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

The basic reproduction number (R0) of ebola virus disease: A systematic review and meta-analysis

BACKGROUND

Ebola virus disease (Ebola) is highly pathogenic, transmissible, and often deadly, with debilitating consequences. Superspreading within a cluster is also possible. In this study, we aim to document Ebola basic reproduction number (R0): the average number of new cases associated with an Ebola case in a completely susceptible population.

METHODS

We undertook a systematic review and meta-analysis. We searched PubMed, EMBASE, and Web of Science for studies published between 1976 and February 27, 2023. We also manually searched the reference lists of the reviewed studies to identify additional studies. We included studies that reported R0 during Ebola outbreaks in Africa. We excluded studies that reported only the effective reproduction number (Rt). Abstracting data from included studies was performed using a pilot-tested standard form. Two investigators reviewed the studies, extracted the data, and assessed quality. The pooled R0 was determined by a random-effects meta-analysis. R0 was stratified by country. We also estimated the theoretically required immunization coverage to reach herd-immunity using the formula of (1-1/R0) × 100 %.

RESULTS

The search yielded 2042 studies. We included 53 studies from six African countries in the systematic review providing 97 Ebola mean R0 estimates. 27 (with 46 data points) studies were included in the meta-analysis. The overall pooled mean Ebola R0 was 1.95 (95 % CI 1.74-2.15), with high heterogeneity (I2 = 99.99 %; τ2 = 0.38; and p < 0.001) and evidence of small-study effects (Egger's statistics: Z = 4.67; p < 0.001). Mean Ebola R0 values ranged from 1.2 to 10.0 in Nigeria, 1.1 to 7 in Guinea, 1.14 to 8.33 in Sierra Leone, 1.13 to 5 in Liberia, 1.2 to 5.2 in DR Congo, 1.34 to 2.7 in Uganda, and from 1.40 to 2.55 for all West African countries combined. Pooled mean Ebola R0 was 9.38 (95 % CI 4.16-14.59) in Nigeria, 3.31 (95 % CI 2.30-4.32) in DR Congo, 2.0 (95 % CI 1.25-2.76) in Uganda, 1.83 (95 % CI 1.61-2.05) in Liberia, 1.73 (95 % CI 1.47-2.0) in Sierra Leonne, and 1.44 (95 % CI 1.29-1.60) in Guinea. In theory, 50 % of the population needs to be vaccinated to achieve herd immunity, assuming that Ebola vaccine would be 100 % effective.

CONCLUSIONS

Ebola R0 varies widely across countries. Ebola has a much wider R0 range than is often claimed (1.3-2.0). It is possible for an Ebola index case to infect more than two susceptible individuals.

Predicting the combined effects of case isolation, safe funeral practices, and contact tracing during Ebola virus disease outbreaks

BACKGROUND

The recent outbreaks of Ebola virus disease (EVD) in Uganda and the Marburg virus disease (MVD) in Ghana reflect a persisting threat of Filoviridae to the global health community. Characteristic of Filoviridae are not just their high case fatality rates, but also that corpses are highly contagious and prone to cause infections in the absence of appropriate precautions. Vaccines against the most virulent Ebolavirus species, the Zaire ebolavirus (ZEBOV) are approved. However, there exists no approved vaccine or treatment against the Sudan ebolavirus (SUDV) which causes the current outbreak of EVD. Hence, the control of the outbreak relies on case isolation, safe funeral practices, and contact tracing. So far, the effectiveness of these control measures was studied only separately by epidemiological models, while the impact of their interaction is unclear.

METHODS AND FINDINGS

To sustain decision making in public health-emergency management, we introduce a predictive model to study the interaction of case isolation, safe funeral practices, and contact tracing. The model is a complex extension of an SEIR-type model, and serves as an epidemic preparedness tool. The model considers different phases of the EVD infections, the possibility of infections being treated in isolation (if appropriately diagnosed), in hospital (if not properly diagnosed), or at home (if the infected do not present to hospital for whatever reason). It is assumed that the corpses of those who died in isolation are buried with proper safety measures, while those who die outside isolation might be buried unsafely, such that transmission can occur during the funeral. Furthermore, the contacts of individuals in isolation will be traced. Based on parameter estimates from the scientific literature, the model suggests that proper diagnosis and hence isolation of cases has the highest impact in reducing the size of the outbreak. However, the combination of case isolation and safe funeral practices alone are insufficient to fully contain the epidemic under plausible parameters. This changes if these measures are combined with contact tracing. In addition, shortening the time to successfully trace back contacts contribute substantially to contain the outbreak.

CONCLUSIONS

In the absence of an approved vaccine and treatment, EVD management by proper and fast diagnostics in combination with epidemic awareness are fundamental. Awareness will particularly facilitate contact tracing and safe funeral practices. Moreover, proper and fast diagnostics are a major determinant of case isolation. The model introduced here is not just applicable to EVD, but also to other viral hemorrhagic fevers such as the MVD or the Lassa fever.

Non-human primate to human immunobridging demonstrates a protective effect of Ad26.ZEBOV, MVA-BN-Filo vaccine against Ebola

Without clinical efficacy data, vaccine protective effect may be extrapolated from animals to humans using an immunologic marker that correlates with protection in animals. This immunobridging approach was used for the two-dose Ebola vaccine regimen Ad26.ZEBOV, MVA-BN-Filo. Ebola virus (EBOV) glycoprotein binding antibody data obtained from 764 vaccinated healthy adults in five clinical studies (NCT02416453, NCT02564523, NCT02509494, NCT02543567, NCT02543268) were used to calculate mean predicted survival probability (with preplanned 95% confidence interval [CI]). We used a logistic regression model based on EBOV glycoprotein binding antibody responses in vaccinated non-human primates (NHPs) and NHP survival after EBOV challenge. While the protective effect of the vaccine regimen in humans can be inferred in this fashion, the extrapolated survival probability cannot be directly translated into vaccine efficacy. The primary immunobridging analysis evaluated the lower limit of the CI against predefined success criterion of 20% and passed with mean predicted survival probability of 53.4% (95% CI: 36.7-67.4).

Social Network Analysis of Ebola Virus Disease During the 2014 Outbreak in Sukudu, Sierra Leone

Background

Transmission by unreported cases has been proposed as a reason for the 2013-2016 Ebola virus (EBOV) epidemic decline in West Africa, but studies that test this hypothesis are lacking. We examined a transmission chain within social networks in Sukudu village to assess spread and transmission burnout.

Methods

Network data were collected in 2 phases: (1) serological and contact information from Ebola cases (n = 48, including unreported); and (2) interviews (n = 148), including Ebola survivors (n = 13), to identify key social interactions. Social links to the transmission chain were used to calculate cumulative incidence proportion as the number of EBOV-infected people in the network divided by total network size.

Results

The sample included 148 participants and 1522 contacts, comprising 10 social networks: 3 had strong links (>50% of cases) to the transmission chain: household sharing (largely kinship), leisure time, and talking about important things (both largely non-kin). Overall cumulative incidence for these networks was 37 of 311 (12%). Unreported cases did not have higher network centrality than reported cases.

Conclusions

Although this study did not find evidence that explained epidemic decline in Sukudu, it excluded potential reasons (eg, unreported cases, herd immunity) and identified 3 social interactions in EBOV transmission.

Building the Sierra Leone Ebola Database: organization and characteristics of data systematically collected during 2014-2015 Ebola epidemic

PURPOSE

During the 2014-2016 Ebola outbreak in West Africa, the Sierra Leone Ministry of Health and Sanitation (MoHS), the US Centers for Disease Control and Prevention, and responding partners under the coordination of the National Ebola Response Center (NERC) and the MoHS's Emergency Operation Center (EOC) systematically recorded information from the 117 Call Center system and district alert phone lines, case investigations, laboratory sample testing, clinical management, and safe and dignified burial records. Since 2017, CDC assisted MoHS in building and managing the Sierra Leone Ebola Database (SLED) to consolidate these major data sources. The primary objectives of the project were helping families to identify the location of graves of their loved ones who died at the time of the Ebola epidemic through the SLED Family Reunification Program and creating a data source for epidemiological research. The objective of this paper is to describe the process of consolidating epidemic records into a useful and accessible data collection and to summarize data characteristics, strength, and limitations of this unique information source for public health research.

METHODS

Because of the unprecedented conditions during the epidemic, most of the records collected from responding organizations required extensive processing before they could be used as a data source for research or the humanitarian purpose of locating burial sites. This process required understanding how the data were collected and used during the outbreak. To manage the complexity of processing the data obtained from various sources, the Sierra Leone Ebola Database (SLED) Team used an organizational strategy that allowed tracking of the data provenance and lifecycle.

RESULTS

The SLED project brought raw data into one consolidated data collection. It provides researchers with secure and ethical access to the SLED data and serves as a basis for the research capacity building in Sierra Leone. The SLED Family Reunification Program allowed Sierra Leonean families to identify location of the graves of loved ones who died during the Ebola epidemic.

CONCLUSIONS

The SLED project consolidated and utilized epidemic data recorded during the Sierra Leone Ebola Virus Disease outbreak that were collected and contributed to SLED by national and international organizations. This project has provided a foundation for developing a method of ethical and secure SLED data access while preserving the host nation's data ownership. SLED serves as a data source for the SLED Family Reunification Program and for epidemiological research. It presents an opportunity for building research capacity in Sierra Leone and provides a foundation for developing a relational database. Large outbreak data systems such as SLED provide a unique opportunity for researchers to improve responses to epidemics and indicate the need to include data management preparedness in the plans for emergency response.

Ebola virus outbreak preparedness plan for developing Nations: Lessons learnt from affected countries

BACKGROUND

Ebola virus (EBOV); a public health emergency of international concern,is known to pose threat of global outbreaks. EBOV has spread in African continent and due to unchecked international travel, importation of cases has been reported in different countries. In this alarming scenario, developing countries need to evaluate and upgrade their preparedness plan to contain the spread of EBOV. The present review lays down the updated preparedness plan for developing countries to contain future EBOV outbreaks.

METHODS

The literature on EBOV outbreaks and preparedness strategies reported were searched on Pubmed and Google Scholar using the MeSH terms such as "Ebola virus disease, Epidemic, Outbreak, Imported case, Preparedness, Public health interventions" combined with Boolean operator (OR) for the period of 2011-2020. Additionally, World Health organization (WHO) and Centers for Disease Control & Prevention (CDC) websites were searched for the guidelines, reports, containment strategies, containment plan of countries, actions taken by countries and international partners, etc. RESULTS: The present review analyzed the EBOV outbreaks between 2011-2020 and containment strategies used by the affected countries. Based on the lessons learned from EBOV outbreaks and personal experience in infectious disease management, we have recommended a preparedness and response plan for EBOV containment in developing countries.

CONCLUSION

Developing countries are particularly vulnerable to major outbreaks of EBOV due to increased international travel and unchecked transmission. The recommended preparedness plan will help developing counties to contain EBOV outbreaks in future.

Nonhuman primate to human immunobridging to infer the protective effect of an Ebola virus vaccine candidate

It has been proven challenging to conduct traditional efficacy trials for Ebola virus (EBOV) vaccines. In the absence of efficacy data, immunobridging is an approach to infer the likelihood of a vaccine protective effect, by translating vaccine immunogenicity in humans to a protective effect, using the relationship between vaccine immunogenicity and the desired outcome in a suitable animal model. We here propose to infer the protective effect of the Ad26.ZEBOV, MVA-BN-Filo vaccine regimen with an 8-week interval in humans by immunobridging. Immunogenicity and protective efficacy data were obtained for Ad26.ZEBOV and MVA-BN-Filo vaccine regimens using a fully lethal EBOV Kikwit challenge model in cynomolgus monkeys (nonhuman primates [NHP]). The association between EBOV neutralizing antibodies, glycoprotein (GP)-binding antibodies, and GP-reactive T cells and survival in NHP was assessed by logistic regression analysis. Binding antibodies against the EBOV surface GP were identified as the immune parameter with the strongest correlation to survival post EBOV challenge, and used to infer the predicted protective effect of the vaccine in humans using published data from phase I studies. The human vaccine-elicited EBOV GP-binding antibody levels are in a range associated with significant protection against mortality in NHP. Based on this immunobridging analysis, the EBOV GP-specific-binding antibody levels elicited by the Ad26.ZEBOV, MVA-BN-Filo vaccine regimen in humans will likely provide protection against EBOV disease.

Outbreak response intervention models of vaccine-preventable diseases in humans and foot-and-mouth disease in livestock: a protocol for a systematic review

INTRODUCTION

Outbreaks of vaccine-preventable diseases continue to threaten public health, despite the proven effectiveness of vaccines. Interventions such as vaccination, social distancing and palliative care are usually implemented, either individually or in combination, to control these outbreaks. Mathematical models are often used to assess the impact of these interventions and for supporting outbreak response decision making. The objectives of this systematic review, which covers all human vaccine-preventable diseases, are to determine the relative impact of vaccination compared with other outbreak interventions, and to ascertain the temporal trends in the use of modelling in outbreak response decision making. We will also identify gaps and opportunities for future research through a comparison with the foot-and-mouth disease outbreak response modelling literature, which has good examples of the use of modelling to inform outbreak response intervention decision making.

METHODS AND ANALYSIS

We searched on PubMed, Scopus, Web of Science, Google Scholar and some preprint servers from the start of indexing to 15 January 2020. Inclusion: modelling studies, published in English, that use a mechanistic approach to evaluate the impact of an outbreak intervention. Exclusion: reviews, and studies that do not describe or use mechanistic models or do not describe an outbreak. We will extract data from the included studies such as their objectives, model types and composition, and conclusions on the impact of the intervention. We will ascertain the impact of models on outbreak response decision making through visualisation of time trends in the use of the models. We will also present our results in narrative style.

ETHICS AND DISSEMINATION

This systematic review will not require any ethics approval since it only involves scientific articles. The review will be disseminated in a peer-reviewed journal and at various conferences fitting its scope.

PROSPERO REGISTRATION NUMBER

CRD42020160803.

Production and Characterization of Monoclonal Antibodies Against Gp Protein of Ebola Virus

The DNA fragment encoding predicted main antigenic region, aa 1-300 on Gp protein of Ebola virus (EBOV) was cloned into the vector pGEX-KG. The recombinant GST-tagged Gp-300 was expressed in Escherichia coli BL21 (DE3) by induction with 1 mM isopropyl-1-thio-b-d-galactoside and purified by dialysis. Four monoclonal antibodies (mAbs) named 1C4, 2A3, 2G7, and 2H9 against Gp protein were generated by fusing mouse myeloma cell line SP2/0 with spleen lymphocytes from Gp-300 protein-immunized mice. The activity of the mAbs was then characterized by enzyme-linked immunosorbent assay, indirect immunofluorescent assays (IFA), and western blot analysis. The results demonstrated that all the mAbs showed high specificity and sensitivity in IFA and in western blot analysis, which indicated that these mAbs against Gp protein of EBOV may be used as valuable tools for analysis of the protein functions and pathogenesis of EBOV.

Risk assessment of Ebola virus disease spreading in Uganda using a two-layer temporal network

Network-based modelling of infectious diseases apply compartmental models on a contact network, which makes the epidemic process crucially dependent on the network structure. For highly contagious diseases such as Ebola virus disease (EVD), interpersonal contact plays the most vital role in human-to-human transmission. Therefore, for accurate representation of EVD spreading, the contact network needs to resemble the reality. Prior research has mainly focused on static networks (only permanent contacts) or activity-driven networks (only temporal contacts) for Ebola spreading. A comprehensive network for EVD spreading should include both these network structures, as there are always some permanent contacts together with temporal contacts. Therefore, we propose a two-layer temporal network for Uganda, which is at risk of an Ebola outbreak from the neighboring Democratic Republic of Congo (DRC) epidemic. The network has a permanent layer representing permanent contacts among individuals within the family level, and a data-driven temporal network for human movements motivated by cattle trade, fish trade, or general communications. We propose a Gillespie algorithm with the susceptible-infected-recovered (SIR) compartmental model to simulate the evolution of EVD spreading as well as to evaluate the risk throughout our network. As an example, we applied our method to a network consisting of 23 districts along different movement routes in Uganda starting from bordering districts of the DRC to Kampala. Simulation results show that some regions are at higher risk of infection, suggesting some focal points for Ebola preparedness and providing direction to inform interventions in the field. Simulation results also show that decreasing physical contact as well as increasing preventive measures result in a reduction of chances to develop an outbreak. Overall, the main contribution of this paper lies in the novel method for risk assessment, which can be more precise with an increasing volume of accurate data for creating the network model.

Infection Rates and Risk Factors for Infection Among Health Workers During Ebola and Marburg Virus Outbreaks: A Systematic Review

Background

Infection in health workers (HWs) has characterized outbreaks of Ebola virus disease (EVD) and Marburg virus disease (MVD). We conducted a systematic review to investigate infection and mortality rates and common exposure risks in HWs in EVD and MVD outbreaks.

Methods

We searched the EMBASE and PubMed databases to identify articles posted before 27 December 2017, with no language restrictions. Data on the number, frequency, and mortality of HW infection and exposure risks were extracted.

Results

Ninety-four articles related to 22 outbreaks were included. HW infections composed 2%-100% of cases in EVD and 5%-50% of cases in MVD outbreaks. Among exposed HWs, 0.6%-92% developed EVD, and 1%-10% developed MVD. HW infection rates were consistent through outbreaks. The most common exposure risk situations were inadequate personal protective equipment and exposure to patients with unrecognized EVD/MVD. Similar risks were reported in past EVD/MVD outbreaks and in the recent outbreak in West Africa.

Conclusions

Many outbreaks reported high proportions of infected HWs. Similar HW infection rates and exposure risk factors in both past and recent EVD and MVD outbreaks emphasize the need to improve the implementation of appropriate infection control measures consistently across all healthcare settings.

Impact of Ebola outbreak on reproductive health services in a rural district of Sierra Leone: a prospective observational study

OBJECTIVES

To assess the trends concerning utilisation of maternal and child health (MCH) services before, during and after the Ebola outbreak, quantifying the contribution of a reorganised referral system (RS).

DESIGN

A prospective observational study of MCH services.

SETTING

Pujehun district in Sierra Leone, 77 community health facilities and 1 hospital from 2012 to 2017.

MAIN OUTCOME MEASURES

MCH utililization was evaluated by assessing: (1) institutional deliveries, Cesarean-sections, paediatric and maternity admissions and deaths, and major direct obstetric complications (MDOCs), at hospital level; (2) antenatal care (ANC) 1 and 4, institutional delivery and family planning, at community level. Contribution of a strengthened RS was also measured.

RESULTS

At hospital level, there is a significant difference between trends Ebola versus pre-Ebola for maternal admissions (7, 95% CI 4 to 11, p<0.001), MDOCs (4, 95% CI 1 to 7, p=0.006) and institutional deliveries (4, 95% CI 2 to 6, p=0.001). There is also a negative trend in the transition from Ebola to post-Ebola for maternal admissions (-7, 95% CI -10 to -4, p<0.001), MDOCs (-4, 95% CI -7 to -1, p=0.009) and institutional deliveries (-3, 95% CI -5 to -1, p=0.001). The differences between trends pre-Ebola versus post-Ebola are only significant for paediatric admissions (3, 95% CI 0 to 5, p=0.035). At community level, the difference between trends Ebola versus pre-Ebola and Ebola versus post-Ebola are not significant for any indicators. The differences between trends pre-Ebola versus post-Ebola show a negative difference for institutional deliveries (-7, 95% CI -10 to -4, p<0.001), ANC 1 (-6, 95% CI -10 to -3, p<0.001), ANC 4 (-8, 95% CI -11 to -5, p<0.001) and family planning (-85, 95% CI -119 to -51, p<0.001).

CONCLUSIONS

A stronger health system compared with other districts in Sierra Leone and a strengthened RS enabled health facilities in Pujehun to maintain service provision and uptake during and after the Ebola epidemic.

Determinants of Transmission Risk During the Late Stage of the West African Ebola Epidemic

Understanding risk factors for Ebola transmission is key for effective prediction and design of interventions. We used data on 860 cases in 129 chains of transmission from the latter half of the 2013-2016 Ebola epidemic in Guinea. Using negative binomial regression, we determined characteristics associated with the number of secondary cases resulting from each infected individual. We found that attending an Ebola treatment unit was associated with a 38% decrease in secondary cases (incidence rate ratio (IRR) = 0.62, 95% confidence interval (CI): 0.38, 0.99) among individuals that did not survive. Unsafe burial was associated with a higher number of secondary cases (IRR = 1.82, 95% CI: 1.10, 3.02). The average number of secondary cases was higher for the first generation of a transmission chain (mean = 1.77) compared with subsequent generations (mean = 0.70). Children were least likely to transmit (IRR = 0.35, 95% CI: 0.21, 0.57) compared with adults, whereas older adults were associated with higher numbers of secondary cases. Men were less likely to transmit than women (IRR = 0.71, 95% CI: 0.55, 0.93). This detailed surveillance data set provided an invaluable insight into transmission routes and risks. Our analysis highlights the key role that age, receiving treatment, and safe burial played in the spread of EVD.

Reporting quality of the 2014 Ebola outbreak in Africa: A systematic analysis

The objective of this study was to conduct a systematic analysis of the reporting quality of the Ebola Virus Disease (EVD) outbreak in West Africa from 2014-2018 using the Modified STROBE statement. We included studies on the 2014 EVD outbreak alone, limited to those on human patients in Africa. We searched the following databases (MEDLINE, EMBASE, and Web of Science) for outbreak reports published between 2014-2018. We assessed factors potentially associated with the quality of reporting. A total of 69 of 131 (53%) articles within the full-text review fulfilled our eligibility criteria and underwent the Modified STROBE assessment for analyzing the quality of reporting. The Modified STROBE scores of the included studies ranged from 11-26 points and the mean was found to be 19.54 out of 30 with a standard deviation (SD) of ± 4.30. The top three reported Modified STROBE components were descriptive characteristics of study participants, scientific background and evidence rational, and clinical significance of observations. More than 75% of the studies met a majority of the criteria in the Modified STROBE assessment tool. Information that was commonly missing included addressing potential source of bias, sensitivity analysis, further results/analysis such as risk estimates and odds ratios, presence of a flowchart, and addressing missing data. In multivariable analysis, peer-reviewed publication was the only predictor that remained significantly associated with a higher Modified STROBE score. In conclusion, the large range of Modified STROBE scores observed indicates variability in the quality of outbreak reports for EVD. The review identified strong reporting in some areas, whereas other areas are in need of improvement, in particular providing an important description of the outbreak setting and identifying any external elements (potential biases and confounding factors) that could hinder the credibility of the findings.

Sexual transmission and the probability of an end of the Ebola virus disease epidemic

The criteria of zero Ebola cases defined by the World Health Organization did not explicitly account for the sexual transmission and led to multiple recrudescent events in West Africa from 2015 to 2016, partly indeed caused by sexual transmission from survivors. We devised a statistical model to compute the probability of the end of an Ebola virus disease epidemic, accounting for sexual transmission and under-ascertainment of cases. Analyzing the empirical data in Guinea, Liberia and Sierra Leone, the performance of the proposed model was compared with the existing criteria comprising a fixed waiting time of 42 days since the last case testing negative or burial. We showed that the waiting time can vary depending on the sexual behaviors of survivors and their adherence to refraining from unprotected sex is likely one of the key factors in determining the absence of additional cases after declaration. If the proportional weight of sexual transmission among all secondary transmission events was substantial, ascertaining the end could even require waiting 1 year from the purported last case. While our proposed method offers an objectively interpretable probability of the end of an epidemic, it highlights that the computation requires a good knowledge of sexual contact.

Control of Ebola virus disease outbreaks: Comparison of health care worker-targeted and community vaccination strategies

BACKGROUND

Health care workers (HCW) are at risk of infection during Ebola virus disease outbreaks and therefore may be targeted for vaccination before or during outbreaks. The effect of these strategies depends on the role of HCW in transmission which is understudied.

METHODS

To evaluate the effect of HCW-targeted or community vaccination strategies, we used a transmission model to explore the relative contribution of HCW and the community to transmission. We calibrated the model to data from multiple Ebola outbreaks. We quantified the impact of ahead-of-time HCW-targeted strategies, and reactive HCW and community vaccination.

RESULTS

We found that for some outbreaks (we call "type 1″) HCW amplified transmission both to other HCW and the community, and in these outbreaks prophylactic vaccination of HCW decreased outbreak size. Reactive vaccination strategies had little effect because type 1 outbreaks ended quickly. However, in outbreaks with longer time courses ("type 2 outbreaks"), reactive community vaccination decreased the number of cases, with or without prophylactic HCW-targeted vaccination. For both outbreak types, we found that ahead-of-time HCW-targeted strategies had an impact at coverage of 30%.

CONCLUSIONS

The vaccine strategies tested had a different impact depending on the transmission dynamics and previous control measures. Although we will not know the characteristics of a new outbreak, ahead-of-time HCW-targeted vaccination can decrease the total outbreak size, even at low vaccine coverage.

The Ebola virus disease outbreak in Tonkolili district, Sierra Leone: a retrospective analysis of the Viral Haemorrhagic Fever surveillance system, July 2014-June 2015

In Sierra Leone, the Ebola virus disease (EVD) outbreak occurred with substantial differences between districts with someone even not affected. To monitor the epidemic, a community event-based surveillance system was set up, collecting data into the Viral Haemorrhagic Fever (VHF) database. We analysed the VHF database of Tonkolili district to describe the epidemiology of the EVD outbreak during July 2014-June 2015 (data availability). Multivariable analysis was used to identify risk factors for EVD, fatal EVD and barriers to healthcare access, by comparing EVD-positive vs. EVD-negative cases. Key-performance indicators for EVD response were also measured. Overall, 454 EVD-positive cases were reported. At multivariable analysis, the odds of EVD was higher among those reporting contacts with an EVD-positive/suspected case (odds ratio (OR) 2.47; 95% confidence interval (CI) 2.44-2.50; P < 0.01) and those attending funeral (OR 1.02; 95% CI 1.01-1.04; P < 0.01). EVD cases from Kunike chiefdom had a lower odds of death (OR 0.22; 95% CI 0.08-0.44; P < 0.01) and were also more likely to be hospitalised (OR 2.34; 95% CI 1.23-4.57; P < 0.05). Only 25.1% of alerts were generated within 1 day from symptom onset. EVD preparedness and response plans for Tonkolili should include social-mobilisation activities targeting Ebola/knowledge-attitudes-practice during funeral attendance, to avoid contact with suspected cases and to increase awareness on EVD symptoms, in order to reduce delays between symptom onset to alert generation and consequently improve the outbreak-response promptness.

Measurability of the epidemic reproduction number in data-driven contact networks

The basic reproduction number is one of the conceptual cornerstones of mathematical epidemiology. Its classical definition as the number of secondary cases generated by a typical infected individual in a fully susceptible population finds a clear analytical expression in homogeneous and stratified mixing models. Along with the generation time (the interval between primary and secondary cases), the reproduction number allows for the characterization of the dynamics of an epidemic. A clear-cut theoretical picture, however, is hardly found in real data. Here, we infer from highly detailed sociodemographic data two multiplex contact networks representative of a subset of the Italian and Dutch populations. We then simulate an infection transmission process on these networks accounting for the natural history of influenza and calibrated on empirical epidemiological data. We explicitly measure the reproduction number and generation time, recording all individual-level transmission events. We find that the classical concept of the basic reproduction number is untenable in realistic populations, and it does not provide any conceptual understanding of the epidemic evolution. This departure from the classical theoretical picture is not due to behavioral changes and other exogenous epidemiological determinants. Rather, it can be simply explained by the (clustered) contact structure of the population. Finally, we provide evidence that methodologies aimed at estimating the instantaneous reproduction number can operationally be used to characterize the correct epidemic dynamics from incidence data.

Risk Factors for Mortality in Children Admitted for Suspected Malaria to a Pediatric Emergency Ward in a Low-Resource Setting: A Case-Control Study

OBJECTIVES

To identify the risk factors for mortality after admission for suspected malaria in a pediatric emergency ward in Sierra Leone.

DESIGN

Retrospective case-control.

SETTING

Pujehun Hospital Pediatric Ward in Pujehun, Sierra Leone.

PATIENTS

All cases were pediatric deaths after admission for suspected malaria at the Pujehun Hospital Pediatric Ward between January 1, 2015, and May 31, 2016. The case-control ratio was 1:1. The controls were infants admitted at Pujehun Hospital Pediatric Ward for malaria and discharged alive during the same period. Controls were selected as the next noncase infant admitted for malaria and discharged alive, as recorded in local medical records.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Children characteristics, vital variables on hospital access, comorbidity status at admission, antibiotic and antimalarial therapy at admission; presence of hematemesis, respiratory arrest or bradypnea, abrupt worsening, and emergency interventions during hospital stay; final diagnosis before discharge or death. In total, 320 subjects (160 cases and 160 controls) were included in the study. Multivariable analysis identified being referred from peripheral health units (odds ratio, 4.00; 95% CI, 1.98-8.43), cerebral malaria (odds ratio, 6.28; 95% CI, 2.19-21.47), malnutrition (odds ratio, 3.14; 95% CI, 1.45-7.15), dehydration (odds ratio, 3.94; 95% CI, 1.50-11.35), being unresponsive or responsive to pain (odds ratio, 2.17; 95% CI, 1.15-4.13), and hepatosplenomegaly (odds ratio, 3.20; 95% CI, 1.74-6.03) as independent risk factors for mortality.

CONCLUSIONS

Risk factors for mortality in children with suspected malaria include cerebral malaria and severe clinical conditions at admission. Being referred from peripheral health units, as proxy of logistics issue, was also associated with increased risk of mortality. These findings suggest that appropriate interventions should focus on training and resources, including the increase of dedicated personnel and available equipment.

Quantifying the spatial spread of dengue in a non-endemic Brazilian metropolis via transmission chain reconstruction

The ongoing geographical expansion of dengue is inducing an epidemiological transition in many previously transmission-free urban areas, which are now prone to annual epidemics. To analyze the spatiotemporal dynamics of dengue in these settings, we reconstruct transmission chains in Porto Alegre, Brazil, by applying a Bayesian inference model to geo-located dengue cases from 2013 to 2016. We found that transmission clusters expand by linearly increasing their diameter with time, at an average rate of about 600 m month⁻¹. The majority (70.4%, 95% CI: 58.2–79.8%) of individual transmission events occur within a distance of 500 m. Cluster diameter, duration, and epidemic size are proportionally smaller when control interventions were more timely and intense. The results suggest that a large proportion of cases are transmitted via short-distance human movement (<1 km) and a limited contribution of long distance commuting within the city. These results can assist the design of control policies, including insecticide spraying and strategies for active case finding.

There is increasing urgency to understand the spatiotemporal dynamics of dengue in non-endemic regions. Here, the authors reconstruct likely dengue transmission chains in the city of Porto Alegre based on geo-located cases only, and find that most transmission events occur over short-distances.

Quantifying the spatial spread of dengue in a non-endemic Brazilian metropolis via transmission chain reconstruction

The ongoing geographical expansion of dengue is inducing an epidemiological transition in many previously transmission-free urban areas, which are now prone to annual epidemics. To analyze the spatiotemporal dynamics of dengue in these settings, we reconstruct transmission chains in Porto Alegre, Brazil, by applying a Bayesian inference model to geo-located dengue cases from 2013 to 2016. We found that transmission clusters expand by linearly increasing their diameter with time, at an average rate of about 600 m month^-1. The majority (70.4%, 95% CI: 58.2-79.8%) of individual transmission events occur within a distance of 500 m. Cluster diameter, duration, and epidemic size are proportionally smaller when control interventions were more timely and intense. The results suggest that a large proportion of cases are transmitted via short-distance human movement (<1 km) and a limited contribution of long distance commuting within the city. These results can assist the design of control policies, including insecticide spraying and strategies for active case finding.

An Exploration of the Spatiotemporal and Demographic Patterns of Ebola Virus Disease Epidemic in West Africa Using Open Access Data Sources

The purpose of this study was to investigate the utility of exploratory analytical techniques using publically available data in informing interventions in case of infectious diseases outbreaks. More exactly spatiotemporal and multivariate methods were used to characterize the dynamics of the Ebola Virus Disease (EVD) epidemic in West Africa, and propose plausible relationships with demographic/social risk factors. The analysis showed that there was significant spatial, temporal, and spatiotemporal dependence in the evolution of the disease. For the first part of the epidemic, the cases were highly clustered in a few administrative units, in the proximity of the point of origin of the outbreak, possibly offering the opportunity to stop the spread of the disease. Later in the epidemic, high clusters were observed, but only in Liberia and Sierra Leone. Although not definitely factors of risk, in the setting in which the epidemic arose, our analysis suggests infrastructure, access to and use of health services, and connectivity possibly accelerated and magnified the spread of EVD. Also, the spatial, temporal, and spatiotemporal patterns of epidemic can be clearly shown - with evident application in the early stages of management of epidemics. In particular, we found that the spatial-temporal analytic tool SaTScan may be used effectively during the evolution of an epidemic to identify areas for targeted intervention. In the case of EVD epidemic in West Africa, better data and integration local knowledge and customs may have been more useful to recognize the proper response.

Contact tracing performance during the Ebola virus disease outbreak in Kenema district, Sierra Leone

Contact tracing in an Ebola virus disease (EVD) outbreak is the process of identifying individuals who may have been exposed to infected persons with the virus, followed by monitoring for 21 days (the maximum incubation period) from the date of the most recent exposure. The goal is to achieve early detection and isolation of any new cases in order to prevent further transmission. We performed a retrospective data analysis of 261 probable and confirmed EVD cases in the national EVD database and 2525 contacts in the Contact Line Lists in Kenema district, Sierra Leone between 27 April and 4 September 2014 to assess the performance of contact tracing during the initial stage of the outbreak. The completion rate of the 21-day monitoring period was 89% among the 2525 contacts. However, only 44% of the EVD cases had contacts registered in the Contact Line List and 6% of probable or confirmed cases had previously been identified as contacts. Touching the body fluids of the case and having direct physical contact with the body of the case conferred a 9- and 20-fold increased risk of EVD status, respectively. Our findings indicate that incompleteness of contact tracing led to considerable unmonitored transmission in the early months of the epidemic. To improve the performance of early outbreak contact tracing in resource poor settings, our results suggest the need for prioritized contact tracing after careful risk assessment and better alignment of Contact Line Listing with case ascertainment and investigation.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

The RAPIDD Ebola forecasting challenge: Model description and synthetic data generation

The Ebola forecasting challenge organized by the Research and Policy for Infectious Disease Dynamics (RAPIDD) program of the Fogarty International Center relies on synthetic disease datasets generated by numerical simulations of a highly detailed spatially-structured agent-based model. We discuss here the architecture and technical steps of the challenge, leading to datasets that mimic as much as possible the data collection, reporting, and communication process experienced in the 2014-2015 West African Ebola outbreak. We provide a detailed discussion of the model's definition, the epidemiological scenarios' construction, synthetic patient database generation and the data communication platform used during the challenge. Finally we offer a number of considerations and takeaways concerning the extension and scalability of synthetic challenges to other infectious diseases.

The Transmission Chain Analysis of 2014-2015 Ebola Virus Disease Outbreak in Koinadugu District, Sierra Leone: An Observational Study

Introduction

Sierra Leone experienced an unprecedented Ebola virus disease (EVD) outbreak in all its districts. Koinadugu District was the last to report an EVD case. Several outbreak response strategies were implemented. As part of lessons learnt, we conducted an observational study to describe the transmission chain in the district and the impact of the control measures implemented to contain the outbreak.

Methods

We reconstructed the transmission chain, positioning both confirmed and probable cases, described the distribution of the EVD confirmed cases in the context of the routes of transmission (Community, Funeral or Health facility setting) and assessed the impact of control measures using the surveillance data collected during the outbreak.

Results

All 142 confirmed and probable EVD cases registered were fully resolved in the transmission chain. 72.5% of all the EVD cases in the district were exposed in the community, 26.1% exposed during funerals, and 1.4% exposed in the health facility setting. Health-care workers contributed little to the EVD outbreak. 71.1% of EVD transmission occurred among family members. Female EVD cases generated more secondary cases than their male counterparts (P = 0.03). With removal of EVD cases from the community and admission to the community care center (CCC), the EVD transmission in the community decreased to substantially lower rates. In addition, transmission due to exposure in health facilities was further reduced with the implementation of full infection and prevention controls.

Conclusion

This study details the transmission chain of EVD in a rural district setting and the public health interventions implemented to successfully limit the outbreak to just one of 11 chiefdoms. Heightened community-based surveillance for early case detection, swift isolation of suspect cases, efficient contact tracing and monitoring, and good infection prevention and control measures in health facilities were highly effective in limiting transmission and, eventually, breaking the transmission chain. CCCs were also instrumental in achieving early isolation and basic care for suspect cases, while ensuring that their family members who were close contacts remained in the community for easy contact tracing and monitoring. These were very useful lessons learnt that would inform the management of future outbreaks.

Estimating the number of secondary Ebola cases resulting from an unsafe burial and risk factors for transmission during the West Africa Ebola epidemic

Background

Safely burying Ebola infected individuals is acknowledged to be important for controlling Ebola epidemics and was a major component of the 2013–2016 West Africa Ebola response. Yet, in order to understand the impact of safe burial programs it is necessary to elucidate the role of unsafe burials in sustaining chains of Ebola transmission and how the risk posed by activities surrounding unsafe burials, including care provided at home prior to death, vary with human behavior and geography.

Methodology/Principal findings

Interviews with next of kin and community members were carried out for unsafe burials in Sierra Leone, Liberia and Guinea, in six districts where the Red Cross was responsible for safe and dignified burials (SDB). Districts were randomly selected from a district-specific sampling frame comprised of villages and neighborhoods that had experienced cases of Ebola. An average of 2.58 secondary cases were potentially generated per unsafe burial and varied by district (range: 0–20). Contact before and after death was reported for 142 (46%) contacts. Caregivers of a primary case were 2.63 to 5.92 times more likely to become EVD infected compared to those with post-mortem contact only. Using these estimates, the Red Cross SDB program potentially averted between 1,411 and 10,452 secondary EVD cases, reducing the epidemic by 4.9% to 36.5%.

Conclusions/Significance

SDB is a fundamental control measure that limits community transmission of Ebola; however, for those individuals having contact before and after death, it was impossible to ascertain the exposure that caused their infection. The number of infections prevented through SDB is significant, yet greater impact would be achieved by early hospitalization of the primary case during acute illness.

The care of an individual infected with Ebola virus disease (EVD), their death, funeral, and burial in the community rather than in an Ebola Treatment Center (ETC) poses a serious risk for continued disease transmission. Consequently, SDB is an essential component of EVD outbreak response; however, its impact on transmission is not well understood. During the 2013–2016 EVD epidemic the Red Cross carried out over 50% of the official burials in Guinea, Liberia and Sierra Leone. We performed epidemiological investigations in EVD affected communities to better understand disease transmission linked to unsafe burials of (suspect) EVD infected individuals, and risk factors for transmission linked to caring and burial practices. An average of 2.58 secondary cases were potentially generated per unsafe burial investigated and varied by district (range: 0–20). Additionally, the Red Cross SDB program potentially averted between 1,411 and 10,452 secondary EVD cases, reducing the epidemic by 4.9% to 36.5%. Our results quantify for the first time the potential impact this essential EVD response component had on the 2013–2016 epidemic and highlight the importance of SDB as a fundamental control measure, while also underlining the well-known importance of isolating EVD infected individuals as soon as they show symptoms in order to limit transmission.

Epidemiology of Ebola Virus Disease in the Western Area Region of Sierra Leone, 2014-2015

Introduction

Western Area (WA) of Sierra Leone including the capital, Freetown, experienced an unprecedented outbreak of Ebola from 2014 to 2015. At the onset of the epidemic, there was little information about the epidemiology, transmission dynamics, and risk factors in urban settings as previous outbreaks were limited to rural/semi-rural settings. This study, therefore, aimed to describe the epidemiology of the outbreak and the factors which had most impact on the transmission of the epidemic and whether there were different drivers from those previously described in rural settings.

Methods

We conducted a descriptive epidemiology study in WA, Sierra Leone using secondary data from the National Ebola outbreak database. We also reviewed the Ebola situation reports, response strategy documents, and other useful documents.

Results

A total of 4,955 Ebola cases were identified between June 2014 and November 2015, although there were reports of cases occurring in WA toward end of May. All wards were affected, and Waterloo Area I (Ward 330), the capital city of Western Area Rural District, recorded the highest numbers of cases (580) and deaths (236). Majority of cases (63.4%) and deaths (66.8%) were in WA Urban District (WAU); 44 cases were imported from other provinces. Only 20% of cases had a history of contact with an Ebola case, and more than 30% were death alerts. Equal numbers of males and females were infected, and very few cases (3.2%) were health workers. Overall, transmission was through contact with infected individuals, and intense transmission occurred at the community level. In WAU, transmission was mostly between neighbors and among inhabitants of shared accommodations. The drivers of transmission included high population movement to and from WA, overcrowding, fear and lack of trust in the response, and negative community behaviors. Transmission was mostly through contact and with limited transmission through sex and breast milk.

Conclusion

The unprecedented outbreak in WA was attributed to delayed detection, inadequate preparedness and response, intense population movements, overcrowding, and unresponsive communities. Anticipation, strengthening preparedness for early detection, and swift and effective response remains critical in mitigating a potential urban explosion of similar future outbreaks.

Perspectives on model forecasts of the 2014-2015 Ebola epidemic in West Africa: lessons and the way forward

The unprecedented impact and modeling efforts associated with the 2014-2015 Ebola epidemic in West Africa provides a unique opportunity to document the performances and caveats of forecasting approaches used in near-real time for generating evidence and to guide policy. A number of international academic groups have developed and parameterized mathematical models of disease spread to forecast the trajectory of the outbreak. These modeling efforts often relied on limited epidemiological data to derive key transmission and severity parameters, which are needed to calibrate mechanistic models. Here, we provide a perspective on some of the challenges and lessons drawn from these efforts, focusing on (1) data availability and accuracy of early forecasts; (2) the ability of different models to capture the profile of early growth dynamics in local outbreaks and the importance of reactive behavior changes and case clustering; (3) challenges in forecasting the long-term epidemic impact very early in the outbreak; and (4) ways to move forward. We conclude that rapid availability of aggregated population-level data and detailed information on a subset of transmission chains is crucial to characterize transmission patterns, while ensemble-forecasting approaches could limit the uncertainty of any individual model. We believe that coordinated forecasting efforts, combined with rapid dissemination of disease predictions and underlying epidemiological data in shared online platforms, will be critical in optimizing the response to current and future infectious disease emergencies.

A systematic review of early modelling studies of Ebola virus disease in West Africa

Phenomenological and mechanistic models are widely used to assist resource planning for pandemics and emerging infections. We conducted a systematic review, to compare methods and outputs of published phenomenological and mechanistic modelling studies pertaining to the 2013-2016 Ebola virus disease (EVD) epidemics in four West African countries - Sierra Leone, Liberia, Guinea and Nigeria. We searched Pubmed, Embase and Scopus databases for relevant English language publications up to December 2015. Of the 874 articles identified, 41 met our inclusion criteria. We evaluated these selected studies based on: the sources of the case data used, and modelling approaches, compartments used, population mixing assumptions, model fitting and calibration approaches, sensitivity analysis used and data bias considerations. We synthesised results of the estimated epidemiological parameters: basic reproductive number (R 0), serial interval, latent period, infectious period and case fatality rate, and examined their relationships. The median of the estimated mean R 0 values were between 1·30 and 1·84 in Sierra Leone, Liberia and Guinea. Much higher R 0 value of 9·01 was described for Nigeria. We investigated several issues with uncertainty around EVD modes of transmission, and unknown observation biases from early reported case data. We found that epidemic models offered R 0 mean estimates which are country-specific, but these estimates are not associating with the use of several key disease parameters within the plausible ranges. We find simple models generally yielded similar estimates of R 0 compared with more complex models. Models that accounted for data uncertainty issues have offered a higher case forecast compared with actual case observation. Simple model which offers transparency to public health policy makers could play a critical role for advising rapid policy decisions under an epidemic emergency.

Containing Ebola at the Source with Ring Vaccination

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.

When the 2014–15 Ebola outbreak in West Africa began, no licensed vaccines for the disease were available. The rVSV-ZEBOV vaccine was developed during the course of the epidemic and underwent a clinical trial demonstrating 100% efficacy when vaccinating contacts and contacts of contacts of confirmed Ebola cases (an approach called ring vaccination). However, the trial did not provide any understanding on whether this vaccination strategy can be effective in containing future Ebola virus disease outbreaks. Through a modelling study on a region of Sierra Leone, we provide numerical estimates for the effectiveness of ring vaccination: we show that outbreaks with moderate transmission potential, with no more than 1.6 secondary cases generated by an index case on average, can be successfully contained; more extensive vaccination(e.g., including spatial rings around index cases) and reinforcement of the healthcare system would increase the likelihood of containment even if the virus were more transmissible than in the past. Our results provide implications for control plans of possible future Ebola outbreaks.

Characterizing the reproduction number of epidemics with early subexponential growth dynamics

Early estimates of the transmission potential of emerging and re-emerging infections are increasingly used to inform public health authorities on the level of risk posed by outbreaks. Existing methods to estimate the reproduction number generally assume exponential growth in case incidence in the first few disease generations, before susceptible depletion sets in. In reality, outbreaks can display subexponential (i.e. polynomial) growth in the first few disease generations, owing to clustering in contact patterns, spatial effects, inhomogeneous mixing, reactive behaviour changes or other mechanisms. Here, we introduce the generalized growth model to characterize the early growth profile of outbreaks and estimate the effective reproduction number, with no need for explicit assumptions about the shape of epidemic growth. We demonstrate this phenomenological approach using analytical results and simulations from mechanistic models, and provide validation against a range of empirical disease datasets. Our results suggest that subexponential growth in the early phase of an epidemic is the rule rather the exception. Mechanistic simulations show that slight modifications to the classical susceptible-infectious-removed model result in subexponential growth, and in turn a rapid decline in the reproduction number within three to five disease generations. For empirical outbreaks, the generalized-growth model consistently outperforms the exponential model for a variety of directly and indirectly transmitted diseases datasets (pandemic influenza, measles, smallpox, bubonic plague, cholera, foot-and-mouth disease, HIV/AIDS and Ebola) with model estimates supporting subexponential growth dynamics. The rapid decline in effective reproduction number predicted by analytical results and observed in real and synthetic datasets within three to five disease generations contrasts with the expectation of invariant reproduction number in epidemics obeying exponential growth. The generalized-growth concept also provides us a compelling argument for the unexpected extinction of certain emerging disease outbreaks during the early ascending phase. Overall, our approach promotes a more reliable and data-driven characterization of the early epidemic phase, which is important for accurate estimation of the reproduction number and prediction of disease impact.

Spatiotemporal dynamics of the Ebola epidemic in Guinea and implications for vaccination and disease elimination: a computational modeling analysis

BACKGROUND

Among the three countries most affected by the Ebola virus disease outbreak in 2014-2015, Guinea presents an unusual spatiotemporal epidemic pattern, with several waves and a long tail in the decay of the epidemic incidence.

METHODS

Here, we develop a stochastic agent-based model at the level of a single household that integrates detailed data on Guinean demography, hospitals, Ebola treatment units, contact tracing, and safe burial interventions. The microsimulation-based model is used to assess the effect of each control strategy and the probability of elimination of the epidemic according to different intervention scenarios, including ring vaccination with the recombinant vesicular stomatitis virus-vectored vaccine.

RESULTS

The numerical results indicate that the dynamics of the Ebola epidemic in Guinea can be quantitatively explained by the timeline of the implemented interventions. In particular, the early availability of Ebola treatment units and the associated isolation of cases and safe burials helped to limit the number of Ebola cases experienced by Guinea. We provide quantitative evidence of a strong negative correlation between the time series of cases and the number of traced contacts. This result is confirmed by the computational model that suggests that contact tracing effort is a key determinant in the control and elimination of the disease. In data-driven microsimulations, we find that tracing at least 5-10 contacts per case is crucial in preventing epidemic resurgence during the epidemic elimination phase. The computational model is used to provide an analysis of the ring vaccination trial highlighting its potential effect on disease elimination.

CONCLUSIONS

We identify contact tracing as one of the key determinants of the epidemic's behavior in Guinea, and we show that the early availability of Ebola treatment unit beds helped to limit the number of Ebola cases in Guinea.

Contact Tracing during an Outbreak of Ebola Virus Disease in the Western Area Districts of Sierra Leone: Lessons for Future Ebola Outbreak Response

INTRODUCTION

Contact tracing is a critical strategy required for timely prevention and control of Ebola virus disease (EVD) outbreaks. Available evidence suggests that poor contact tracing was a driver of the EVD outbreak in West Africa, including Sierra Leone. In this article, we answered the question as to whether EVD contact tracing, as practiced in Western Area (WA) districts of Sierra Leone from 2014 to 2015, was effective. The goal is to describe contact tracing and identify obstacles to its effective implementation.

METHODS

Mixed methods comprising secondary data analysis of the EVD case and contact tracing data sets collected from WA during the period from 2014 to 2015, key informant interviews of contact tracers and their supervisors, and a review of available reports on contact tracing were implemented to obtain data for this study.

RESULTS

During the study period, 3,838 confirmed cases and 32,706 contacts were listed in the viral hemorrhagic fever and contact databases for the district (mean 8.5 contacts per case). Only 22.1% (852) of the confirmed cases in the study area were listed as contacts at the onset of their illness, which indicates incomplete identification and tracing of contacts. Challenges associated with effective contact tracing included lack of community trust, concealing of exposure information, political interference with recruitment of tracers, inadequate training of contact tracers, and incomplete EVD case and contact database. While the tracers noted the usefulness of community quarantine in facilitating their work, they also reported delayed or irregular supply of basic needs, such as food and water, which created resistance from the communities.

CONCLUSION

Multiple gaps in contact tracing attributed to a variety of factors associated with implementers, and communities were identified as obstacles that impeded timely control of the EVD outbreak in the WA of Sierra Leone. In future outbreaks, early community engagement and participation in contact tracing, establishment of appropriate mechanisms for selection, adequate training and supervision of qualified contact tracers, establishment of a well-managed and complete contact tracing database, and provision of basic needs to quarantined contacts are recommended as measures to enhance effective contact tracing.

Maintaining Maternal and Child Health Services During the Ebola Outbreak: Experience from Pujehun, Sierra Leone

BACKGROUND

During the Ebola outbreak the overall confidence of the population in the national health system declined in Sierra Leone, with a reduction in the use of health services. The objective of this study is to provide information on understanding of how Ebola impacted maternal and child health services in Sierra Leone. Data come from an operational setting which is representative of the communities affected by the outbreak.

METHODS

By integrating hospital registers and contact tracing form data with healthcare workers and local population interviews, the transmission chain was reconstructed. Data on the utilization of maternal and neonatal health services were collected from the local district's Health Management Information System. The main measures put in place to control the Ebola epidemic were: the organization of a rapid response to the crisis by the local health authorities; triage, contact tracing and quarantine; isolation, clinical management and safe burials; training and community sensitization.

RESULTS

A total of 49 case patients were registered between July and November 2014 in the Pujehun district. Hospitalization rate was 89%. Overall, 74.3% of transmission events occurred between members of the same family, 17.9% in the community and 7.7% in hospital. The mean number of contacts investigated per case raised from 11.5 in July to 25 in September 2014. The 2014 admission trend in the pediatric ward shows a decrease after beginning of June: the reduction was almost significant in the period July-December (p 0.05). The admission in the maternity ward showed no statistical differences in comparison with the previous year (p 0.07). Also the number of deliveries appeared to be similar to the previous year, without significant variations (p 0.41).

CONCLUSION

The Ebola outbreak reduced the number of patients at hospital level in Pujehun district. However, the activities undertaken to manage Ebola, reduced the spread of infection and the impact of the disease in mothers and children. A number of reasons which may explain these results are presented and discussed.

Deaths, late deaths, and role of infecting dose in Ebola virus disease in Sierra Leone: retrospective cohort study

OBJECTIVES

 To assess the frequency of fatal recrudescence from Ebola virus disease after discharge from treatment centres, and explore the influence of infecting dose on case fatality rates.

DESIGN

 Retrospective cohort study.

SETTING

 Western Area, Sierra Leone.

PARTICIPANTS

 151 survivors treated for Ebola virus disease at the Kerry Town treatment centre and discharged. Survivors were followed up for a vital status check at four to nine months after discharge, and again at six to 13 months after discharge. Verbal autopsies were conducted for four survivors who had died since discharge (that is, late deaths). Survivors still living in Western Area were interviewed together with their household members. Exposure level to Ebola virus disease was ascertained as a proxy of infecting dose, including for those who died.

MAIN OUTCOME MEASURES

 Risks and causes of late death; case fatality rates; odds ratios of death from Ebola virus disease by age, sex, exposure level, date, occupation, and household risk factors.

RESULTS

 Follow-up information was obtained on all 151 survivors of Ebola virus disease, a mean of 10 months after discharge. Four deaths occurred after discharge, all within six weeks: two probably due to late complications, one to prior tuberculosis, and only one after apparent full recovery, giving a maximum estimate of recrudescence leading to death of 0.7%. In these households, 395 people were reported to have had Ebola virus disease, of whom 227 died. A further 53 people fulfilled the case definition for probable disease, of whom 11 died. Therefore, the case fatality rate was 57.5% (227/395) for reported Ebola virus disease, or 53.1% (238/448) including probable disease. Case fatality rates were higher in children aged under 2 years and adults older than 30 years, in larger households, and in infections occurring earlier in the epidemic in Sierra Leone. There was no consistent trend of case fatality rate with exposure level, although increasing exposure increased the risk of Ebola virus disease.

CONCLUSIONS

 In this study of survivors in Western Area, Sierra Leone, late recrudescence of severe Ebola virus disease appears to be rare. There was no evidence for an effect of infecting dose (as measured by exposure level) on the severity of disease.