Dataset Information

Ebola virus disease nosocomial infections in the Democratic Republic of the Congo: a descriptive study of cases during the 2018-2020 outbreak.

ABSTRACT:

Objectives

To describe the characteristics of nosocomial cases of Ebola virus disease (EVD) in the Democratic Republic of the Congo between July 2018 and May 2020 in order to inform future interventions.

Methods

Nosocomial cases of EVD were identified during outbreak response surveillance, and a retrospective analysis of cases was conducted according to demographic characteristics and type of health facility (HF).

Results

Of 3481 cases of EVD, 579 (16.6%) were nosocomial. Of these, 332 cases occurred in women (57.3%). Patients and visitors accounted for 419 cases (72.4%), of which 79 (18.9%) were aged 6-≤18 years and 108 (25.8%) were aged ≤5 years. Health workers (HWs) accounted for the remaining 160 (27.6%) nosocomial cases. The case fatality rate (CFR) for HWs (66/160, 41.3%) was significantly lower than the CFR for patients and visitors (292/419, 69.7%) (P<0.001). The CFR was higher among cases aged 6-≤18 years (54/79, 68.4%) and ≤5 years (89/108, 82.4%). Referral HFs (>39 beds) had the highest prevalence of nosocomial EVD (148/579, 25.6%). Among HFs with at least one case of nosocomial infection, 50.0% (98/196) were privately owned.

Conclusions

Nurses and traditional healers should be targeted for infection prevention and control training, and supportive supervision should be provided to HFs to mitigate EVD transmission.

SUBMITTER: Baller A

PROVIDER: S-EPMC8755545 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Publications

Ebola virus disease nosocomial infections in the Democratic Republic of the Congo: a descriptive study of cases during the 2018-2020 outbreak.

Baller April A Padoveze Maria Clara MC Mirindi Patrick P Hazim Carmen Emily CE Lotemo Jonathan J Pfaffmann Jerome J Ndiaye Aminata A Carter Simone S Chabrat Marie-Amelie Degail MD Mangala Samuel S Banzua Berthe B Umutoni Chantal C Niang N'Deye Rosalie NR Kabego Landry L Ouedraogo Abdoulaye A Houdjo Bienvenue B Mwesha Didier D Ousman Kevin Babila KB Kolwaite Amy A Blaney David D DD Choi Mary J MJ Pallawo Raymond R Legand Anais A Park Benjamin B Formenty Pierre P Montgomery Joel M JM Gueye Abdou Salam AS Allegranzi Benedetta B Yao N'da Kona Michel NKM Fall Ibrahima Soce IS

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 20211207

<h4>Objectives</h4>To describe the characteristics of nosocomial cases of Ebola virus disease (EVD) in the Democratic Republic of the Congo between July 2018 and May 2020 in order to inform future interventions.<h4>Methods</h4>Nosocomial cases of EVD were identified during outbreak response surveillance, and a retrospective analysis of cases was conducted according to demographic characteristics and type of health facility (HF).<h4>Results</h4>Of 3481 cases of EVD, 579 (16.6%) were nosocomial. O ...[more]

PMID: 34883237

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Project description:ImportanceIn 2018 to 2020, the Democratic Republic of the Congo experienced the world's second largest Ebola virus disease (EVD) outbreak, killing 2290 individuals; women were disproportionately infected (57% of all cases) despite no evidence of differential biological EVD risk. Understanding how gender norms may influence exposure to EVD, intensity, and prognosis as well as personal protective behaviors against the virus is important to disease risk reduction and control interventions.ObjectiveTo assess whether men and women differ in personal protective behaviors (vaccine acceptance, health-seeking behaviors, physical distancing) and the mediating role of EVD information and knowledge, perceived disease risk, and social relations.Design, setting, and participantsThis cross-sectional, multistage cluster survey study of 1395 randomly selected adults was conducted in the Ebola-affected regions of North Kivu from April 20, 2019, to May 10, 2019. Path analyses were conducted using structural equation modeling to examine associations among study variables. Statistical analysis was conducted from August 2019 to May 2020.Main outcomes and measuresThe main behavioral outcomes of interest were (1) vaccine acceptance, (2) formal health care seeking, and (3) self-protective behaviors. The primary factor of interest was self-reported gender identity. We also assessed sociodemographic factors.ResultsAmong the study's 1395 participants, 1286 (93%) had Nande ethnicity and 698 (50%) were women; the mean (SD) age was 34.5 (13.1) years. Compared with female participants, male participants reported significantly higher levels of education, wealth, and mobile phone access. There were associations found between gender and all EVD preventive behavioral outcomes, with evidence for mediation through EVD knowledge and belief in rumors. Men reported greater EVD knowledge accuracy compared with women (mean [SE] score for men: 12.06 [0.13] vs women: 11.08 [0.16]; P < .001), and greater knowledge accuracy was associated with increases in vaccine acceptance (β = 0.37; P < .001), formal care seeking (β = 0.39; P < .001), and self-protective behaviors (β = 0.35; P < .001). Lower belief in rumors was associated with greater vaccine acceptance (β = -0.30; P < .001), and greater EVD information awareness was associated with increased adoption of self-protective behaviors (β = 0.23; P < .001).Conclusions and relevanceThis survey study found gender differences in adopting preventive protective behaviors against EVD. These findings suggest that it is critical to design gender-sensitive communication and vaccination strategies, while engaging women and their community as a whole in any response to infectious disease outbreaks. Research on the potential link between gender and sociodemographics factors associated with disease risk and outcomes is needed.

Project description:BackgroundAn Ebola Virus Disease (EVD) outbreak occurred in North Kivu between 2018 and 2020. This eastern province of the Democratic Republic of Congo was also grappling with insecurity caused by several armed groups. This study aimed to explore the barriers and facilitators to utilizing Healthcare Facilities (HCFs) by non-Ebola patients during the crisis.MethodsA qualitative case study was conducted in Beni and Butembo with 24 relatives of 15 deceased non-EVD patients, 47 key informants from healthcare workers (HCWs), as well as community leaders. Semi-structured interviews were conducted to explore three key areas: (i) the participants' illness history, care pathway, care, and social support; (ii) their perceptions of how EVD affected the care outcome; and (iii) their opinions on the preparedness, supply, use, and quality of healthcare before and during the outbreak. All interviews were recorded, transcribed verbatim, and thematically analysed using Atlas-ti 8.0.ResultsNine of the 15 deaths were female and their ages ranged from 7 to 79 years. The causes of death were non-communicable (13) or infectious (2) diseases. Conspiracy theories, failure to establish security, and the concept of the ''Ebola business'' were associated with misinformation and lower levels of trust in government and HCFs. The negative perceptions, fear of being identified as an Ebola case, apprehension about the triage unit, and inadequacy of personal protective equipment resulted in a preference for private or informal HCFs. For half of the deceased's relatives, the Ebola outbreak hastened their death. Conversely, community involvement, employing familiar, neutral, and credible HCWs, and implementing a free care policy increased the number of visits. These results were observable despite a lack of funds, overstretched HCWs, and long waiting time.ConclusionsOur findings can inform policies before and during future outbreaks to enhance the resilience of routine HCFs by maintaining dialogue between HCWs and patients, and rebuilding confidence in HCFs. Quantitative studies including context analysis are essential to identify the determinants of care-seeking during such a crisis.

Project description:BackgroundThe 2018-2019 Ebola virus disease (EVD) outbreak in North Kivu and Ituri provinces in the Democratic Republic of the Congo (DRC) is the largest ever recorded in the DRC. It has been declared a Public Health Emergency of International Concern. The outbreak emerged in a region of chronic conflict and insecurity, and directed attacks against health care workers may have interfered with disease response activities. Our study characterizes and quantifies the broader conflict dynamics over the course of the outbreak by pairing epidemiological and all available spatial conflict data.MethodsWe build a set of conflict variables by mapping the spatial locations of all conflict events and their associated deaths in each of the affected health zones in North Kivu and Ituri, eastern DRC, before and during the outbreak. Using these data, we compare patterns of conflict before and during the outbreak in affected health zones and those not affected. We then test whether conflict is correlated with increased EVD transmission at the health zone level.FindingsThe incidence of conflict events per capita is ~ 600 times more likely in Ituri and North Kivu than for the rest of the DRC. We identified 15 time periods of substantial uninterrupted transmission across 11 health zones and a total of 120 bi-weeks. We do not find significant short-term associations between the bi-week reproduction numbers and the number of conflicts. However, we do find that the incidence of conflict per capita was correlated with the incidence of EVD per capita at the health zone level for the entire outbreak (Pearson's r = 0.33, 95% CI 0.05-0.57). In the two provinces, the monthly number of conflict events also increased by a factor of 2.7 in Ebola-affected health zones (p value < 0.05) compared to 2.0 where no transmission was reported and 1.3 in the rest of the DRC, in the period between February 2019 and July 2019.ConclusionWe characterized the association between variables documenting broad conflict levels and EVD transmission. Such assessment is important to understand if and how such conflict variables could be used to inform the outbreak response. We found that while these variables can help characterize long-term challenges and susceptibilities of the different regions they provide little insight on the short-term dynamics of EVD transmission.

Project description:BackgroundThe Democratic Republic of the Congo has had 15 Ebola virus disease (EVD) outbreaks, from 1976 to 2023. On June 1, 2020, the Democratic Republic of the Congo declared an outbreak of EVD in the western Équateur Province (11th outbreak), proximal to the 2018 Tumba and Bikoro outbreak and concurrent with an outbreak in the eastern Nord Kivu Province. In this Article, we assessed whether the 11th outbreak was genetically related to previous or concurrent EVD outbreaks and connected available epidemiological and genetic data to identify sources of possible zoonotic spillover, uncover additional unreported cases of nosocomial transmission, and provide a deeper investigation into the 11th outbreak.MethodsWe analysed epidemiological factors from the 11th EVD outbreak to identify patient characteristics, epidemiological links, and transmission modes to explore virus spread through space, time, and age groups in the Équateur Province, Democratic Republic of the Congo. Trained field investigators and health professionals recorded data on suspected, probable, and confirmed cases, including demographic characteristics, possible exposures, symptom onset and signs and symptoms, and potentially exposed contacts. We used blood samples from individuals who were live suspected cases and oral swabs from individuals who were deceased to diagnose EVD. We applied whole-genome sequencing of 87 available Ebola virus genomes (from 130 individuals with EVD between May 19 and Sept 16, 2020), phylogenetic divergence versus time, and Bayesian reconstruction of phylogenetic trees to calculate viral substitution rates and study viral evolution. We linked the available epidemiological and genetic datasets to conduct a genomic and epidemiological study of the 11th EVD outbreak.FindingsBetween May 19 and Sept 16, 2020, 130 EVD (119 confirmed and 11 probable) cases were reported across 13 Équateur Province health zones. The individual identified as the index case reported frequent consumption of bat meat, suggesting the outbreak started due to zoonotic spillover. Sequencing revealed two circulating Ebola virus variants associated with this outbreak-a Mbandaka variant associated with the majority (97%) of cases and a Tumba-like variant with similarity to the ninth EVD outbreak in 2018. The Tumba-like variant exhibited a reduced substitution rate, suggesting transmission from a previous survivor of EVD.InterpretationIntegrating genetic and epidemiological data allowed for investigative fact-checking and verified patient-reported sources of possible zoonotic spillover. These results demonstrate that rapid genetic sequencing combined with epidemiological data can inform responders of the mechanisms of viral spread, uncover novel transmission modes, and provide a deeper understanding of the outbreak, which is ultimately needed for infection prevention and control during outbreaks.FundingWHO and US Centers for Disease Control and Prevention.

Project description:The Democratic Republic of the Congo's (DRC) 10th known Ebola virus disease (EVD) outbreak occurred between August 1, 2018 and June 25, 2020, and was the largest EVD outbreak in the country's history. During this outbreak, the DRC Ministry of Health initiated traveller health screening at points of control (POC, locations not on the border) and points of entry (POE) to minimize disease translocation via ground and air travel. We sought to develop a model-based approach that could be applied in future outbreaks to inform decisions for optimizing POC and POE placement, and allocation of resources more broadly, to mitigate the risk of disease translocation associated with ground-level population mobility. We applied a parameter-free mobility model, the radiation model, to estimate likelihood of ground travel between selected origin locations (including Beni, DRC) and surrounding population centres, based on population size and drive-time. We then performed a road network route analysis and included estimated population movement results to calculate the proportionate volume of travellers who would move along each road segment; this reflects the proportion of travellers that could be screened at a POC or POE. For Beni, the road segments estimated to have the highest proportion of travellers that could be screened were part of routes into Uganda and Rwanda. Conversely, road segments that were part of routes to other population centres within the DRC were estimated to have relatively lower proportions. We observed a posteriori that, in many instances, our results aligned with locations that were selected for actual POC or POE placement through more time-consuming methods. This study has demonstrated that mobility models and simple spatial techniques can help identify potential locations for health screening at newly placed POC or existing POE during public health emergencies based on expected movement patterns. Importantly, we have provided methods to estimate the proportionate volume of travellers that POC or POE screening measures would assess based on their location. This is critical information in outbreak situations when timely decisions must be made to implement public health interventions that reach the most individuals across a network.

Project description:BackgroundThe second largest Ebola virus disease (EVD) outbreak began in the Democratic Republic of Congo in July 2018 in North Kivu Province. Data suggest the outbreak is not epidemiologically linked to the 2018 outbreak in Equateur Province, and that independent introduction of Ebola virus (EBOV) into humans occurred. We tested for antibodies to ebolaviruses in febrile patients seeking care in North Kivu Province prior to the EVD outbreak.MethodsPatients were enrolled between May 2017 and April 2018, before the declared start of the outbreak in eastern DRC. Questionnaires were administered to collect demographic and behavioural information to identify risk factors for exposure. Biological samples were evaluated for ebolavirus nucleic acid, and for antibodies to ebolaviruses. Prevalence of exposure was calculated, and demographic factors evaluated for associations with ebolavirus serostatus.ResultsSamples were collected and tested from 272 people seeking care in the Rutshuru Health Zone in North Kivu Province. All patients were negative for filoviruses by PCR. Intial screening by indirect ELISA found that 30 people were reactive to EBOV-rGP. Results were supported by detection of ebolavirus reactive linear peptides using the Serochip platform. Differential screening of all reactive serum samples against the rGP of all six ebolaviruses and Marburg virus (MARV) showed that 29 people exhibited the strongest reactivity to EBOV and one to Bombali virus (BOMV), and western blotting confirmed results. Titers ranged from 1:100 to 1:12,800. Although both sexes and all ages tested positive for antibodies, women were significantly more likely to be positive and the majority of positives were in February 2018.ConclusionsWe provide the first documented evidence of exposure to Ebola virus in people in eastern DRC. We detected antibodies to EBOV in 10% of febrile patients seeking healthcare prior to the declaration of the 2018-2020 outbreak, suggesting early cases may have been missed or exposure ocurred without associated illness. We also report the first known detection of antibodies to BOMV, previously detected in bats in West and East Africa, and show that human exposure to BOMV has occurred. Our data suggest human exposure to ebolaviruses may be more frequent and geographically widespread.

Dataset Information

Ebola virus disease nosocomial infections in the Democratic Republic of the Congo: a descriptive study of cases during the 2018-2020 outbreak.

Objectives

Methods

Results

Conclusions

Publications

Ebola virus disease nosocomial infections in the Democratic Republic of the Congo: a descriptive study of cases during the 2018-2020 outbreak.

Similar Datasets

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