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. 2017 May 26;372(1721):20160302.
doi: 10.1098/rstb.2016.0302.

The impact of control strategies and behavioural changes on the elimination of Ebola from Lofa County, Liberia

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The impact of control strategies and behavioural changes on the elimination of Ebola from Lofa County, Liberia

Sebastian Funk et al. Philos Trans R Soc Lond B Biol Sci. .

Abstract

The Ebola epidemic in West Africa was stopped by an enormous concerted effort of local communities and national and international organizations. It is not clear, however, how much the public health response and behavioural changes in affected communities, respectively, contributed to ending the outbreak. Here, we analyse the epidemic in Lofa County, Liberia, lasting from March to November 2014, by reporting a comprehensive time line of events and estimating the time-varying transmission intensity using a mathematical model of Ebola transmission. Model fits to the epidemic show an alternation of peaks and troughs in transmission, consistent with highly heterogeneous spread. This is combined with an overall decline in the reproduction number of Ebola transmission from early August, coinciding with an expansion of the local Ebola treatment centre. We estimate that healthcare seeking approximately doubled over the course of the outbreak, and that isolation of those seeking healthcare reduced their reproduction number by 62% (mean estimate, 95% credible interval (CI) 59-66). Both expansion of bed availability and improved healthcare seeking contributed to ending the epidemic, highlighting the importance of community engagement alongside clinical intervention.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Keywords: behavioural changes; community engagement; infectious disease dynamics; interventions; isolation; mathematical model.

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Conflict of interest statement

We have no competing interests.

Figures

Figure 1.
Figure 1.
Schematic of the model. The transitions used to calculate the weekly incidence of ETU admissions that was compared with the data are coloured in red, infectious compartments are shaded red and the compartments inside the ETC marked by a box.
Figure 2.
Figure 2.
Timeline of the EVD epidemic in Lofa County. (a–e) Data: number of hospital admissions, community deaths, days from onset to ETC admission (median and IQR), people reached by MSF health promotion (HP) activities, time line of events. (f,g) Modelling results: community reproduction number (i.e. the reproduction number in the absence of isolation beds) and the proportion of patients seeking healthcare. Black line: median; grey area: interquartile range.
Figure 3.
Figure 3.
Geographical progression of the epidemic. Shades of grey indicate the number of Ebola cases admitted to the ETC, darker shades reflecting more cases (maximum: 59 in Quardu Bundi district, August).
Figure 4.
Figure 4.
Model and data. Model fits to hospital admissions. Median: black line, IQR: dark shaded area, 95% credible interval: light shaded area. Data on weekly ETC admissions are shown as points. The shown fits are filtered trajectories from the posterior distribution of simulated observations.
Figure 5.
Figure 5.
Incidence of EVD under alternative scenarios. Incidence under the alternative scenarios of (a) lower ETC capacity and (b) no improvements in healthcare-seeking behaviour. Shown are the median (line) and IQR (shaded area) at each time point.

References

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