Abstract
The unexpected early cessation of the recent West Africa Ebola outbreak demonstrated shortcomings of popular forecasting approaches and has not been fully understood yet. A popular hypothesis is that public health interventions mitigated the spread, such as ETUs and safe burials. We investigate whether risk heterogeneity within the population could serve as an alternative explanation. We introduce a model for spread in heterogeneous host population that is particularly well suited for early predictions due to its simplicity and ease of application. Furthermore, we explore the conditions under which the observed epidemic trajectory can be explained without taking into account the effect of public health interventions. While the obtained fits closely match the total case count time series, closer inspection of sub-population results made us conclude that risk heterogeneity is unlikely to fully explain the early cessation of Ebola; other factors such as behavioral changes and other interventions likely played a major role. More accurate predictions in a future scenario require models that allow for early sub-exponential growth, as well as access to additional data on patient occupation (risk level) and location, to allow identify local phenomena that influence spreading behavior.
Highlights
The devastating 2014 outbreak of Ebola in West Africa was unexpected, as previous outbreaks have been far smaller
The results for Liberia are shown in the main text
The best fits to the case count data require a much higher risk of infection (> 1000 fold) in the high risk population and attribute nearly half of all cases to the high risk population
Summary
The devastating 2014 outbreak of Ebola in West Africa was unexpected, as previous outbreaks have been far smaller. A “perfect storm” of a broken health care system, increased mobility, recent unrest and low public trust were cited to explain the unprecedented scale of the epidemics [1]. Based on the assumption of prolonged exponential growth of the epidemic, exceedingly dire predictions were disseminated by both scientific press [2] and news media outlets [3]. The spread of the epidemic slowed down quicker than expected and eventually ceased, even though the vast majority of people were still susceptible to the virus. Early modeling efforts to predict the likely trajectory in the autumn of 2014 greatly overestimated the size and duration of the outbreak.
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