38 research outputs found

    Ebola viral load at diagnosis associates with patient outcome and outbreak evolution

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    BACKGROUND. Ebola virus (EBOV) causes periodic outbreaks of life-threatening EBOV disease in Africa. Historically, these outbreaks have been relatively small and geographically contained; however, the magnitude of the EBOV outbreak that began in 2014 in West Africa has been unprecedented. The aim of this study was to describe the viral kinetics of EBOV during this outbreak and identify factors that contribute to outbreak progression. METHODS. From July to December 2014, one laboratory in Sierra Leone processed over 2,700 patient samples for EBOV detection by quantitative PCR (qPCR). Viremia was measured following patient admission. Age, sex, and approximate time of symptom onset were also recorded for each patient. The data was analyzed using various mathematical models to find trends of potential interest. RESULTS. The analysis revealed a significant difference (P = 2.7 × 10–77) between the initial viremia of survivors (4.02 log10 genome equivalents [GEQ]/ml) and nonsurvivors (6.18 log10 GEQ/ml). At the population level, patient viral loads were higher on average in July than in November, even when accounting for outcome and time since onset of symptoms. This decrease in viral loads temporally correlated with an increase in circulating EBOV-specific IgG antibodies among individuals who were suspected of being infected but shown to be negative for the virus by PCR. CONCLUSIONS. Our results indicate that initial viremia is associated with outcome of the individual and outbreak duration; therefore, care must be taken in planning clinical trials and interventions. Additional research in virus adaptation and the impacts of host factors on EBOV transmission and pathogenesis is needed

    Clinical and epidemiological performance of WHO Ebola case definitions: a systematic review and meta-analysis.

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    BACKGROUND: Ebola virus disease case definition is a crucial surveillance tool to detect suspected cases for referral and as a screening tool for clinicians to support admission and laboratory testing decisions at Ebola health facilities. We aimed to assess the performance of the WHO Ebola virus disease case definitions and other screening scores. METHODS: In this systematic review and meta-analysis, we searched PubMed, Scopus, Embase, and Web of Science for studies published in English between June 13, 1978, and Jan 14, 2020. We included studies that estimated the sensitivity and specificity of WHO Ebola virus disease case definitions, clinical and epidemiological characteristics (symptoms at admission and contact history), and predictive risk scores against the reference standard (laboratory-confirmed Ebola virus disease). Summary estimates of sensitivity and specificity were calculated using bivariate and hierarchical summary receiver operating characteristic (when four or more studies provided data) or random-effects meta-analysis (fewer than four studies provided data). FINDINGS: We identified 2493 publications, of which 14 studies from four countries (Sierra Leone, Guinea, Liberia, and Angola) were included in the analysis. 12 021 people with suspected disease were included, of whom 4874 were confirmed as positive for Ebola virus infection. Six studies explored the performance of WHO case definitions in non-paediatric populations, and in all of these studies, suspected and probable cases were combined and could not be disaggregated for analysis. The pooled sensitivity of the WHO Ebola virus disease case definitions from these studies was 81·5% (95% CI 74·1-87·2) and pooled specificity was 35·7% (28·5-43·6). History of contact or epidemiological link was a key predictor for the WHO case definitions (seven studies) and for risk scores (six studies). The most sensitive symptom was intense fatigue (79·0% [95% CI 74·4-83·0]), assessed in seven studies, and the least sensitive symptom was pain behind the eyes (1·0% [0·0-7·0]), assessed in three studies. The performance of fever as a symptom varied depending on the cutoff used to define fever. INTERPRETATION: WHO Ebola virus disease case definitions perform suboptimally to identify cases at both community level and during triage at Ebola health facilities. Inclusion of intense fatigue as a key symptom and contact history could improve the performance of case definitions, but implementation of these changes will require effective collaboration with, and trust of, affected communities. FUNDING: Médecins sans Frontières

    Deep Sequencing of RNA from Blood and Oral Swab Samples Reveals the Presence of Nucleic Acid from a Number of Pathogens in Patients with Acute Ebola Virus Disease and Is Consistent with Bacterial Translocation across the Gut.

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    In this study, samples from the 2013-2016 West African Ebola virus outbreak from patients in Guinea with Ebola virus disease (EVD) were analyzed to discover and classify what other pathogens were present. Throat swabs were taken from deceased EVD patients, and peripheral blood samples were analyzed that had been taken from patients when they presented at the treatment center with acute illness. High-throughput RNA sequencing (RNA-seq) and bioinformatics were used to identify the potential microorganisms. This approach confirmed Ebola virus (EBOV) in all samples from patients diagnosed as acute positive for the virus by quantitative reverse transcription-PCR in deployed field laboratories. Nucleic acid mapping to Plasmodium was also used on the patient samples, confirming results obtained with an antigen-based rapid diagnostic test (RDT) conducted in the field laboratories. The data suggested that a high Plasmodium load, as determined by sequence read depth, was associated with mortality and influenced the host response, whereas a lower parasite load did not appear to affect outcome. The identifications of selected bacteria from throat swabs via RNA-seq were confirmed by culture. The data indicated that the potential pathogens identified in the blood samples were associated with translocation from the gut, suggesting the presence of bacteremia, which transcriptome data suggested may induce or aggravate the acute-phase response observed during EVD. Transcripts mapping to different viruses were also identified, including those indicative of lytic infections. The development of high-resolution analysis of samples from patients with EVD will help inform care pathways and the most appropriate general antimicrobial therapy to be used in a resource-poor setting. IMPORTANCE Our results highlight the identification of an array of pathogens in the blood of patients with Ebola virus disease (EVD). This has not been done before, and the data have important implications for the treatment of patients with EVD, particularly considering antibiotic stewardship. We show that EVD patients who were also infected with Plasmodium, particularly at higher loads, had more adverse outcomes than patients with lower levels of Plasmodium. However, the presence of Plasmodium did not influence the innate immune response, and it is likely that the presence of EBOV dominated this response. Several viruses other than EBOV were identified, and bacteria associated with sepsis were also identified. These findings were indicative of bacterial translocation across the gut during the acute phase of EVD

    Clinical Presentation of Patients with Ebola Virus Disease in Conakry, Guinea

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    BACKGROUND: In March 2014, the World Health Organization was notified of an outbreak of Zaire ebolavirus in a remote area of Guinea. The outbreak then spread to the capital, Conakry, and to neighboring countries and has subsequently become the largest epidemic of Ebola virus disease (EVD) to date. METHODS: From March 25 to April 26, 2014, we performed a study of all patients with laboratory-confirmed EVD in Conakry. Mortality was the primary outcome. Secondary outcomes included patient characteristics, complications, treatments, and comparisons between survivors and nonsurvivors. RESULTS: Of 80 patients who presented with symptoms, 37 had laboratory-confirmed EVD. Among confirmed cases, the median age was 38 years (interquartile range, 28 to 46), 24 patients (65%) were men, and 14 (38%) were health care workers; among the health care workers, nosocomial transmission was implicated in 12 patients (32%). Patients with confirmed EVD presented to the hospital a median of 5 days (interquartile range, 3 to 7) after the onset of symptoms, most commonly with fever (in 84% of the patients; mean temperature, 38.6°C), fatigue (in 65%), diarrhea (in 62%), and tachycardia (mean heart rate, \u3e93 beats per minute). Of these patients, 28 (76%) were treated with intravenous fluids and 37 (100%) with antibiotics. Sixteen patients (43%) died, with a median time from symptom onset to death of 8 days (interquartile range, 7 to 11). Patients who were 40 years of age or older, as compared with those under the age of 40 years, had a relative risk of death of 3.49 (95% confidence interval, 1.42 to 8.59; P=0.007). CONCLUSIONS: Patients with EVD presented with evidence of dehydration associated with vomiting and severe diarrhea. Despite attempts at volume repletion, antimicrobial therapy, and limited laboratory services, the rate of death was 43%

    The Use of a Mobile Laboratory Unit in Support of Patient Management and Epidemiological Surveillance during the 2005 Marburg Outbreak in Angola

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    A mobile laboratory unit (MLU) was deployed to Uige, Angola as part of the World Health Organization response to an outbreak of viral hemorrhagic fever caused by Marburg virus (MARV). Utilizing mainly quantitative real-time PCR assays, this laboratory provided specific MARV diagnostics in the field. The MLU operated for 88 consecutive days allowing MARV-specific diagnostic response in <4 hours from sample receiving. Most cases were found among females in the child-bearing age and in children less than five years of age including a high number of paediatric cases implicating breastfeeding as potential transmission route. Oral swabs were identified as a useful alternative specimen source to the standard whole blood/serum specimens for patients refusing blood draw. There was a high concordance in test results between the MLU and the reference laboratory in Luanda operated by the US Centers for Disease Control and Prevention. The MLU was an important outbreak response asset providing valuable support in patient management and epidemiological surveillance. Field laboratory capacity should be expanded and made an essential part of any future outbreak investigation

    New filovirus disease classification and nomenclature.

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    The recent large outbreak of Ebola virus disease (EVD) in Western Africa resulted in greatly increased accumulation of human genotypic, phenotypic and clinical data, and improved our understanding of the spectrum of clinical manifestations. As a result, the WHO disease classification of EVD underwent major revision

    Temporal and spatial analysis of the 2014-2015 Ebola virus outbreak in West Africa

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    West Africa is currently witnessing the most extensive Ebola virus (EBOV) outbreak so far recorded. Until now, there have been 27,013 reported cases and 11,134 deaths. The origin of the virus is thought to have been a zoonotic transmission from a bat to a two-year-old boy in December 2013 (ref. 2). From this index case the virus was spread by human-to-human contact throughout Guinea, Sierra Leone and Liberia. However, the origin of the particular virus in each country and time of transmission is not known and currently relies on epidemiological analysis, which may be unreliable owing to the difficulties of obtaining patient information. Here we trace the genetic evolution of EBOV in the current outbreak that has resulted in multiple lineages. Deep sequencing of 179 patient samples processed by the European Mobile Laboratory, the first diagnostics unit to be deployed to the epicentre of the outbreak in Guinea, reveals an epidemiological and evolutionary history of the epidemic from March 2014 to January 2015. Analysis of EBOV genome evolution has also benefited from a similar sequencing effort of patient samples from Sierra Leone. Our results confirm that the EBOV from Guinea moved into Sierra Leone, most likely in April or early May. The viruses of the Guinea/Sierra Leone lineage mixed around June/July 2014. Viral sequences covering August, September and October 2014 indicate that this lineage evolved independently within Guinea. These data can be used in conjunction with epidemiological information to test retrospectively the effectiveness of control measures, and provides an unprecedented window into the evolution of an ongoing viral haemorrhagic fever outbreak.status: publishe
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