Rapid Decision Algorithm for Patient Triage during Ebola Outbreaks.

The low specificity of Ebola virus disease clinical signs increases the risk for nosocomial transmission to patients and healthcare workers during outbreaks. Reducing this risk requires identifying patients with a high likelihood of Ebola virus infection. Analyses of retrospective data from patients suspected of having Ebola virus infection identified 13 strong predictors and time from disease onset as constituents of a prediction score for Ebola virus disease. We also noted 4 highly predictive variables that could distinguish patients at high risk for infection, independent of their scores. External validation of this algorithm on retrospective data revealed the probability of infection continuously increased with the score.

Ebola Virus Disease Outbreak - Democratic Republic of the Congo, August 2018-November 2019.

On August 1, 2018, the Democratic Republic of the Congo Ministry of Health (DRC MoH) declared the tenth outbreak of Ebola virus disease (Ebola) in DRC, in the North Kivu province in eastern DRC on the border with Uganda, 8 days after another Ebola outbreak was declared over in northwest Équateur province. During mid- to late-July 2018, a cluster of 26 cases of acute hemorrhagic fever, including 20 deaths, was reported in North Kivu province.* Blood specimens from six patients hospitalized in the Mabalako health zone and sent to the Institut National de Recherche Biomédicale (National Biomedical Research Institute) in Kinshasa tested positive for Ebola virus. Genetic sequencing confirmed that the outbreaks in North Kivu and Équateur provinces were unrelated. From North Kivu province, the outbreak spread north to Ituri province, and south to South Kivu province (1). On July 17, 2019, the World Health Organization designated the North Kivu and Ituri outbreak a public health emergency of international concern, based on the geographic spread of the disease to Goma, the capital of North Kivu province, and to Uganda and the challenges to implementing prevention and control measures specific to this region (2). This report describes the outbreak in the North Kivu and Ituri provinces. As of November 17, 2019, a total of 3,296 Ebola cases and 2,196 (67%) deaths were reported, making this the second largest documented outbreak after the 2014-2016 epidemic in West Africa, which resulted in 28,600 cases and 11,325 deaths.† Since August 2018, DRC MoH has been collaborating with partners, including the World Health Organization, the United Nations Children's Fund, the United Nations Office for the Coordination of Humanitarian Affairs, the International Organization of Migration, The Alliance for International Medical Action (ALIMA), Médecins Sans Frontières, DRC Red Cross National Society, and CDC, to control the outbreak. Enhanced communication and effective community engagement, timing of interventions during periods of relative stability, and intensive training of local residents to manage response activities with periodic supervision by national and international personnel are needed to end the outbreak.

Effectiveness of rVSV-ZEBOV vaccination during the 2018-20 Ebola virus disease epidemic in the Democratic Republic of the Congo: a retrospective test-negative study.

BACKGROUND: The recombinant vesicular stomatitis virus-Zaire Ebola virus (rVSV-ZEBOV) vaccine is the only WHO prequalified vaccine recommended for use to respond to outbreaks of Ebola virus (species Zaire ebolavirus) by WHO's Strategic Advisory Group of Experts on Immunization. Despite the vaccine's widespread use during several outbreaks, no real-world effectiveness estimates are currently available in the literature. METHODS: We conducted a retrospective test-negative analysis to estimate effectiveness of rVSV-ZEBOV vaccination against Ebola virus disease during the 2018-20 epidemic in the Democratic Republic of the Congo, using data on suspected Ebola virus disease cases collected from Ebola treatment centres. Those eligible for inclusion had an available Ebola virus RT-PCR result, available key data, were eligible for vaccination during the outbreak, and had symptom onset aligning with the period in which a ring-vaccination protocol was in use. After imputing missing data, each individual confirmed by RT-PCR to be Ebola virus disease-positive (defined as a case) was matched to one individual negative for Ebola virus disease (control) by sex, age, health zone, and month of symptom onset. Effectiveness was estimated from the odds ratio of being vaccinated (≥10 days before symptom onset) versus being unvaccinated among cases and controls, after adjusting for the matching factors. The imputation, matching and effectiveness estimation, was repeated 500 times. FINDINGS: 1273 (4·8%) of 26 438 eligible individuals were positive for Ebola virus disease (cases) and 25 165 (95·2%) were negative (controls). 40 (3·1%) cases and 1271 (5·1%) controls were reported as being vaccinated at least 10 days before symptom onset. After selecting individuals who reported exposure to an individual with Ebola virus disease within the 21 days before symptom onset and matching, the analysis datasets comprised a median of 309 cases and 309 controls. 10 days or more after vaccination, the effectiveness of rVSV-ZEBOV against Ebola virus disease was estimated to be 84% (95% credible interval 70-92). INTERPRETATION: This analysis is the first to provide estimates of the real-world effectiveness of the rVSV-ZEBOV vaccine against Ebola virus disease, amid the widespread use of the vaccine during a large Ebola virus disease outbreak. Our findings confirm that rVSV-ZEBOV is highly protective against Ebola virus disease and support its use during outbreaks, even in challenging contexts such as in the eastern Democratic Republic of the Congo. FUNDING: Médecins Sans Frontières. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Effect of anti-Ebola virus monoclonal antibodies on endogenous antibody production in survivors of Ebola virus disease in the Democratic Republic of the Congo: an observational cohort study.

BACKGROUND: The use of specific anti-Ebola virus therapy, especially monoclonal antibodies, has improved survival in patients with Ebola virus disease. We aimed to assess the effect of monoclonal antibodies on anti-Ebola virus antibody responses in survivors of the 2018-20 Ebola outbreak in the Democratic Republic of the Congo. METHODS: In this observational prospective cohort study, participants were enrolled at three Ebola survivor clinics in Beni, Mangina, and Butembo (Democratic Republic of the Congo). Eligible children and adults notified as survivors of Ebola virus disease (ie, who had confirmed Ebola virus disease [RT-PCR positive in blood sample] and were subsequently declared recovered from the virus [RT-PCR negative in blood sample] with a certificate of recovery from Ebola virus disease issued by an Ebola treatment centre) during the 2018-20 Ebola virus disease outbreak were invited to participate in the study. Participants were recruited on discharge from Ebola treatment centres and followed up for 12-18 months depending on recruitment date. Routine follow-up assessments were done at 1, 3, 6, and 12-18 months after inclusion. We collected sociodemographic (age, sex, visit site), clinical (anti-Ebola virus drugs), and laboratory data (RT-PCR and Ct values). The primary outcome was the antibody concentrations against Ebola virus glycoprotein, nucleoprotein, and 40-kDa viral protein antigens over time assessed in all participants. Antibody concentrations were measured by the multiplex immunoassay, and the association between anti-Ebola virus antibody levels and the relevant exposures, such as anti-Ebola virus disease drugs (ansuvimab, REGN-EB3, ZMapp, or remdesivir), was assessed using both linear and logistic mixed regression models. This study is registered at ClinicalTrials.gov, NCT04409405. FINDINGS: Between April 16, 2020, and Oct 18, 2021, 1168 survivors were invited to participate in the Les Vainqueurs d'Ebola cohort study. 787 survivors were included in the study, of whom 358 had data available for antibody responses. 85 (24%) of 358 were seronegative for at least two Ebola virus antigens on discharge from the Ebola treatment centre. The antibody response over time fluctuated but a continuous decrease in an overall linear evolution was observed. Quantitative modelling showed a decrease in nucleoprotein, glycoprotein, and VP-40 antibody concentrations over time (p<0·0001) with the fastest decrease observed for glycoprotein. The probability of being seropositive for at least two antigens after 36 months was 53·6% (95% CI 51·6-55·6) for participants who received ansuvimab, 73·5% (71·5-75·5) for participants who received REGN-EB3, 76·8% (74·8-78·8) for participants who received remdesivir, and 78·5% (76·5-80·5) for participants who received ZMapp. INTERPRETATION: Almost a quarter of survivors were seronegative on discharge from the Ebola treatment centre and antibody concentrations decreased rapidly over time. These results indicate that monoclonal antibodies might negatively affect the production of anti-Ebola virus antibodies in survivors of Ebola virus disease which could increase the risk of reinfection or reactivation. FUNDING: The French National Agency for AIDS Research-Emergent Infectious Diseases-The French National Institute of Health and Medical Research, the French National Research Institute for Development, and the European and Developing Countries Clinical Trials Partnership. TRANSLATION: For the French translation of the abstract see Supplementary Materials section.

Differential symptomology of possible and confirmed Ebola virus disease infection in the Democratic Republic of the Congo: a retrospective cohort study.

BACKGROUND: In its earliest phases, Ebola virus disease's rapid-onset, high fever, and gastrointestinal symptoms are largely indistinguishable from other infectious illnesses. We aimed to characterise the clinical indicators associated with Ebola virus disease to improve outbreak response. METHODS: In this retrospective analysis, we assessed routinely collected data from individuals with possible Ebola virus disease attending 30 Ebola health facilities in two provinces of the Democratic Republic of the Congo between Aug 1, 2018, and Aug 28, 2019. We used logistic regression analysis to model the probability of Ebola infection across 34 clinical variables and four types of possible Ebola virus disease exposures: contact with an individual known to have Ebola virus disease, attendance at any funeral, health facility consultation, or consultation with an informal health practitioner. FINDINGS: Data for 24 666 individuals were included. If a patient presented to care in the early symptomatic phase (ie, days 0-2), Ebola virus disease positivity was most associated with previous exposure to an individual with Ebola virus disease (odds ratio [OR] 11·9, 95% CI 9·1-15·8), funeral attendance (2·1, 1·6-2·7), or health facility consultations (2·1, 1·6-2·8), rather than clinical parameters. If presentation occurred on day 3 or later (after symptom onset), bleeding at an injection site (OR 33·9, 95% CI 12·7-101·3), bleeding gums (7·5, 3·7-15·4), conjunctivitis (2·4, 1·7-3·4), asthenia (1·9, 1·5-2·3), sore throat (1·8, 1·3-2·4), dysphagia (1·8, 1·4-2·3), and diarrhoea (1·6, 1·3-1·9) were additional strong predictors of Ebola virus disease. Some Ebola virus disease-specific signs were less prevalent among vaccinated individuals who were positive for Ebola virus disease when compared with the unvaccinated, such as dysphagia (-47%, p=0·0024), haematemesis (-90%, p=0·0131), and bleeding gums (-100%, p=0·0035). INTERPRETATION: Establishing the exact time an individual first had symptoms is essential to assessing their infection risk. An individual's exposure history remains of paramount importance, especially in the early phase. Ebola virus disease vaccination reduces symptom severity and should also be considered when assessing the likelihood of infection. These findings about symptomatology should be translated into practice during triage and should inform testing and quarantine procedures. FUNDING: Médecins Sans Frontières and its research affiliate Epicentre.

Development of Ebola virus disease prediction scores: Screening tools for Ebola suspects at the triage-point during an outbreak.

BACKGROUND: The control of Ebola virus disease (EVD) outbreaks relies on rapid diagnosis and prompt action, a daunting task in limited-resource contexts. This study develops prediction scores that can help healthcare workers improve their decision-making at the triage-point of EVD suspect-cases during EVD outbreaks. METHODS: We computed accuracy measurements of EVD predictors to assess their diagnosing ability compared with the reference standard GeneXpert® results, during the eastern DRC EVD outbreak. We developed predictive scores using the Spiegelhalter-Knill-Jones approach and constructed a clinical prediction score (CPS) and an extended clinical prediction score (ECPS). We plotted the receiver operating characteristic curves (ROCs), estimated the area under the ROC (AUROC) to assess the performance of scores, and computed net benefits (NB) to assess the clinical utility (decision-making ability) of the scores at a given cut-off. We performed decision curve analysis (DCA) to compare, at a range of threshold probabilities, prediction scores' decision-making ability and to quantify the number of unnecessary isolation. RESULTS: The analysis was done on data from 10432 subjects, including 651 EVD cases. The EVD prevalence was 6.2% in the whole dataset, 14.8% in the subgroup of suspects who fitted the WHO Ebola case definition, and 3.2% for the set of suspects who did not fit this case definition. The WHO clinical definition yielded 61.6% sensitivity and 76.4% specificity. Fatigue, difficulty in swallowing, red eyes, gingival bleeding, hematemesis, confusion, hemoptysis, and a history of contact with an EVD case were predictors of EVD. The AUROC for ECPS was 0.88 (95%CI: 0.86-0.89), significantly greater than this for CPS, 0.71 (95%CI: 0.69-0.73) (p < 0.0001). At -1 point of score, the CPS yielded a sensitivity of 85.4% and specificity of 42.3%, and the ECPS yielded sensitivity of 78.8% and specificity of 81.4%. The diagnostic performance of the scores varied in the three disease contexts (the whole, fitting or not fitting the WHO case definition data sets). At 10% of threshold probability, e.g. in disease-adverse context, ECPS gave an NB of 0.033 and a net reduction of unnecessary isolation of 67.1%. Using ECPS as a joint approach to isolate EVD suspects reduces the number of unnecessary isolations by 65.7%. CONCLUSION: The scores developed in our study showed a good performance as EVD case predictors since their use improved the net benefit, i.e., their clinical utility. These rapid and low-cost tools can help in decision-making to isolate EVD-suspicious cases at the triage point during an outbreak. However, these tools still require external validation and cost-effectiveness evaluation before being used on a large scale.

Development of the PREDS score to predict in-hospital mortality of patients with Ebola virus disease under advanced supportive care: Results from the EVISTA cohort in the Democratic Republic of the Congo.

Background: As mortality remains high for patients with Ebola virus disease (EVD) despite new treatment options, the ability to level up the provided supportive care and to predict the risk of death is of major importance. This analysis of the EVISTA cohort aims to describe advanced supportive care provided to EVD patients in the Democratic Republic of the Congo (DRC) and to develop a simple risk score for predicting in-hospital death, called PREDS. Methods: In this prospective cohort (NCT04815175), patients were recruited during the 10th EVD outbreak in the DRC across three Ebola Treatment Centers (ETCs). Demographic, clinical, biological, virological and treatment data were collected. We evaluated factors known to affect the risk of in-hospital death and applied univariate and multivariate Cox proportional-hazards analyses to derive the risk score in a training dataset. We validated the score in an internal-validation dataset, applying C-statistics as a measure of discrimination. Findings: Between August 1st 2018 and December 31th 2019, 711 patients were enrolled in the study. Regarding supportive care, patients received vasopressive drug (n = 111), blood transfusion (n = 101), oxygen therapy (n = 250) and cardio-pulmonary ultrasound (n = 15). Overall, 323 (45%) patients died before day 28. Six independent prognostic factors were identified (ALT, creatinine, modified NEWS2 score, viral load, age and symptom duration). The final score range from 0 to 13 points, with a good concordance (C = 86.24%) and calibration with the Hosmer-Lemeshow test (p = 0.12). Interpretation: The implementation of advanced supportive care is possible for EVD patients in emergency settings. PREDS is a simple, accurate tool that could help in orienting early advanced care for at-risk patients after external validation. Funding: This study was funded by ALIMA.