BACKGROUND Ebola virus has been detected in the semen of men after their recovery from Ebola virus disease (EVD). We report the presence of Ebola virus RNA in semen in a cohort of survivors of EVD in Sierra Leone. METHODS We enrolled a convenience sample of 220 adult male survivors of EVD in Sierra Leone, at various times after discharge from an Ebola treatment unit (ETU), in two phases (100 participants were in phase 1, and 120 in phase 2). Semen specimens obtained at baseline were tested by means of a quantitative reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assay with the use of the target sequences of NP and VP40 (in phase 1) or NP and GP (in phase 2). This study did not evaluate directly the risk of sexual transmission of EVD. RESULTS Of 210 participants who provided an initial semen specimen for analysis, 57 (27%) had positive results on quantitative RT-PCR. Ebola virus RNA was detected in the semen of all 7 men with a specimen obtained within 3 months after ETU discharge, in 26 of 42 (62%) with a specimen obtained at 4 to 6 months, in 15 of 60 (25%) with a specimen obtained at 7 to 9 months, in 4 of 26 (15%) with a specimen obtained at 10 to 12 months, in 4 of 38 (11%) with a specimen obtained at 13 to 15 months, in 1 of 25 (4%) with a specimen obtained at 16 to 18 months, and in no men with a specimen obtained at 19 months or later. Among the 46 participants with a positive result in phase 1, the median baseline cycle-threshold values (higher values indicate lower RNA values) for the NP and VP40 targets were lower within 3 months after ETU discharge (32.4 and 31.3, respectively; in 7 men) than at 4 to 6 months (34.3 and 33.1; in 25), at 7 to 9 months (37.4 and 36.6; in 13), and at 10 to 12 months (37.7 and 36.9; in 1). In phase 2, a total of 11 participants had positive results for NP and GP targets (samples obtained at 4.1 to 15.7 months after ETU discharge); cycle-threshold values ranged from 32.7 to 38.0 for NP and from 31.1 to 37.7 for GP. CONCLUSIONS These data showed the long-term presence of Ebola virus RNA in semen and declining persistence with increasing time after ETU discharge. (Funded by the World Health Organization and others.)

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The 2013–2016 Ebola outbreak in West Africa is the largest on record with 28 616 confirmed, probable and suspected cases and 11 310 deaths officially recorded by 10 June 2016, the true burden probably considerably higher. The case fatality ratio (CFR: proportion of cases that are fatal) is a key indicator of disease severity useful for gauging the appropriate public health response and for evaluating treatment benefits, if estimated accurately. We analysed individual-level clinical outcome data from Guinea, Liberia and Sierra Leone officially reported to the World Health Organization. The overall mean CFR was 62.9% (95% CI: 61.9% to 64.0%) among confirmed cases with recorded clinical outcomes. Age was the most important modifier of survival probabilities, but country, stage of the epidemic and whether patients were hospitalized also played roles. We developed a statistical analysis to detect outliers in CFR between districts of residence and treatment centres (TCs), adjusting for known factors influencing survival and identified eight districts and three TCs with a CFR significantly different from the average. From the current dataset, we cannot determine whether the observed variation in CFR seen by district or treatment centre reflects real differences in survival, related to the quality of care or other factors or was caused by differences in reporting practices or case ascertainment.This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

BackgroundThe ongoing West African Ebola epidemic began in December 2013 in Guinea, probably from a single zoonotic introduction. As a result of ineffective initial control efforts, an Ebola outbreak of unprecedented scale emerged. As of 4 May 2015, it had resulted in more than 19,000 probable and confirmed Ebola cases, mainly in Guinea (3,529), Liberia (5,343), and Sierra Leone (10,746). Here, we present analyses of data collected during the outbreak identifying drivers of transmission and highlighting areas where control could be improved.Methods and FindingsOver 19,000 confirmed and probable Ebola cases were reported in West Africa by 4 May 2015. Individuals with confirmed or probable Ebola (“cases”) were asked if they had exposure to other potential Ebola cases (“potential source contacts”) in a funeral or non-funeral context prior to becoming ill. We performed retrospective analyses of a case line-list, collated from national databases of case investigation forms that have been reported to WHO. These analyses were initially performed to assist WHO’s response during the epidemic, and have been updated for publication.We analysed data from 3,529 cases in Guinea, 5,343 in Liberia, and 10,746 in Sierra Leone; exposures were reported by 33% of cases. The proportion of cases reporting a funeral exposure decreased over time. We found a positive correlation (r = 0.35, p < 0.001) between this proportion in a given district for a given month and the within-district transmission intensity, quantified by the estimated reproduction number (R). We also found a negative correlation (r = −0.37, p < 0.001) between R and the district proportion of hospitalised cases admitted within ≤4 days of symptom onset. These two proportions were not correlated, suggesting that reduced funeral attendance and faster hospitalisation independently influenced local transmission intensity. We were able to identify 14% of potential source contacts as cases in the case line-list. Linking cases to the contacts who potentially infected them provided information on the transmission network. This revealed a high degree of heterogeneity in inferred transmissions, with only 20% of cases accounting for at least 73% of new infections, a phenomenon often called super-spreading. Multivariable regression models allowed us to identify predictors of being named as a potential source contact. These were similar for funeral and non-funeral contacts: severe symptoms, death, non-hospitalisation, older age, and travelling prior to symptom onset. Non-funeral exposures were strongly peaked around the death of the contact. There was evidence that hospitalisation reduced but did not eliminate onward exposures. We found that Ebola treatment units were better than other health care facilities at preventing exposure from hospitalised and deceased individuals. The principal limitation of our analysis is limited data quality, with cases not being entered into the database, cases not reporting exposures, or data being entered incorrectly (especially dates, and possible mis...