person-to-person reproduction number was 1.34 (95% CI: 0.92-2.11) in the early part of the outbreak.Using stochastic simulations we demonstrate that the same epidemiological conditions that were present in 1976 could have generated a large outbreak purely by chance.
Affiliation: Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom. Electronic address: email@example.com.Show MeSH
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Mentions: We used a compartmental model of infection to analyse the temporal dynamics of Ebola (Legrand et al., 2007). The model structure is outlined in Fig. 2. We assumed that individuals start off susceptible to infection (S). Upon infection they enter an incubation period (E), then become symptomatic and infectious in the community (I). We therefore assume that the latent and incubation periods are equivalent. After this point, they either: enter a recovered state (R); remain infectious and go into hospital (H); or die and remain infectious (D) until buried (B). Following hospitalisation, infectious hosts also move either into the recovered or dead compartment.
Affiliation: Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom. Electronic address: firstname.lastname@example.org.