- Supervisor
- Dr. Stefano Merler, FBK - - Trento
- Date and time
- Saturday, January 16, 2016 at 2:00 PM - Sala verde
- Contact person
- Giandomenico Orlandi
- Publication date
- November 25, 2016
- Department
- Computer Science

The 2014-2015 Ebola virus disease (EVD) epidemic in West Africa represented an unprecedented health threat. In July 2014 an outbreak of EVD started in Pujehun district, Sierra Leone, and on January 10th 2015 the district was the first to be declared Ebola-free by local authorities.

Here we combine epidemiological investigation and modeling techniques to reconstruct the main characteristics of the outbreak and to evaluate the impact of the implemented intervention measures. Specifically, (i) we reconstructed the transmission chain in the district, obtaining information on EVD transmissibility, e.g. individual infectivity, individual susceptibility, basic reproduction number, and on the main routes of infection transmission; (ii) we estimated the key time periods of the epidemic, e.g. incubation period, serial interval; (iii) we gathered quantitative information on the implemented interventions; (iv) we calibrated a detailed mathematical model of EVD transmission informed with all the above information.

We show that (i) the local containment of the outbreak is mainly ascribable to the early availability of a sufficient number of isolation units (“Ebola beds”) in health care settings and massive contact tracing (identification and monitoring of potential contacts of EVD cases), and (ii) EVD transmissibility is strongly affected by the clusterization of the contact network of EVD cases and superspreading events. Finally, we give quantitative insights into the best options for containing an emerging Ebola epidemic at the source. In particular, we show that in case of low to moderate transmissibility future EVD outbreaks can be successfully contained by readily implementing ring vaccination policies, i.e. vaccination of contacts of EVD cases and vaccination of contacts of contacts.

Attached figures (to be mixed and used for graphical purposes on the department announcement web page)

Figure 1. A Fraction of transmission linked to contacts with members of the nuclear family, extended family, close friends, hospital, community and of unknown source, according to the data reported in (4). B Proportion of EVD transmission due to a given proportion of infectious cases in Pujehun district, Sierra Leone (4). Infectious cases are ranked by number of secondary infections generated. The point represents expected percentages under the 20/80 rule. C Probability of observing an outbreak (defined as an epidemic of no less than 3,000 cases, i.e. 1% of the population) after the introduction of one single case in a fully susceptible population (mean and 95%CI, exact binomial test) in the baseline scenario (grey) and as predicted by the classical theory (Rindex=1.67) that does not account for clustering (i.e., all contacts occur at random in the overall population – 0% clustered transmission) and individual heterogeneity in infectiousness (i.e., all individuals are equally infectious - k=∞) (brown). D Instantaneous reproduction number of baseline simulations (grey line, mean; shaded area, 95%CI) compared to estimates reported in (4) (blue points represent the average number of secondary infections per primary case at different generations of cases and vertical bars represent the observed range). The horizontal dashed line represents the elimination threshold. E Instantaneous reproduction number of baseline simulations and as resulting from the classical theory (solid lines, colors as in C), and corresponding mean cumulative number of cases (dashed lines, colors as in C). The horizontal dashed line represent the epidemic threshold Rt=1. F Final attack rate of baseline simulations and as resulting from the classical theory (solid lines, colors as in C). Model estimates reported in panels C-F are based on the analysis of a variable number of simulations, such that 1,000 simulations result in an epidemic outbreak.

Here we combine epidemiological investigation and modeling techniques to reconstruct the main characteristics of the outbreak and to evaluate the impact of the implemented intervention measures. Specifically, (i) we reconstructed the transmission chain in the district, obtaining information on EVD transmissibility, e.g. individual infectivity, individual susceptibility, basic reproduction number, and on the main routes of infection transmission; (ii) we estimated the key time periods of the epidemic, e.g. incubation period, serial interval; (iii) we gathered quantitative information on the implemented interventions; (iv) we calibrated a detailed mathematical model of EVD transmission informed with all the above information.

We show that (i) the local containment of the outbreak is mainly ascribable to the early availability of a sufficient number of isolation units (“Ebola beds”) in health care settings and massive contact tracing (identification and monitoring of potential contacts of EVD cases), and (ii) EVD transmissibility is strongly affected by the clusterization of the contact network of EVD cases and superspreading events. Finally, we give quantitative insights into the best options for containing an emerging Ebola epidemic at the source. In particular, we show that in case of low to moderate transmissibility future EVD outbreaks can be successfully contained by readily implementing ring vaccination policies, i.e. vaccination of contacts of EVD cases and vaccination of contacts of contacts.

Attached figures (to be mixed and used for graphical purposes on the department announcement web page)

Figure 1. A Fraction of transmission linked to contacts with members of the nuclear family, extended family, close friends, hospital, community and of unknown source, according to the data reported in (4). B Proportion of EVD transmission due to a given proportion of infectious cases in Pujehun district, Sierra Leone (4). Infectious cases are ranked by number of secondary infections generated. The point represents expected percentages under the 20/80 rule. C Probability of observing an outbreak (defined as an epidemic of no less than 3,000 cases, i.e. 1% of the population) after the introduction of one single case in a fully susceptible population (mean and 95%CI, exact binomial test) in the baseline scenario (grey) and as predicted by the classical theory (Rindex=1.67) that does not account for clustering (i.e., all contacts occur at random in the overall population – 0% clustered transmission) and individual heterogeneity in infectiousness (i.e., all individuals are equally infectious - k=∞) (brown). D Instantaneous reproduction number of baseline simulations (grey line, mean; shaded area, 95%CI) compared to estimates reported in (4) (blue points represent the average number of secondary infections per primary case at different generations of cases and vertical bars represent the observed range). The horizontal dashed line represents the elimination threshold. E Instantaneous reproduction number of baseline simulations and as resulting from the classical theory (solid lines, colors as in C), and corresponding mean cumulative number of cases (dashed lines, colors as in C). The horizontal dashed line represent the epidemic threshold Rt=1. F Final attack rate of baseline simulations and as resulting from the classical theory (solid lines, colors as in C). Model estimates reported in panels C-F are based on the analysis of a variable number of simulations, such that 1,000 simulations result in an epidemic outbreak.

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