The 2014 Ebola virus disease outbreak in Pujehun, Sierra Leone: epidemiology and impact of interventions

BACKGROUND: In July 2014, an outbreak of Ebola virus disease (EVD) started in Pujehun district, Sierra Leone. On January 10th, 2015, the district was the first to be declared Ebola-free by local authorities after 49 cases and a case fatality rate of 85.7 %. The Pujehun outbreak represents a precious opportunity for improving the body of work on the transmission characteristics and effects of control interventions during the 2014–2015 EVD epidemic in West Africa. METHODS: By integrating hospital registers and contact tracing form data with healthcare worker and local population interviews, we reconstructed the transmission chain and investigated the key time periods of EVD transmission. The impact of intervention measures has been assessed using a microsimulation transmission model calibrated with the collected data. RESULTS: The mean incubation period was 9.7 days (range, 6–15). Hospitalization rate was 89 %. The mean time from the onset of symptoms to hospitalization was 4.5 days (range, 1–9). The mean serial interval was 13.7 days (range, 2–18). The distribution of the number of secondary cases (R(0) = 1.63) was well fitted by a negative binomial distribution with dispersion parameter k = 0.45 (95 % CI, 0.19–1.32). Overall, 74.3 % of transmission events occurred between members of the same family or extended family, 17.9 % in the community, mainly between friends, and 7.7 % in hospital. The mean number of contacts investigated per EVD case raised from 11.5 in July to 25 in September 2014. In total, 43.0 % of cases were detected through contact investigation. Model simulations suggest that the most important factors determining the probability of disease elimination are the number of EVD beds, the mean time from symptom onset to isolation, and the mean number of contacts traced per case. By assuming levels and timing of interventions performed in Pujehun, the estimated probability of eliminating an otherwise large EVD outbreak is close to 100 %. CONCLUSIONS: Containment of EVD in Pujehun district is ascribable to both the natural history of the disease (mainly transmitted through physical contacts, long generation time, overdispersed distribution of secondary cases per single primary case) and intervention measures (isolation of cases and contact tracing), which in turn strongly depend on preparedness, population awareness, and compliance. Our findings are also essential to determine a successful ring vaccination strategy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-015-0524-z) contains supplementary material, which is available to authorized users

Bartolomeo S: Evaluation of lung ultrasound for the diagnosis of pneumonia

Abstract Objectives: The aim of this study is to assess the ability of bedside lung ultrasound (US) to confirm clinical suspicion of pneumonia and the feasibility of its integration in common emergency department (ED) clinical practice. Methods: In this study we performed lung US in adult patients admitted in our ED with a suspected pneumonia.Subsequently, a chest radiograph (CXR) was carried out for each patient. A thoracic computed tomographic (CT) scan was made in patients with a positive lung US and a negative CXR. In patients with confirmed pneumonia, we performed a follow-up after 10 days to evaluate clinical conditions after antibiotic therapy. Results: We studied 49 patients: pneumonia was confirmed in 32 cases (65.3%). In this group we had 31 (96.9%) positive lung US and 24 (75%) positive CXR. In 8 (25%) cases, lung US was positive with a negative CXR. In this group, CT scan always confirmed the US results. In one case, US was negative and CXR positive. Follow-up turned out to be always consistent with the diagnosis. Conclusion: Considering that lung US is a bedside, reliable, rapid, and noninvasive technique, these results suggest it could have a significant role in the diagnostic workup of pneumonia in the ED, even if no sensitivity nor specificity can be inferred from this study because the real gold standard is CT, which could not be performed in all patients

The 2014 Ebola virus disease outbreak in Pujehun, Sierra Leone: epidemiology and impact of interventions

Background In July 2014, an outbreak of Ebola virus disease (EVD) started in Pujehun district, Sierra Leone. On January 10th, 2015, the district was the first to be declared Ebola-free by local authorities after 49 cases and a case fatality rate of 85.7 %. The Pujehun outbreak represents a precious opportunity for improving the body of work on the transmission characteristics and effects of control interventions during the 2014–2015 EVD epidemic in West Africa. Methods By integrating hospital registers and contact tracing form data with healthcare worker and local population interviews, we reconstructed the transmission chain and investigated the key time periods of EVD transmission. The impact of intervention measures has been assessed using a microsimulation transmission model calibrated with the collected data. Results The mean incubation period was 9.7 days (range, 6–15). Hospitalization rate was 89 %. The mean time from the onset of symptoms to hospitalization was 4.5 days (range, 1–9). The mean serial interval was 13.7 days (range, 2–18). The distribution of the number of secondary cases (R 0  = 1.63) was well fitted by a negative binomial distribution with dispersion parameter k = 0.45 (95 % CI, 0.19–1.32). Overall, 74.3 % of transmission events occurred between members of the same family or extended family, 17.9 % in the community, mainly between friends, and 7.7 % in hospital. The mean number of contacts investigated per EVD case raised from 11.5 in July to 25 in September 2014. In total, 43.0 % of cases were detected through contact investigation. Model simulations suggest that the most important factors determining the probability of disease elimination are the number of EVD beds, the mean time from symptom onset to isolation, and the mean number of contacts traced per case. By assuming levels and timing of interventions performed in Pujehun, the estimated probability of eliminating an otherwise large EVD outbreak is close to 100 %. Conclusions Containment of EVD in Pujehun district is ascribable to both the natural history of the disease (mainly transmitted through physical contacts, long generation time, overdispersed distribution of secondary cases per single primary case) and intervention measures (isolation of cases and contact tracing), which in turn strongly depend on preparedness, population awareness, and compliance. Our findings are also essential to determine a successful ring vaccination strategy

The hidden burden of measles in Ethiopia: how distance to hospital shapes the disease mortality rate

Abstract Background A sequence of annual measles epidemics has been observed from January 2013 to April 2017 in the South West Shoa Zone of the Oromia Region, Ethiopia. We aimed at estimating the burden of disease in the affected area, taking into account inequalities in access to health care due to travel distances from the nearest hospital. Methods We developed a dynamic transmission model calibrated on the time series of hospitalized measles cases. The model provided estimates of disease transmissibility and incidence at a population level. Model estimates were combined with a spatial analysis to quantify the hidden burden of disease and to identify spatial heterogeneities characterizing the effectiveness of the public health system in detecting severe measles infections and preventing deaths. Results A total of 1819 case patients and 36 deaths were recorded at the hospital. The mean age was 6.0 years (range, 0–65). The estimated reproduction number was 16.5 (95% credible interval (CI) 14.5–18.3) with a cumulative disease incidence of 2.34% (95% CI 2.06–2.66). Three thousand eight hundred twenty-one (95% CI 1969–5671) severe cases, including 2337 (95% CI 716–4009) measles-related deaths, were estimated in the Woliso hospital’s catchment area (521,771 inhabitants). The case fatality rate was found to remarkably increase with travel distance from the nearest hospital: ranging from 0.6% to more than 19% at 20 km. Accordingly, hospital treatment prevented 1049 (95% CI 757–1342) deaths in the area. Conclusions Spatial heterogeneity in the access to health care can dramatically affect the burden of measles disease in low-income settings. In sub-Saharan Africa, passive surveillance based on hospital admitted cases might miss up to 60% of severe cases and 98% of related deaths

Additional file 1:Â contact tracing form. of The 2014 Ebola virus disease outbreak in Pujehun, Sierra Leone: epidemiology and impact of interventions

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Additional file 3:Â additional methods. of The 2014 Ebola virus disease outbreak in Pujehun, Sierra Leone: epidemiology and impact of interventions

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Containing Ebola at the Source with Ring Vaccination

<div><p>Interim results from the Guinea Ebola ring vaccination trial suggest high efficacy of the rVSV-ZEBOV vaccine. These findings open the door to the use of ring vaccination strategies in which the contacts and contacts of contacts of each index case are promptly vaccinated to contain future Ebola virus disease outbreaks. To provide a numerical estimate of the effectiveness of ring vaccination strategies we introduce a spatially explicit agent-based model to simulate Ebola outbreaks in the Pujehun district, Sierra Leone, structurally similar to previous modelling approaches. We find that ring vaccination can successfully contain an outbreak for values of the effective reproduction number up to 1.6. Through an extensive sensitivity analysis of parameters characterising the readiness and capacity of the health care system, we identify interventions that, alongside ring vaccination, could increase the likelihood of containment. In particular, shortening the time from symptoms onset to hospitalisation to 2–3 days on average through improved contact tracing procedures, adding a 2km spatial component to the vaccination ring, and decreasing human mobility by quarantining affected areas might contribute increase our ability to contain outbreaks with effective reproduction number up to 2.6. These results have implications for future control of Ebola and other emerging infectious disease threats.</p></div

Ring vaccination with baseline parameters.

<p><b>A</b> Probability (with 95%CI; exact binomial test) of an uncontained outbreak (more than 300 cases) after introducing one infected case into a fully susceptible population for a range of <i>R_e</i> values. The dashed line represents the theoretical value 1 − 1/<i>R_e</i> under a homogeneous mixing assumption. <b>B</b> Estimated epidemic prevention potential and 95%CI for a range of <i>R_e</i> values. The shaded grey area denotes the most plausible <i>R_e</i> values for the 2014–15 West African epidemic. <b>C</b> Mean number of vaccine doses and 95%CIs for containing an outbreak for a range of <i>R_e</i> values. <b>D</b> As C but for the number of rings defined. Each estimate is based on 1,000 simulated outbreaks.</p

Sensitivity analysis.

<p><b>A</b> Estimated epidemic prevention potential (points) and 95%CI (vertical lines) as a function of <i>R_e</i> and by varying the vaccine coverage. Baseline coverage: 65% [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005093#pntd.0005093.ref004" target="_blank">4</a>]. The shaded grey area represents the range of most plausible values of <i>R_e</i> for the 2014–15 epidemic in West Africa. <b>B</b> As in <b>A</b> but by varying the eligible population. Symbols: C indicates contacts of index cases; CC indicates contacts of contacts; S indicates geographical rings (ring radius: 2 km). Baseline value: C&CC [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005093#pntd.0005093.ref004" target="_blank">4</a>]. <b>C</b> As in <b>A</b> but by varying the parameter regulating human mobility. Spatial transmission is proportional to a power law kernel 1/(1 + d^b) where <i>d</i> is the geographical distance and <i>b</i> regulates the decrease of transmission with distance. Baseline value: <i>b</i> = 2.25, resulting in an average distance of 7.7 km [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005093#pntd.0005093.ref023" target="_blank">23</a>]. Other scenarios assume different values of <i>b</i>, corresponding to an average distance ranging from 1.5 to 25 km. In these scenarios, probabilities of outbreaks in the absence of interventions were recomputed for each value of the parameter <i>b</i>. <b>D</b> As in <b>A</b> but by varying the time from symptoms onset to hospitalisation. Baseline value: 4 days [<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0005093#pntd.0005093.ref009" target="_blank">9</a>]. Each estimate is based on 1,000 simulated outbreaks.</p

Model parameter values.

<p>Model parameter values.</p