scholarly journals Estimates of Ebola Virus Case-Fatality Ratio in the 2014 West African Outbreak

2015 ◽  
Vol 60 (5) ◽  
pp. 829-829 ◽  
Author(s):  
Daniele Focosi ◽  
Fabrizio Maggi
Keyword(s):  
Ebola Virus ◽  
Case Fatality ◽  
West African ◽  
Case Fatality Ratio

scholarly journals Use of Viremia to Evaluate the Baseline Case Fatality Ratio of Ebola Virus Disease and Inform Treatment Studies: A Retrospective Cohort Study

PLoS Medicine ◽  
2015 ◽  
Vol 12 (12) ◽  
pp. e1001908 ◽  
Author(s):  
Oumar Faye ◽  
Alessio Andronico ◽  
Ousmane Faye ◽  
Henrik Salje ◽  
Pierre-Yves Boëlle ◽  
...  
Keyword(s):  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Ebola Virus ◽  
Virus Disease ◽  
Case Fatality ◽  
Ebola Virus Disease ◽  
Case Fatality Ratio ◽  
Baseline Case

scholarly journals The Ebola outbreak, 2013–2016: old lessons for new epidemics

2017 ◽  
Vol 372 (1721) ◽  
pp. 20160297 ◽  
Author(s):  
Cordelia E. M. Coltart ◽  
Benjamin Lindsey ◽  
Isaac Ghinai ◽  
Anne M. Johnson ◽  
David L. Heymann
Keyword(s):  
Decision Making ◽  
West Africa ◽  
Disease Control ◽  
Ebola Virus ◽  
Case Fatality ◽  
West African ◽  
Lessons Learned ◽  
Haemorrhagic Fever ◽  
Chronological Order ◽  
Epidemiological Parameters

Ebola virus causes a severe haemorrhagic fever in humans with high case fatality and significant epidemic potential. The 2013–2016 outbreak in West Africa was unprecedented in scale, being larger than all previous outbreaks combined, with 28 646 reported cases and 11 323 reported deaths. It was also unique in its geographical distribution and multicountry spread. It is vital that the lessons learned from the world's largest Ebola outbreak are not lost. This article aims to provide a detailed description of the evolution of the outbreak. We contextualize this outbreak in relation to previous Ebola outbreaks and outline the theories regarding its origins and emergence. The outbreak is described by country, in chronological order, including epidemiological parameters and implementation of outbreak containment strategies. We then summarize the factors that led to rapid and extensive propagation, as well as highlight the key successes, failures and lessons learned from this outbreak and the response. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

The Epidemiological Presentation Pattern of Ebola Virus Disease Outbreaks: Changes from 1976 to 2019

2020 ◽  
Vol 35 (3) ◽  
pp. 247-253
Author(s):  
Pedro Arcos González ◽  
Ángel Fernández Camporro ◽  
Anneli Eriksson ◽  
Carmen Alonso Llada
Keyword(s):  
At Risk ◽  
Ebola Virus ◽  
Virus Disease ◽  
Disease Outbreaks ◽  
Case Fatality ◽  
Ebola Virus Disease ◽  
World Health ◽  
Study Objective ◽  
Population At Risk ◽  
Case Fatality Ratio

AbstractIntroduction:Ebola Virus Disease (EVD) is the international health emergency paradigm due to its epidemiological presentation pattern, impact on public health, resources necessary for its control, and need for a national and international response.Study Objective:The objective of this work is to study the evolution and progression of the epidemiological presentation profile of Ebola disease outbreaks since its discovery in 1976 to the present, and to explore the possible reasons for this evolution from different perspectives.Methods:Retrospective observational study of 38 outbreaks of Ebola disease occurred from 1976 through 2019, excluding laboratory accidents. United Nations agencies and programs; Ministries of Health; the US Centers for Disease Control and Prevention (CDC); ReliefWeb; emergency nongovernmental organizations; and publications indexed in PubMed, EmBase, and Clinical Key have been used as sources of data. Information on the year of the outbreak, date of beginning and end, duration of the outbreak in days, number of cases, number of deaths, population at risk, geographic extension affected in Km2, and time of notification of the first cases to the World Health Organization (WHO) have been searched and analyzed.Results:Populations at risk have increased (P = .024) and the geographical extent of Ebola outbreaks has grown (P = .004). Reporting time of the first cases of Ebola to WHO has been reduced (P = .017) and case fatality (P = .028) has gone from 88% to 62% in the period studied. There have been differences (P = .04) between the outbreaks produced by the Sudan and Zaire strains of the virus, both in terms of duration and case fatality ratio (Sudan strain 74.5 days on average and 62.7% of case fatality ratio versus Zaire strain with 150 days on average and 55.4% case fatality ratio).Conclusion:There has been a change in the epidemiological profile of the Ebola outbreaks from 1976 through 2019 with an increase in the geographical extent of the outbreaks and the population at risk, as well as a significant decrease in the outbreaks case fatality rate. There have been advances in the detection and management capacity of outbreaks, and the notification time to the WHO has been reduced. However, there are social, economic, cultural, and political obstacles that continue to greatly hinder a more efficient epidemiological approach to Ebola disease, mainly in Central Africa.

scholarly journals Case Fatality Ratio Estimates for the 2013–2016 West African Ebola Epidemic: Application of Boosted Regression Trees for Imputation

2019 ◽  
Vol 70 (12) ◽  
pp. 2476-2483 ◽  
Author(s):  
Alpha Forna ◽  
Pierre Nouvellet ◽  
Ilaria Dorigatti ◽  
Christl A Donnelly
Keyword(s):  
Characteristic Curve ◽  
Regression Tree ◽  
Case Fatality ◽  
West African ◽  
Boosted Regression Trees ◽  
Survival Outcomes ◽  
Tree Model ◽  
Boosted Regression Tree ◽  
Case Fatality Ratio ◽  
Out Of Sample

Abstract Background The 2013–2016 West African Ebola epidemic has been the largest to date with >11 000 deaths in the affected countries. The data collected have provided more insight into the case fatality ratio (CFR) and how it varies with age and other characteristics. However, the accuracy and precision of the naive CFR remain limited because 44% of survival outcomes were unreported. Methods Using a boosted regression tree model, we imputed survival outcomes (ie, survival or death) when unreported, corrected for model imperfection to estimate the CFR without imputation, with imputation, and adjusted with imputation. The method allowed us to further identify and explore relevant clinical and demographic predictors of the CFR. Results The out-of-sample performance (95% confidence interval [CI]) of our model was good: sensitivity, 69.7% (52.5–75.6%); specificity, 69.8% (54.1–75.6%); percentage correctly classified, 69.9% (53.7–75.5%); and area under the receiver operating characteristic curve, 76.0% (56.8–82.1%). The adjusted CFR estimates (95% CI) for the 2013–2016 West African epidemic were 82.8% (45.6–85.6%) overall and 89.1% (40.8–91.6%), 65.6% (61.3–69.6%), and 79.2% (45.4–84.1%) for Sierra Leone, Guinea, and Liberia, respectively. We found that district, hospitalisation status, age, case classification, and quarter (date of case reporting aggregated at three-month intervals) explained 93.6% of the variance in the naive CFR. Conclusions The adjusted CFR estimates improved the naive CFR estimates obtained without imputation and were more representative. Used in conjunction with other resources, adjusted estimates will inform public health contingency planning for future Ebola epidemics, and help better allocate resources and evaluate the effectiveness of future inventions.

scholarly journals Heterogeneities in the case fatality ratio in the West African Ebola outbreak 2013–2016

2017 ◽  
Vol 372 (1721) ◽  
pp. 20160308 ◽  
Author(s):  
Tini Garske ◽  
Anne Cori ◽  
Archchun Ariyarajah ◽  
Isobel M. Blake ◽  
Ilaria Dorigatti ◽  
...  
Keyword(s):  
Case Fatality ◽  
Outcome Data ◽  
West African ◽  
World Health ◽  
Public Health Response ◽  
Individual Level ◽  
Reporting Practices ◽  
Case Fatality Ratio ◽  
Treatment Centre ◽  
Health Organization

The 2013–2016 Ebola outbreak in West Africa is the largest on record with 28 616 confirmed, probable and suspected cases and 11 310 deaths officially recorded by 10 June 2016, the true burden probably considerably higher. The case fatality ratio (CFR: proportion of cases that are fatal) is a key indicator of disease severity useful for gauging the appropriate public health response and for evaluating treatment benefits, if estimated accurately. We analysed individual-level clinical outcome data from Guinea, Liberia and Sierra Leone officially reported to the World Health Organization. The overall mean CFR was 62.9% (95% CI: 61.9% to 64.0%) among confirmed cases with recorded clinical outcomes. Age was the most important modifier of survival probabilities, but country, stage of the epidemic and whether patients were hospitalized also played roles. We developed a statistical analysis to detect outliers in CFR between districts of residence and treatment centres (TCs), adjusting for known factors influencing survival and identified eight districts and three TCs with a CFR significantly different from the average. From the current dataset, we cannot determine whether the observed variation in CFR seen by district or treatment centre reflects real differences in survival, related to the quality of care or other factors or was caused by differences in reporting practices or case ascertainment. This article is part of the themed issue ‘The 2013–2016 West African Ebola epidemic: data, decision-making and disease control’.

scholarly journals Early transmission and case fatality of Ebola virus at the index site of the 2013–16 west African Ebola outbreak: a cross-sectional seroprevalence survey

2019 ◽  
Vol 19 (4) ◽  
pp. 429-438 ◽  
Author(s):  
Joseph W S Timothy ◽  
Yper Hall ◽  
Joseph Akoi-Boré ◽  
Boubacar Diallo ◽  
Thomas R W Tipton ◽  
...  
Keyword(s):  
Ebola Virus ◽  
Case Fatality ◽  
West African ◽  
Cross Sectional ◽  
Index Site

A Note on Estimating the Case Fatality Ratio for Novel Corona Virus Disease (Covid-19)

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Prafulla Kumar Swain
Keyword(s):  
Confidence Interval ◽  
Graphical Representation ◽  
Virus Disease ◽  
Case Fatality ◽  
Case Fatality Ratio ◽  
Healthcare Planning ◽  
Robust Estimates ◽  
University Of Oxford ◽  
Pros And Cons ◽  
Death Cases

Background: In this paper an attempt has been made to estimate the Case Fatality Ratio (CFR) for coronavirus disease of India and few selected countries. and Also, highlighted the pros and cons of obtaining crude and adjusted CFR of COVID-19 pandemic. Material and Methods: Data extracted from WHO situation report and University of Oxford website have been used for this analysis. The CFR and its 95% confidence interval were computed, trend and bar plot was used for graphical representation. Results: The worldwide crude CFR stands 6.73% (95% CI 6.69 to 6.76) based on 21, 83, 877 confirmed and 1,46,872 death cases(as on 17th April,2020). Belgium was highest CFR 13.95% as compared to others. However, India’s CFR was found to be around 3.26% (as on 17th April, 2020). Conclusion: In conclusion, the estimation and interpretation of CFR is critical in response to ongoing COVID-19. The initial CFR estimates are subject to change, still it is useful for healthcare planning over the coming months. Moreover, the precise and robust estimates of CFR will be available only at the end of the epidemic.

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