A systematic review and meta-analysis of patient data from the west Africa (2013-16) Ebola virus disease epidemic

Science Direct
5 Jul 2019
Amanda M.Rojek, Alex Salam, Robert J.Ragotte, Emily Liddiard, Ahmed Elhussain, Anna Carlqvist, Michael Butler, Nzelle Kayem, Lyndsey Castle, Lang’O.Odondi, Kasia Stepniewska, Peter W.Horby



Over 28,000 patients were infected with Ebola virus disease (EVD) during the west Africa (2013-16) epidemic, yet there has been criticism of the lack of robust clinical descriptions of illness from that outbreak.


To perform a meta-analysis of published data from the epidemic in order to describe the clinical presentation, evolution of disease, and predictors of mortality in patients with EVD. To assess the quality and utility of published data for clinical and public health decision making.

Data sources

Primary articles available in PubMed and published between January 2014 and May 2017.


Studies that sequentially enrolled patients hospitalised for EVD and that reported acute clinical outcomes.


We performed meta-analyses using random-effect models and assessed heterogeneity using the I2 method. We assessed data representativeness by comparing meta-analysis estimates to World Health Organization aggregate data. We examined data utility by examining the availability and compatibility of data sets.


We screened 3653 articles and included 34 articles, representing 16 independent cohorts of patients (18 overlapping cohorts) and at least 6168 patients. The pooled estimate for case fatality rate was 51% (CI 46% to 56%). However, pooling of estimates for clinical presentation, and predictors of mortality in patients with EVD was hampered by significant heterogeneity, and inadequate data on clinical progression. Our assessment of data quality found that heterogeneity was largely unexplained, and data availability and compatibility were poor.


We have quantified a missed opportunity to generate reliable estimates of the clinical manifestations of EVD during the west Africa epidemic. Clinical data standards and data capture platforms are urgently needed.


Ebola, Ebola Virus Disease, emerging infection, epidemic, outbreak, viral haemorrhagic fever, viral hemorrhagic fever