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.

BackgroundAs 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.MethodsFor 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.ResultsDuring 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.ConclusionsOur 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

Ebola virus disease in the Democratic Republic of the Congo, 1976-2014: Figures and Data

The Democratic Republic of the Congo has experienced the most outbreaks of Ebola virus disease since the virus' discovery in 1976. This dataset contains details on all outbreaks in this country, comprising 996 cases. The study found that, compared to patients over 15 years old, the odds of dying were significantly lower in patients aged 5 to 15 and higher in children under five (with 100% mortality in those under 2 years old). The odds of dying increased by 11% per day that a patient was not hospitalised. Outbreaks with an initially high reproduction number, R (>3), were rapidly brought under control, whilst outbreaks with a lower initial R caused longer and generally larger outbreaks. These findings can inform the choice of target age groups for interventions and highlight the importance of both reducing the delay between symptom onset and hospitalisation and rapid national and international response

A resource planning analysis of district hospital surgical services in the Democratic Republic of the Congo.

BACKGROUND: The impact of surgical conditions on global health, particularly on vulnerable populations, is gaining recognition. However, only 3.5% of the 234.2 million cases per year of major surgery are performed in countries where the world\u27s poorest third reside, such as the Democratic Republic of the Congo (DRC). METHODS: Data on the availability of anesthesia and surgical services were gathered from 12 DRC district hospitals using the World Health Organization\u27s (WHO\u27s) Emergency and Essential Surgical Care Situation Analysis Tool. We complemented these data with an analysis of the costs of surgical services in a Congolese norms-based district hospital as well as in 2 of the 12 hospitals in which we conducted the situational analysis (Demba and Kabare District Hospitals). For the cost analysis, we used WHO\u27s integrated Healthcare Technology Package tool. RESULTS: Of the 32 surgical interventions surveyed, only 2 of the 12 hospitals provided all essential services. The deficits in procedures varied from no deficits to 17 services that could not be provided, with an average of 7 essential procedures unavailable. Many of the hospitals did not have basic infrastructure such as running water and electricity; 9 of 12 had no or interrupted water and 7 of 12 had no or interrupted electricity. On average, 21% of lifesaving surgical interventions were absent from the facilities, compared with the model normative hospital. According to the normative hospital, all surgical services would cost US$2.17 per inhabitant per year, representing 33.3$0.08 per inhabitant per year, and at Kabare Hospital, US$0.69 per inhabitant per year. CONCLUSION: A significant portion of the health problems addressed at Congolese district hospitals is surgical in nature, but there is a current inability to meet this surgical need. The deficient services and substandard capacity in the surveyed district hospitals are systemic in nature, representing infrastructure, supply, equipment, and human resource constraints. Yet surgical services are affordable and represent a minor portion of the total operating budget. Greater emphasis should be made to appropriately fund district hospitals to meet the need for lifesaving surgical services

What questions we should be asking about COVID-19 in humanitarian settings: perspectives from the Social Sciences Analysis Cell in the Democratic Republic of the Congo.

COVID-19 is but one of many public health crises facing the people of the Democratic Republic of the Congo (DRC). On 25 June 2020, the DRC government announced the end of the country's largest Ebola outbreak on record and the second largest Ebola outbreak worldwide, a mere few weeks after a new outbreak (11th) started on 1 June 2020, in Mbandaka, Equateur Province.1 In 2019, measles claimed the lives of over 6000 people including 4500 children under the age of 5, malaria killed 17000 individuals, and cholera outbreaks affected 20 of 26 provinces, resulting in 31000 cases

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

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

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

Urban yellow fever outbreak-Democratic Republic of the Congo, 2016: Towards more rapid case detection.

BackgroundBetween December 2015 and July 2016, a yellow fever (YF) outbreak affected urban areas of Angola and the Democratic Republic of the Congo (DRC). We described the outbreak in DRC and assessed the accuracy of the YF case definition, to facilitate early diagnosis of cases in future urban outbreaks.Methodology/principal findingsIn DRC, suspected YF infection was defined as jaundice within 2 weeks after acute fever onset and was confirmed by either IgM serology or PCR for YF viral RNA. We used case investigation and hospital admission forms. Comparing clinical signs between confirmed and discarded suspected YF cases, we calculated the predictive values of each sign for confirmed YF and the diagnostic accuracy of several suspected YF case definitions. Fifty seven of 78 (73%) confirmed cases had travelled from Angola: 88% (50/57) men; median age 31 years (IQR 25-37). 15 (19%) confirmed cases were infected locally in urban settings in DRC. Median time from symptom onset to healthcare consultation was 7 days (IQR 6-9), to appearance of jaundice 8 days (IQR 7-11), to sample collection 9 days (IQR 7-14), and to hospitalization 17 days (IQR 11-26). A case definition including fever or jaundice, combined with myalgia or a negative malaria test, yielded an improved sensitivity (100%) and specificity (57%).Conclusions/significanceAs jaundice appeared late, the majority of cases were diagnosed too late for supportive care and prompt vector control. In areas with known local YF transmission, a suspected case definition without jaundice as essential criterion could facilitate earlier YF diagnosis, care and control

Evolution of a Disease Surveillance System: An Increase in Reporting of Human Monkeypox Disease in the Democratic Republic of the Congo, 2001–2013

Evaluating the effectiveness of a surveillance system, and how it improves over time has significant implications for disease control and prevention. In the Democratic Republic of Congo (DRC), the Integrated Disease Surveillance and Response (IDSR) was implemented to estimate the burden of disease, monitor changes in disease occurrence, and inform resource allocation. For this effort we utilized national passive surveillance data from DRC's IDSR to explore reporting trends of human monkeypox (MPX) from 2001 to 2013. We obtained surveillance data on MPX cases occurring between January 2001 and December 2013 from the DRC Ministry of Health (MoH). Phases of the surveillance system, yearly trends in reporting and estimated incidence for MPX were analyzed using SAS v9.2 and Health Mapper. Between 2001 and 2013, three discrete surveillance phases were identified that described the evolution of the surveillance system. Overall, an increase in suspected MPX cases was reported, beyond what would be expected from simply an improved reporting system. When restricting the analysis to the "stable phase," national estimated incidence increased from 2.13 per 100,000 in 2008 to 2.84 per 100,000 in 2013. The reported increase in MPX, based on an evolving surveillance system, is likely to be a true increase in disease occurrence rather than simply improvements to the surveillance system. Further analyses should provide critical information for improved prevention and control strategies and highlight areas of improvement for future data collection efforts