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.

Assessment of the integrated disease surveillance and response system implementation in health zones at risk for viral hemorrhagic fever outbreaks in North Kivu, Democratic Republic of the Congo, following a major Ebola outbreak, 2021.

BACKGROUND: The Democratic Republic of the Congo (DRC) experienced its largest Ebola Virus Disease Outbreak in 2018-2020. As a result of the outbreak, significant funding and international support were provided to Eastern DRC to improve disease surveillance. The Integrated Disease Surveillance and Response (IDSR) strategy has been used in the DRC as a framework to strengthen public health surveillance, and full implementation could be critical as the DRC continues to face threats of various epidemic-prone diseases. In 2021, the DRC initiated an IDSR assessment in North Kivu province to assess the capabilities of the public health system to detect and respond to new public health threats. METHODS: The study utilized a mixed-methods design consisting of quantitative and qualitative methods. Quantitative assessment of the performance in IDSR core functions was conducted at multiple levels of the tiered health system through a standardized questionnaire and analysis of health data. Qualitative data were also collected through observations, focus groups and open-ended questions. Data were collected at the North Kivu provincial public health office, five health zones, 66 healthcare facilities, and from community health workers in 15 health areas. RESULTS: Thirty-six percent of health facilities had no case definition documents and 53% had no blank case reporting forms, limiting identification and reporting. Data completeness and timeliness among health facilities were 53% and 75% overall but varied widely by health zone. While these indicators seemingly improved at the health zone level at 100% and 97% respectively, the health facility data feeding into the reporting structure were inconsistent. The use of electronic Integrated Disease Surveillance and Response is not widely implemented. Rapid response teams were generally available, but functionality was low with lack of guidance documents and long response times. CONCLUSION: Support is needed at the lower levels of the public health system and to address specific zones with low performance. Limitations in materials, resources for communication and transportation, and workforce training continue to be challenges. This assessment highlights the need to move from outbreak-focused support and funding to building systems that can improve the long-term functionality of the routine disease surveillance system.

Novel Use of Capture-Recapture Methods to Estimate Completeness of Contact Tracing during an Ebola Outbreak, Democratic Republic of the Congo, 2018-2020.

Despite its critical role in containing outbreaks, the efficacy of contact tracing, measured as the sensitivity of case detection, remains an elusive metric. We estimated the sensitivity of contact tracing by applying unilist capture-recapture methods on data from the 2018-2020 outbreak of Ebola virus disease in the Democratic Republic of the Congo. To compute sensitivity, we applied different distributional assumptions to the zero-truncated count data to estimate the number of unobserved case-patients with any contacts and infected contacts. Geometric distributions were the best-fitting models. Our results indicate that contact tracing efforts identified almost all (n = 792, 99%) of case-patients with any contacts but only half (n = 207, 48%) of case-patients with infected contacts, suggesting that contact tracing efforts performed well at identifying contacts during the listing stage but performed poorly during the contact follow-up stage. We discuss extensions to our work and potential applications for the ongoing coronavirus pandemic.

The cost of insecurity: from flare-up to control of a major Ebola virus disease hotspot during the outbreak in the Democratic Republic of the Congo, 2019.

The ongoing Ebola outbreak in the eastern Democratic Republic of the Congo is facing unprecedented levels of insecurity and violence. We evaluate the likely impact in terms of added transmissibility and cases of major security incidents in the Butembo coordination hub. We also show that despite this additional burden, an adapted response strategy involving enlarged ring vaccination around clusters of cases and enhanced community engagement managed to bring this main hotspot under control.

Recurrent Cholera Outbreaks, Democratic Republic of the Congo, 2008-2017.

In 2017, the exacerbation of an ongoing countrywide cholera outbreak in the Democratic Republic of the Congo resulted in >53,000 reported cases and 1,145 deaths. To guide control measures, we analyzed the characteristics of cholera epidemiology in DRC on the basis of surveillance and cholera treatment center data for 2008-2017. The 2017 nationwide outbreak resulted from 3 distinct mechanisms: considerable increases in the number of cases in cholera-endemic areas, so-called hot spots, around the Great Lakes in eastern DRC; recurrent outbreaks progressing downstream along the Congo River; and spread along Congo River branches to areas that had been cholera-free for more than a decade. Case-fatality rates were higher in nonendemic areas and in the early phases of the outbreaks, possibly reflecting low levels of immunity and less appropriate prevention and treatment. Targeted use of oral cholera vaccine, soon after initial cases are diagnosed, could contribute to lower case-fatality rates.

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.

Detecting Ebola with limited laboratory access in the Democratic Republic of Congo: evaluation of a clinical passive surveillance reporting system.

BACKGROUND: Ebola virus disease (EVD) can be clinically severe and highly fatal, making surveillance efforts for early disease detection of paramount importance. In areas with limited access to laboratory testing, the Integrated Disease Surveillance and Response (IDSR) strategy in the Democratic Republic of Congo (DRC) may be a vital tool in improving outbreak response. METHODS: Using DRC IDSR data from the nation's four EVD outbreak periods from 2007-2014, we assessed trends of Viral Hemorrhagic Fever (VHF) and EVD differential diagnoses reportable through IDSR. With official case counts from active surveillance of EVD outbreaks, we assessed accuracy of reporting through the IDSR passive surveillance system. RESULTS: Although the active and passive surveillance represent distinct sets of data, the two were correlated, suggesting that passive surveillance based only on clinical evaluation may be a useful predictor of true cases prior to laboratory confirmation. There were 438 suspect VHF cases reported through the IDSR system and 416 EVD cases officially recorded across the outbreaks examined. CONCLUSION: Although collected prior to official active surveillance cases, case reporting through the IDSR during the 2007, 2008 and 2012 outbreaks coincided with official EVD epidemic curves. Additionally, all outbreak areas experienced increases in suspected cases for both malaria and typhoid fever during EVD outbreaks, underscoring the importance of training health care workers in recognising EVD differential diagnoses and the potential for co-morbidities.

Health service planning contributes to policy dialogue around strengthening district health systems: an example from DR Congo 2008-2013.

BACKGROUND: This case study from DR Congo demonstrates how rational operational planning based on a health systems strengthening strategy (HSSS) can contribute to policy dialogue over several years. It explores the operationalization of a national strategy at district level by elucidating a normative model district resource plan which details the resources and costs of providing an essential health services package at district level. This paper then points to concrete examples of how the results of this exercise were used for Ministry of Health (MoH) decision-making over a time period of 5 years. METHODS: DR Congo's HSSS and its accompanying essential health services package were taken as a base to construct a normative model health district comprising of 10 Health Centres (HC) and 1 District Hospital (DH). The normative model health district represents a standard set by the Ministry of Health for providing essential primary health care services. RESULTS: The minimum operating budget necessary to run a normative model health district is $17.91 per inhabitant per year, of which $11.86 is for the district hospital and $6.05 for the health centre. The Ministry of Health has employed the results of this exercise in 4 principal ways: 1.Advocacy and negotiation instrument; 2. Instrument to align donors; 3. Field planning; 4. Costing database to extract data from when necessary. CONCLUSIONS: The above results have been key in the policy dialogue on affordability of the essential health services package in DR Congo. It has allowed the MoH to provide transparent information on financing needs around the HSSS; it continues to help the MoH negotiate with the Ministry of Finance and bring partner support behind the HSSS.

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.

How to improve outbreak response: a case study of integrated outbreak analytics from Ebola in Eastern Democratic Republic of the Congo.

The emerging field of outbreak analytics calls attention to the need for data from multiple sources to inform evidence-based decision making in managing infectious diseases outbreaks. To date, these approaches have not systematically integrated evidence from social and behavioural sciences. During the 2018-2020 Ebola outbreak in Eastern Democratic Republic of the Congo, an innovative solution to systematic and timely generation of integrated and actionable social science evidence emerged in the form of the Cellulle d'Analyse en Sciences Sociales (Social Sciences Analytics Cell) (CASS), a social science analytical cell. CASS worked closely with data scientists and epidemiologists operating under the Epidemiological Cell to produce integrated outbreak analytics (IOA), where quantitative epidemiological analyses were complemented by behavioural field studies and social science analyses to help better explain and understand drivers and barriers to outbreak dynamics. The primary activity of the CASS was to conduct operational social science analyses that were useful to decision makers. This included ensuring that research questions were relevant, driven by epidemiological data from the field, that research could be conducted rapidly (ie, often within days), that findings were regularly and systematically presented to partners and that recommendations were co-developed with response actors. The implementation of the recommendations based on CASS analytics was also monitored over time, to measure their impact on response operations. This practice paper presents the CASS logic model, developed through a field-based externally led consultation, and documents key factors contributing to the usefulness and adaption of CASS and IOA to guide replication for future outbreaks.

A Multidisciplinary Investigation of the First Chikungunya Virus Outbreak in Matadi in the Democratic Republic of the Congo.

Early March 2019, health authorities of Matadi in the Democratic Republic of the Congo alerted a sudden increase in acute fever/arthralgia cases, prompting an outbreak investigation. We collected surveillance data, clinical data, and laboratory specimens from clinical suspects (for CHIKV-PCR/ELISA, malaria RDT), semi-structured interviews with patients/caregivers about perceptions and health seeking behavior, and mosquito sampling (adult/larvae) for CHIKV-PCR and estimation of infestation levels. The investigations confirmed a large CHIKV outbreak that lasted February-June 2019. The total caseload remained unknown due to a lack of systematic surveillance, but one of the two health zones of Matadi notified 2686 suspects. Of the clinical suspects we investigated (n = 220), 83.2% were CHIKV-PCR or IgM positive (acute infection). One patient had an isolated IgG-positive result (while PCR/IgM negative), suggestive of past infection. In total, 15% had acute CHIKV and malaria. Most adult mosquitoes and larvae (>95%) were Aedes albopictus. High infestation levels were noted. CHIKV was detected in 6/11 adult mosquito pools, and in 2/15 of the larvae pools. This latter and the fact that 2/6 of the CHIKV-positive adult pools contained only males suggests transovarial transmission. Interviews revealed that healthcare seeking shifted quickly toward the informal sector and self-medication. Caregivers reported difficulties to differentiate CHIKV, malaria, and other infectious diseases resulting in polypharmacy and high out-of-pocket expenditure. We confirmed a first major CHIKV outbreak in Matadi, with main vector Aedes albopictus. The health sector was ill-prepared for the information, surveillance, and treatment needs for such an explosive outbreak in a CHIKV-naïve population. Better surveillance systems (national level/sentinel sites) and point-of-care diagnostics for arboviruses are needed.

Contextual, Social and Epidemiological Characteristics of the Ebola Virus Disease Outbreak in Likati Health Zone, Democratic Republic of the Congo, 2017.

While the clinical, laboratory and epidemiological investigation results of the Ebola outbreak in Likati Health Zone, Democratic Republic of the Congo (DRC) in May 2017 have been previously reported, we provide novel commentary on the contextual, social, and epidemiological characteristics of the epidemic. As first responders with the outbreak Surveillance Team, we explain the procedures that led to a successful epidemiological investigation and ultimately a rapid end to the epidemic. We discuss the role that several factors played in the trajectory of the epidemic, including traditional healers, insufficient knowledge of epidemiological case definitions, a lack of community-based surveillance systems and tools, and remote geography. We also demonstrate how a collaborative Rapid Response Team and implementation of community-based surveillance methods helped counter contextual challenges during the Likati epidemic and aid in identifying and reporting suspected cases and contacts in remote and rural settings. Understanding these factors can hinder or help in the rapid detection, notification, and response to future epidemics in the DRC.

Lessons Learned from Reinforcing Epidemiologic Surveillance During the 2017 Ebola Outbreak in the Likati District, Democratic Republic of the Congo.

On May 12, 2017, the Democratic Republic of Congo (DRC) publicly declared an outbreak of Ebola virus disease (EVD) in the Likati District of the Bas-Uélé Province, 46 days after the index case became symptomatic. The delayed EVD case detection and reporting highlights the importance of establishing real-time surveillance, consistent with the Global Health Security Agenda. We describe lessons learned from implementing improved EVD case detection and reporting strategies at the outbreak epicenter and make recommendations for future response efforts. The strategies included daily coordination meetings to enhance effective and efficient outbreak response activities, assessment and adaptation of case definitions and reporting tools, establishment of a community alert system using context-appropriate technology, training facility and community health workers on adapted case definitions and reporting procedures, development of context-specific plans for outbreak data management, and strengthened operational support for communications and information-sharing networks. Post-outbreak, surveillance officials should preemptively plan for the next outbreak by developing emergency response plans, evaluating the case definitions and reporting tools used, retraining on revised case definitions, and developing responsive strategies for overcoming telecommunications and technology challenges. The ongoing EVD outbreak in the North Kivu and Ituri provinces of DRC, currently the second largest EVD outbreak in history, demonstrates that documentation of successful context-specific strategies and tools are needed to combat the next outbreak. The lessons learned from the rapid containment of the EVD outbreak in Likati can be applied to the DRC and other rural low-resource settings to ensure readiness for future zoonotic disease outbreaks.

Recommendations for the COVID-19 Response at the National Level Based on Lessons Learned from the Ebola Virus Disease Outbreak in the Democratic Republic of the Congo.

The tenth outbreak of Ebola virus disease (EVD) in North Kivu, the Democratic Republic of the Congo (DRC), was declared 8 days after the end of the ninth EVD outbreak, in the Equateur Province on August 1, 2018. With a total of 3,461 confirmed and probable cases, the North Kivu outbreak was the second largest outbreak after that in West Africa in 2014-2016, and the largest observed in the DRC. This outbreak was difficult to control because of multiple challenges, including armed conflict, population displacement, movement of contacts, community mistrust, and high population density. It took more than 21 months to control the outbreak, with critical innovations and systems put into place. We describe systems that were put into place during the EVD response in the DRC that can be leveraged for the response to the current COVID-19 global pandemic.

The impact of Infection Prevention and control (IPC) bundle implementationon IPC compliance during the Ebola virus outbreak in Mbandaka/Democratic Republic of the Congo: a before and after design.

OBJECTIVES: To assess the impact of refresher training of healthcare workers (HCWs) in infection prevention and control (IPC), ensuring consistent adequate supplies and availability of IPC kits and carrying out weekly monitoring of IPC performance in healthcare facilities (HCFs) DESIGN: This was a before and after comparison study SETTINGS: This study was conducted from June to July 2018 during an Ebola virus disease (EVD) outbreak in Equateur Province in the Democratic Republic of the Congo (DRC). PARTICIPANTS: 48 HCFs INTERVENTIONS: HCWs capacity building in basic IPC, IPC kit donation and IPC mentoring. PRIMARY OUTCOME MEASURES: IPC score RESULTS: 48 HCFs were evaluated and 878 HCWs were trained, of whom 437 were women and 441 were men. The mean IPC score at baseline was modestly higher in hospitals (8%) compared with medical centres (4%) and health centres (4%), respectively. The mean IPC score at follow-up significantly increased to 50% in hospitals, 39% in medical centres and 36% in health centres (p value<0.001). The aggregate mean IPC score at baseline for all HCFs, combined was 4.41% and at follow-up it was 39.51% with a mean difference of 35.08% (p-value<0.001). CONCLUSIONS: Implementation of HCW capacity building in IPC, IPC kit donation to HCF and mentoring in IPC improved IPC compliance during the ninth EVD outbreak in the DRC.

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BACKGROUND: As of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak. METHODS: For short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts. RESULTS: During validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone. CONCLUSIONS: Our projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges.

Estimating the impact of violent events on transmission in Ebola virus disease outbreak, Democratic Republic of the Congo, 2018-2019.

INTRODUCTION: As of April 2019, the current Ebola virus disease (EVD) outbreak in the Democratic Republic of the Congo (DRC) is occurring in a longstanding conflict zone and has become the second largest EVD outbreak in history. It is suspected that after violent events occur, EVD transmission will increase; however, empirical studies to understand the impact of violence on transmission are lacking. Here, we use spatial and temporal trends of EVD case counts to compare transmission rates between health zones that have versus have not experienced recent violent events during the outbreak. METHODS: We collected daily EVD case counts from DRC Ministry of Health. A time-varying indicator of recent violence in each health zone was derived from events documented in the WHO situation reports. We used the Wallinga-Teunis technique to estimate the reproduction number R for each case by day per zone in the 2018-2019 outbreak. We fit an exponentially decaying curve to estimates of R overall and by health zone, for comparison to past outbreaks. RESULTS: As of 16 April 2019, the mean overall R for the entire outbreak was 1.11. We found evidence of an increase in the estimated transmission rates in health zones with recently reported violent events versus those without (p = 0.008). The average R was estimated as between 0.61 and 0.86 in regions not affected by recent violent events, and between 1.01 and 1.07 in zones affected by violent events within the last 21 days, leading to an increase in R between 0.17 and 0.53. Within zones with recent violent events, the mean estimated quenching rate was lower than for all past outbreaks except the 2013-2016 West African outbreak. CONCLUSION: The difference in the estimated transmission rates between zones affected by recent violent events suggests that violent events are contributing to increased transmission and the ongoing nature of this outbreak.

Real-time predictions of the 2018-2019 Ebola virus disease outbreak in the Democratic Republic of the Congo using Hawkes point process models.

As of June 16, 2019, an Ebola virus disease (EVD) outbreak has led to 2136 reported cases in the northeastern region of the Democratic Republic of the Congo (DRC). As this outbreak continues to threaten the lives and livelihoods of people already suffering from civil strife and armed conflict, relatively simple mathematical models and their short-term predictions have the potential to inform Ebola response efforts in real time. We applied recently developed non-parametrically estimated Hawkes point processes to model the expected cumulative case count using daily case counts from May 3, 2018, to June 16, 2019, initially reported by the Ministry of Health of DRC and later confirmed in World Health Organization situation reports. We generated probabilistic estimates of the ongoing EVD outbreak in DRC extending both before and after June 16, 2019, and evaluated their accuracy by comparing forecasted vs. actual outbreak sizes, out-of-sample log-likelihood scores and the error per day in the median forecast. The median estimated outbreak sizes for the prospective thee-, six-, and nine-week projections made using data up to June 16, 2019, were, respectively, 2317 (95% PI: 2222, 2464); 2440 (95% PI: 2250, 2790); and 2544 (95% PI: 2273, 3205). The nine-week projection experienced some degradation with a daily error in the median forecast of 6.73 cases, while the six- and three-week projections were more reliable, with corresponding errors of 4.96 and 4.85 cases per day, respectively. Our findings suggest the Hawkes point process may serve as an easily-applied statistical model to predict EVD outbreak trajectories in near real-time to better inform decision-making and resource allocation during Ebola response efforts.

Medical countermeasures during the 2018 Ebola virus disease outbreak in the North Kivu and Ituri Provinces of the Democratic Republic of the Congo: a rapid genomic assessment.

BACKGROUND: The real-time generation of information about pathogen genomes has become a vital goal for transmission analysis and characterisation in rapid outbreak responses. In response to the recently established genomic capacity in the Democratic Republic of the Congo, we explored the real-time generation of genomic information at the start of the 2018 Ebola virus disease (EVD) outbreak in North Kivu Province. METHODS: We used targeted-enrichment sequencing to produce two coding-complete Ebola virus genomes 5 days after declaration of the EVD outbreak in North Kivu. Subsequent sequencing efforts yielded an additional 46 genomes. Genomic information was used to assess early transmission, medical countermeasures, and evolution of Ebola virus. FINDINGS: The genomic information demonstrated that the EVD outbreak in the North Kivu and Ituri Provinces was distinct from the 2018 EVD outbreak in Équateur Province of the Democratic Republic of the Congo. Primer and probe mismatches to Ebola virus were identified in silico for all deployed diagnostic PCR assays, with the exception of the Cepheid GeneXpert GP assay. INTERPRETATION: The first two coding-complete genomes provided actionable information in real-time for the deployment of the rVSVΔG-ZEBOV-GP Ebola virus envelope glycoprotein vaccine, available therapeutics, and sequence-based diagnostic assays. Based on the mutations identified in the Ebola virus surface glycoprotein (GP12) observed in all 48 genomes, deployed monoclonal antibody therapeutics (mAb114 and ZMapp) should be efficacious against the circulating Ebola virus variant. Rapid Ebola virus genomic characterisation should be included in routine EVD outbreak response procedures to ascertain efficacy of medical countermeasures. FUNDING: Defense Biological Product Assurance Office.