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.

Presumed Transmission of 2 Distinct Monkeypox Virus Variants from Central African Republic to Democratic Republic of the Congo.

We linked 4 mpox cases in South Ubangi, Democratic Republic of the Congo, to transboundary transmission from Central African Republic. Viral genome sequencing demonstrated that the monkeypox virus sequences belonged to distinct clusters of subclade Ia. This finding demonstrates the borderless nature of mpox and highlights the need for vigilant regional surveillance.

2017 Outbreak of Ebola Virus Disease in Northern Democratic Republic of Congo.

BACKGROUND: In 2017, the Democratic Republic of the Congo (DRC) recorded its eighth Ebola virus disease (EVD) outbreak, approximately 3 years after the previous outbreak. METHODS: Suspect cases of EVD were identified on the basis of clinical and epidemiological information. Reverse transcription-polymerase chain reaction (RT-PCR) analysis or serological testing was used to confirm Ebola virus infection in suspected cases. The causative virus was later sequenced from a RT-PCR-positive individual and assessed using phylogenetic analysis. RESULTS: Three probable and 5 laboratory-confirmed cases of EVD were recorded between 27 March and 1 July 2017 in the DRC. Fifty percent of cases died from the infection. EVD cases were detected in 4 separate areas, resulting in > 270 contacts monitored. The complete genome of the causative agent, a variant from the Zaireebolavirus species, denoted Ebola virus Muyembe, was obtained using next-generation sequencing. This variant is genetically closest, with 98.73% homology, to the Ebola virus Mayinga variant isolated from the first DRC outbreaks in 1976-1977. CONCLUSION: A single spillover event into the human population is responsible for this DRC outbreak. Human-to-human transmission resulted in limited dissemination of the causative agent, a novel Ebola virus variant closely related to the initial Mayinga variant isolated in 1976-1977 in the DRC.

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.

Metagenomic Next-Generation Sequencing of the 2014 Ebola Virus Disease Outbreak in the Democratic Republic of the Congo.

We applied metagenomic next-generation sequencing (mNGS) to detect Zaire Ebola virus (EBOV) and other potential pathogens from whole-blood samples from 70 patients with suspected Ebola hemorrhagic fever during a 2014 outbreak in Boende, Democratic Republic of the Congo (DRC) and correlated these findings with clinical symptoms. Twenty of 31 patients (64.5%) tested in Kinshasa, DRC, were EBOV positive by quantitative reverse transcriptase PCR (qRT-PCR). Despite partial degradation of sample RNA during shipping and handling, mNGS followed by EBOV-specific capture probe enrichment in a U.S. genomics laboratory identified EBOV reads in 22 of 70 samples (31.4%) versus in 21 of 70 (30.0%) EBOV-positive samples by repeat qRT-PCR (overall concordance = 87.1%). Reads from Plasmodium falciparum (malaria) were detected in 21 patients, of which at least 9 (42.9%) were coinfected with EBOV. Other positive viral detections included hepatitis B virus (n = 2), human pegivirus 1 (n = 2), Epstein-Barr virus (n = 9), and Orungo virus (n = 1), a virus in the Reoviridae family. The patient with Orungo virus infection presented with an acute febrile illness and died rapidly from massive hemorrhage and dehydration. Although the patient's blood sample was negative by EBOV qRT-PCR testing, identification of viral reads by mNGS confirmed the presence of EBOV coinfection. In total, 9 new EBOV genomes (3 complete genomes, and an additional 6 ≥50% complete) were assembled. Relaxed molecular clock phylogenetic analysis demonstrated a molecular evolutionary rate for the Boende strain 4 to 10× slower than that of other Ebola lineages. These results demonstrate the utility of mNGS in broad-based pathogen detection and outbreak surveillance.

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.

Contribution of Environment Sample-Based Detection to Ebola Outbreak Management.

Detection of chains of transmission is critical to interrupt Ebola virus (EBOV) outbreaks. For >25 years, quantitative reverse transcription polymerase chain reaction performed on biological fluids has been the reference standard for EBOV detection and identification. In the current study, we investigated the use of environmental sampling to detect EBOV shed from probable case patients buried without the collection of bodily fluids. During the 2012 Bundibugyo virus (BDBV) outbreak in the Democratic Republic of the Congo, environmental samples were screened for BDBV RNA by means of real-time polymerase chain reaction. Low levels of BDBV genomic RNA were detected in a hospital and in a house. Detection of BDBV RNA in the house led to the identification of the last chain of transmission still active, which resulted in the safe burial of the person with the last laboratory-confirmed case of this outbreak. Overall, environmental sampling can fill specific gaps to help confirm EBOV positivity and therefore be of value in outbreak management.

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.

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.

Community-based COVID-19 active case finding and rapid response in the Democratic Republic of the Congo: Improving case detection and response.

A community-based coronavirus disease (COVID-19) active case-finding strategy using an antigen-detecting rapid diagnostic test (Ag-RDT) was implemented in the Democratic Republic of Congo (DRC) to enhance COVID-19 case detection. With this pilot community-based active case finding and response program that was designed as a clinical, prospective testing performance, and implementation study, we aimed to identify insights to improve community diagnosis and rapid response to COVID-19. This pilot study was modeled on the DRC's National COVID-19 Response Plan and the COVID-19 Ag-RDT screening algorithm defined by the World Health Organization (WHO), with case findings implemented in 259 health areas, 39 health zones, and 9 provinces. In each health area, a 7-member interdisciplinary field team tested the close contacts (ring strategy) and applied preventive and control measures to each confirmed case. The COVID-19 testing capacity increased from 0.3 tests per 10,000 inhabitants per week in the first wave to 0.4, 1.6, and 2.2 in the second, third, and fourth waves, respectively. From January to November 2021, this capacity increase contributed to an average of 10.5% of COVID-19 tests in the DRC, with 7,110 positive Ag-RDT results for 40,226 suspected cases and close contacts who were tested (53.6% female, median age: 37 years [interquartile range: 26.0-50.0)]. Overall, 79.7% (n = 32,071) of the participants were symptomatic and 7.6% (n = 3,073) had comorbidities. The Ag-RDT sensitivity and specificity were 55.5% and 99.0%, respectively, based on reverse transcription polymerase chain reaction analysis, and there was substantial agreement between the tests (k = 0.63). Despite its limited sensitivity, the Ag-RDT has improved COVID-19 testing capacity, enabling earlier detection, isolation, and treatment of COVID-19 cases. Our findings support the community testing of suspected cases and asymptomatic close contacts of confirmed cases to reduce disease spread and virus transmission.

Epidemiological Comparison of Four COVID-19 Waves in the Democratic Republic of the Congo, March 2020-January 2022.

PURPOSE: Nationwide analyses are required to optimise and tailor activities to control future COVID-19 waves of resurgence continent-wide. We compared epidemiological and clinical outcomes of the four COVID-19 waves in the Democratic Republic of Congo (DRC). METHODS: This retrospective descriptive epidemiological analysis included data from the national line list of confirmed COVID-19 cases in all provinces for all waves between 9 March 2020 and 2 January 2022. Descriptive statistical measures (frequencies, percentages, case fatality rates [CFR], test positivity rates [TPR], and characteristics) were compared using chi-squared or the Fisher-Irwin test. RESULTS: During the study period, 72,108/445,084 (16.2%) tests were positive, with 9,641/56,637 (17.0%), 16,643/66,560 (25.0%), 24,172/157,945 (15.3%), and 21,652/163,942 (13.2%) cases during the first, second, third, and fourth waves, respectively. TPR significantly decreased from 17.0% in the first wave to 13.2% in the fourth wave as did infection of frontline health workers (5.2% vs. 0.9%). CFR decreased from 5.1 to 0.9% from the first to fourth wave. No sex- or age-related differences in distributions across different waves were observed. The majority of cases were asymptomatic in the first (73.1%) and second (86.6%) waves, in contrast to that in the third (11.1%) and fourth (31.3%) waves. CONCLUSION: Despite fewer reported cases, the primary waves (first and second) of the COVID-19 pandemic in the DRC were more severe than the third and fourth waves, with each wave being associated with a new SARS-CoV-2 variant. Tailored public health and social measures, and resurgence monitoring are needed to control future waves of COVID-19.

Accounting for population structure reveals ambiguity in the Zaire Ebolavirus reservoir dynamics.

Ebolaviruses pose a substantial threat to wildlife populations and to public health in Africa. Evolutionary analyses of virus genome sequences can contribute significantly to elucidate the origin of new outbreaks, which can help guide surveillance efforts. The reconstructed between-outbreak evolutionary history of Zaire ebolavirus so far has been highly consistent. By removing the confounding impact of population growth bursts during local outbreaks on the free mixing assumption that underlies coalescent-based demographic reconstructions, we find-contrary to what previous results indicated-that the circulation dynamics of Ebola virus in its animal reservoir are highly uncertain. Our findings also accentuate the need for a more fine-grained picture of the Ebola virus diversity in its reservoir to reliably infer the reservoir origin of outbreak lineages. In addition, the recent appearance of slower-evolving variants is in line with latency as a survival mechanism and with bats as the natural reservoir host.

Responding to the Challenge of the Dual COVID-19 and Ebola Epidemics in the Democratic Republic of Congo-Priorities for Achieving Control.

As of June 11, 2020, the Democratic Republic of the Congo (DRC) has reported 4,258 COVID-19 cases with 90 deaths. With other African countries, the DRC faces the challenge of striking a balance between easing public health lockdown measures to curtail the spread of SARS-CoV-2 and minimizing both economic hardships for large sectors of the population and negative impacts on health services for other infectious and noninfectious diseases. The DRC recently controlled its tenth Ebola virus disease (EVD) outbreak, but COVID-19 and a new EVD outbreak beginning on June 1, 2020 in the northwest Équateur Province have added an additional burden to health services. Although the epidemiology and transmission of EVD and COVID-19 differ, leveraging the public health infrastructures and experiences from coordinating the EVD response to guide the public health response to COVID-19 is critical. Building on the DRC's 40 years of experience with 10 previous EVD outbreaks, we highlight the DRC's multi-sectoral public health approach to COVID-19, which includes community-based screening, testing, contact-tracing, risk communication, community engagement, and case management. We also highlight remaining challenges and discuss the way forward for achieving control of both COVID-19 and EVD in the DRC.

Clinical Characteristics and Outcomes of Patients Hospitalized for COVID-19 in Africa: Early Insights from the Democratic Republic of the Congo.

Little is known about the clinical features and outcomes of SARS-CoV-2 infection in Africa. We conducted a retrospective cohort study of patients hospitalized for COVID-19 between March 10, 2020 and July 31, 2020 at seven hospitals in Kinshasa, Democratic Republic of the Congo (DRC). Outcomes included clinical improvement within 30 days (primary) and in-hospital mortality (secondary). Of 766 confirmed COVID-19 cases, 500 (65.6%) were male, with a median (interquartile range [IQR]) age of 46 (34-58) years. One hundred ninety-one (25%) patients had severe/critical disease requiring admission in the intensive care unit (ICU). Six hundred twenty patients (80.9%) improved and were discharged within 30 days of admission. Overall in-hospital mortality was 13.2% (95% CI: 10.9-15.8), and almost 50% among those in the ICU. Independent risk factors for death were age < 20 years (adjusted hazard ratio [aHR] = 6.62, 95% CI: 1.85-23.64), 40-59 years (aHR = 4.45, 95% CI: 1.83-10.79), and ≥ 60 years (aHR = 13.63, 95% CI: 5.70-32.60) compared with those aged 20-39 years, with obesity (aHR = 2.30, 95% CI: 1.24-4.27), and with chronic kidney disease (aHR = 5.33, 95% CI: 1.85-15.35). In marginal structural model analysis, there was no statistically significant difference in odds of clinical improvement (adjusted odds ratio [aOR] = 1.53, 95% CI: 0.88-2.67, P = 0.132) nor risk of death (aOR = 0.65, 95% CI: 0.35-1.20) when comparing the use of chloroquine/azithromycin versus other treatments. In this DRC study, the high mortality among patients aged < 20 years and with severe/critical disease is of great concern, and requires further research for confirmation and targeted interventions.

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.

2018 Ebola virus disease outbreak in Équateur Province, Democratic Republic of the Congo: a retrospective genomic characterisation.

BACKGROUND: The 2018 Ebola virus disease (EVD) outbreak in Équateur Province, Democratic Republic of the Congo, began on May 8, and was declared over on July 24; it resulted in 54 documented cases and 33 deaths. We did a retrospective genomic characterisation of the outbreak and assessed potential therapeutic agents and vaccine (medical countermeasures). METHODS: We used target-enrichment sequencing to produce Ebola virus genomes from samples obtained in the 2018 Équateur Province outbreak. Combining these genomes with genomes associated with known outbreaks from GenBank, we constructed a maximum-likelihood phylogenetic tree. In-silico analyses were used to assess potential mismatches between the outbreak strain and the probes and primers of diagnostic assays and the antigenic sites of the experimental rVSVΔG-ZEBOV-GP vaccine and therapeutics. An in-vitro flow cytometry assay was used to assess the binding capability of the individual components of the monoclonal antibody cocktail ZMapp. FINDINGS: A targeted sequencing approach produced 16 near-complete genomes. Phylogenetic analysis of these genomes and 1011 genomes from GenBank revealed a distinct cluster, confirming a new Ebola virus variant, for which we propose the name "Tumba". This new variant appears to have evolved at a slower rate than other Ebola virus variants (0·69 × 10-3 substitutions per site per year with "Tumba" vs 1·06 × 10-3 substitutions per site per year without "Tumba"). We found few sequence mismatches in the assessed assay target regions and antigenic sites. We identified nine amino acid changes in the Ebola virus surface glycoprotein, of which one resulted in reduced binding of the 13C6 antibody within the ZMapp cocktail. INTERPRETATION: Retrospectively, we show the feasibility of using genomics to rapidly characterise a new Ebola virus variant within the timeframe of an outbreak. Phylogenetic analysis provides further indications that these variants are evolving at differing rates. Rapid in-silico analyses can direct in-vitro experiments to quickly assess medical countermeasures. FUNDING: Defense Biological Product Assurance Office.

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

BACKGROUND: Between 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 FINDINGS: In 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/SIGNIFICANCE: As 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.