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BackgroundNo distinctive clinical signs of Ebola virus disease (EVD) have prompted the development of rapid screening tools or called for a new approach to screening suspected Ebola cases. New screening approaches require evidence of clinical benefit and economic efficiency. As of now, no evidence or defined algorithm exists.ObjectiveTo evaluate, from a healthcare perspective, the efficiency of incorporating Ebola prediction scores and rapid diagnostic tests into the EVD screening algorithm during an outbreak.MethodsWe collected data on rapid diagnostic tests (RDTs) and prediction scores' accuracy measurements, e.g., sensitivity and specificity, and the cost of case management and RDT screening in EVD suspect cases. The overall cost of healthcare services (PPE, procedure time, and standard-of-care (SOC) costs) per suspected patient and diagnostic confirmation of EVD were calculated. We also collected the EVD prevalence among suspects from the literature. We created an analytical decision model to assess the efficiency of eight screening strategies: 1) Screening suspect cases with the WHO case definition for Ebola suspects, 2) Screening suspect cases with the ECPS at -3 points of cut-off, 3) Screening suspect cases with the ECPS as a joint test, 4) Screening suspect cases with the ECPS as a conditional test, 5) Screening suspect cases with the WHO case definition, then QuickNavi™-Ebola RDT, 6) Screening suspect cases with the ECPS at -3 points of cut-off and QuickNavi™-Ebola RDT, 7) Screening suspect cases with the ECPS as a conditional test and QuickNavi™-Ebola RDT, and 8) Screening suspect cases with the ECPS as a joint test and QuickNavi™-Ebola RDT. We performed a cost-effectiveness analysis to identify an algorithm that minimizes the cost per patient correctly classified. We performed a one-way and probabilistic sensitivity analysis to test the robustness of our findings.ResultsOur analysis found dual ECPS as a conditional test with the QuickNavi™-Ebola RDT algorithm to be the most cost-effective screening algorithm for EVD, with an effectiveness of 0.86. The cost-effectiveness ratio was 106.7 USD per patient correctly classified. The following algorithms, the ECPS as a conditional test with an effectiveness of 0.80 and an efficiency of 111.5 USD per patient correctly classified and the ECPS as a joint test with the QuickNavi™-Ebola RDT algorithm with an effectiveness of 0.81 and a cost-effectiveness ratio of 131.5 USD per patient correctly classified. These findings were sensitive to variations in the prevalence of EVD in suspected population and the sensitivity of the QuickNavi™-Ebola RDT.ConclusionsFindings from this study showed that prediction scores and RDT could improve Ebola screening. The use of the ECPS as a conditional test algorithm and the dual ECPS as a conditional test and then the QuickNavi™-Ebola RDT algorithm are the best screening choices because they are more efficient and lower the number of confirmation tests and overall care costs during an EBOV epidemic.

Introduction A serosurvey among health care providers (HCPs) and frontliners of an area previously affected by Ebola virus disease (EVD) in the Democratic Republic of the Congo (DRC) was conducted to assess the seroreactivity to Ebola virus antigens. Methods Serum samples were collected in a cohort of HCPs and frontliners (n = 698) participants in the EBL2007 vaccine trial (December 2019 to October 2022). Specimens seroreactive for EBOV were confirmed using either the Filovirus Animal Nonclinical Group (FANG) ELISA or a Luminex multiplex assay. Results The seroreactivity to at least two EBOV-Mayinga (m) antigens was found in 10 (1.4%: 95% CI, 0.7–2.6) samples for GP-EBOV-m + VP40-EBOV-m, and 2 (0.3%: 95% CI, 0.0–1.0) samples for VP40-EBOV-m + NP-EBOV-m using the Luminex assay. Seroreactivity to GP-EBOV-Kikwit (k) was observed in 59 (8.5%: 95%CI, 6.5–10.9) samples using FANG ELISA. Conclusion In contrast to previous serosurveys, a low seroprevalence was found in the HCP and frontline population participating in the EBL2007 Ebola vaccine trial in Boende, DRC. This underscores the high need for standardized antibody assays and cutoffs in EBOV serosurveys to avoid the broad range of reported EBOV seroprevalence rates in EBOV endemic areas.

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.

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

INTRODUCTION:The establishment of the influenza sentinel surveillance system in Kinshasa, Bas Congo, Maniema, Katanga, and Kasai Provinces allowed generation of important data on the molecular epidemiology of human influenza viruses circulating in the Democratic Republic of Congo (DRC). However, some challenges still exist, including the need for extending the influenza surveillance to more provinces. This study describes the pattern of influenza virus circulating in DRC during 2015. METHODOLOGY:Nasopharyngeal swabs were collected from January to December 2015 from outpatients with influenza-like illness (ILI) and in all hospitalized patients with Severe Acute Respiratory Infection (SARI). Molecular analysis was done to determine influenza type and subtype at the National Reference Laboratory (NRL) in Kinshasa using real time reverse transcription-polymerase chain reaction (rRT-PCR). Analysis of antiviral resistance by enzyme inhibition assay and nucleotide sequencing was performed by the Collaborating center in the USA (CDC, Atlanta). RESULTS:Out of 2,376 nasopharyngeal swabs collected from patients, 218 (9.1%) were positive for influenza virus. Among the positive samples, 149 were characterized as influenza virus type A (Flu A), 67 as type B (Flu B) and 2 mixed infections (Flu A and B). Flu A subtypes detected were H3N2 and H1N1. The Yamagata strain of Flu B was detected among patients in the country. Individuals aged between 5 and 14 years accounted for the largest age group affected by influenza virus. All influenza viruses detected were found to be sensitive to antiviral drugs such as oseltamivar, zanamivir, peramivir and laninamivar. CONCLUSION:The present study documented the possible involvement of both circulation of Flu A and B viruses in human respiratory infection in certain DRC provinces during 2015. This study emphasises the need to extend the influenza surveillance to other provinces for a better understanding of the epidemiology of influenza in DRC. It is envisioned that such a system would lead to improved disease control and patient management.

Rickettsia felis is a common emerging pathogen detected in mosquitoes in sub-Saharan Africa. We hypothesized that, as with malaria, great apes may be exposed to the infectious bite of infected mosquitoes and release R. felis DNA in their feces.We conducted a study of 17 forest sites in Central Africa, testing 1,028 fecal samples from 313 chimpanzees, 430 gorillas and 285 bonobos. The presence of rickettsial DNA was investigated by specific quantitative real-time PCR. Positive results were confirmed by a second PCR using primers and a probe targeting a specific gene for R. felis. All positive samples were sequenced.Overall, 113 samples (11%) were positive for the Rickettsia-specific gltA gene, including 25 (22%) that were positive for R. felis. The citrate synthase (gltA) sequence and outer membrane protein A (ompA) sequence analysis indicated 99% identity at the nucleotide level to R. felis. The 88 other samples (78%) were negative using R. felis-specific qPCR and were compatible with R. felis-like organisms.For the first time, we detected R. felis in wild-living ape feces. This non invasive detection of human pathogens in endangered species opens up new possibilities in the molecular epidemiology and evolutionary analysis of infectious diseases, beside HIV and malaria.