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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 A descriptive cross-sectional survey was conducted using mixed quantitative and qualitative methods. Performance in IDSR core functions was assessed at multiple levels of the tiered health system through observations, key informant interviews, and analysis of health data. Qualitative data were also collected through focus groups and open-ended questions to guide the interpretation of the findings. 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 Data completeness was 100% at the provincial and health zone levels, and timeliness was 100% and 97% at the provincial and health zone levels, respectively. Healthcare facility data had an average completeness of 86%, and timeliness varied between health zones from 41 to 100%. The use of electronic Integrated Disease Surveillance and Response is not widely implemented. Data analyses are conducted mainly at the provincial and health zone levels, and are regularly disseminated to all levels. Preparedness capabilities were low, with 44% of health zones in North Kivu having a preparedness and response plan and 41% having a functional rapid response team. Conclusion Comparing the results of this assessment to the last IDSR assessment conducted in DRC in 2016, slight improvements in disease reporting have been made, despite several limitations in materials, equipment, infrastructure, and workforce training. 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.

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.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.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).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.Médecins Sans Frontières and its research affiliate Epicentre.

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.

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 Equateur 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 Biomedicale (National Biomedical Research Institute) in Kinshasa tested positive for Ebola virus. Genetic sequencing confirmed that the outbreaks in North Kivu and Equateur 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), Medecins Sans Frontieres, 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.

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.

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.

The world has seen outbreaks of emergency and re-emergency of infectious diseases very often in the past years, many of them with devastating consequences for low-income countries with fragile or nonexistent health system, covid-19 being by now the last of a long series of global challenges. Although it is a huge challenge for the whole world, one country is facing it together with a current Ebola outbreak plus violence and some other diseases. The Democratic Republic of Congo is facing the immediate effects of both epidemics as illness and death, however its consequences at the political and economic level are usually more complex and may be protracted. Following the debate on why poor countries remain poor, it is maybe useful to rethink poverty and inequality keeping in mind Amartya Sen's seminal concepts: development must comprise freedom and respect for human rights and institutions at the price of fostering a vicious circle of (re)emerging diseases and structural violence. Ebola epidemics, that usually face some challenges when they happen alone, now together with malaria, measles, plague and covid, on top of violence in some areas, the disease sees its protocols harmed: for covid the orientation is to stay isolated, for Ebola the response includes tracking contacts. What means coming with a team to field to do the mapping in the middle of a confinement. The surveillance for such many epidemics on top of violence and humanitarian crisis makes the Democratic Republic of Congo one of the most worrying countries in terms of consequences of the Covid outbreak. Key messages Study of the association between the Covid, Ebola virus disease outbreak and the at-risk population living in the conflict zone in Eastern Democratic Republic of Congo. The study presents the difficulties that the population encountered in the face of restrictions imposed by armed groups to reach health services during an Ebola outbreak, in a conflict zone.

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.

Summary box 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 17 000 individuals, and cholera outbreaks affected 20 of 26 provinces, resulting in 31 000 cases.2 These epidemics arise among communities living in overwhelming poverty, affected by conflict and regular population …

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-Uele 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.

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.

Objective 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. Methods 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. Results 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. Conclusions 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.

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. Keywords: Ebola virus disease, Hawkes point process, Mathematical modeling, Democratic Republic of Congo, Compartmental models

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., Author summary 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 been reported, and in which EVD cases and their contacts have been difficult for health workers to reach. We used an ensemble of models to estimate EVD transmission rates and to forecast the short- and long-term course of the outbreak. Our models project that a final size of roughly up to 300 additional cases is most likely, and estimate that transmission rates are higher than would be seen under optimal levels of contact tracing and vaccination. While a catastrophic outbreak is not projected, is it not ruled out, and prevention and vigilance are warranted.

Summary 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 Equateur 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.

High-functioning communicable disease surveillance systems are critical for public health preparedness. Countries that cannot quickly detect and contain diseases are a risk to the global community. The ability of all countries to comply with the International Health Regulations is paramount for global health security. Zoonotic diseases can be particularly dangerous for humans. We conducted a surveillance system assessment of institutional and individual capacity in Kinshasa and Haut Katanga provinces in the Democratic Republic of the Congo for nationally identified priority zoonotic diseases (eg, viral hemorrhagic fever [VHF], yellow fever, rabies, monkeypox, and influenza monitored through acute respiratory infections). Data were collected from 79 health workers responsible for disease surveillance at 2 provincial health offices, 9 health zone offices, 9 general reference hospitals, and 18 health centers and communities. A set of questionnaires was used to assess health worker training in disease surveillance methods; knowledge of case definitions; availability of materials and tools to support timely case detection, reporting, and data interpretation; timeliness and completeness of reporting; and supervision from health authorities. We found that health workers either had not been recently or ever trained in surveillance methods and that their knowledge of case definitions was low. Timeliness and completeness of weekly notification of epidemic-prone diseases was generally well performed, but the lack of available standardized reporting forms and archive of completed forms affected the quality of data collected. Lessons learned from our assessment can be used for targeted strengthening efforts to improve global health security.

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, 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.Author summaryAs 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 been reported, and in which EVD cases and their contacts have been difficult for health workers to reach. We used an ensemble of models to estimate EVD transmission rates and to forecast the short- and long-term course of the outbreak. Our models project that a final size of roughly up to 300 additional cases is most likely, and estimate that transmission rates are higher than would be seen under optimal levels of contact tracing and vaccination. While a catastrophic outbreak is not projected, is it not ruled out, and prevention and vigilance are warranted.

District hospitals in the DRC, on average, could not provide 21% of lifesaving surgical interventions due to deficiencies in basic infrastructure and essential surgical equipment and supplies. Surgery's important health impact and proportionally low service delivery budget argue for greater emphasis on surgical interventions, including for obstetric care., 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's 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's (WHO's) 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's 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% of the total patient caseload but only 18.3% of the total district hospital operating budget. At Demba Hospital, the operating budget required for surgical interventions was US$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.

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.

The Democratic Republic of the Congo has experienced the most outbreaks of Ebola virus disease since the virus' discovery in 1976. This article provides for the first time a description and a line list for all outbreaks in this country, comprising 996 cases. 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. DOI: http://dx.doi.org/10.7554/eLife.09015.001, eLife digest Ebola virus disease commonly causes symptoms such as high fever, vomiting, and diarrhoea. It may also cause muscle pain, headaches, and bleeding, and often leads to death. There have been seven outbreaks of Ebola virus disease in the Democratic Republic of the Congo (DRC) since 1976. The DRC is the country that has had the most outbreaks of this disease in the world. The most recent outbreak in the DRC was in 2014; this was separate from the outbreak that started in West Africa in the same year. Rosello, Mossoko et al. have now compiled the data from all seven of the outbreaks in the DRC into a single dataset, which covers almost 1000 patients. Analysing this data revealed that people between 25 and 64 years of age were most likely to be infected by the Ebola virus, possibly because most healthcare workers fall into this category. Age also affected how likely a patient was to die, with those aged under 5 and over 15 more likely to die than those aged between 5 and 15. Delaying going to hospital once symptoms had started, even by one day, also increased the likelihood of death. Rosello, Mossoko et al. also examined the Ebola virus effective reproduction number, which indicates how many people, on average, an infected person passes the virus on to. Outbreaks that initially featured viruses with a reproduction number larger than three tended to be stemmed quickly. However, when the reproduction number was lower, national and international organisations were slower to respond to the signs of the outbreak, leading to outbreaks that lasted longer. Further research is needed to understand why the likelihood of death is different for different age groups and to investigate the effect of the different routes of transmission of the virus on interventions such as vaccination. DOI: http://dx.doi.org/10.7554/eLife.09015.002

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.