Imperial College London
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DrIlariaDorigatti

Faculty of Medicine, School of Public Health

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 1451i.dorigatti

 
 
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Location

 

G24Norfolk PlaceSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Forna:2020:cid/ciz678,
author = {Forna, A and Nouvellet, P and Dorigatti, I and Donnelly, C},
doi = {cid/ciz678},
journal = {Clinical Infectious Diseases},
pages = {2476--2483},
title = {Case fatality ratio estimates for the 2013 – 2016 West African Ebola epidemic: application of Boosted Regression Trees for imputation},
url = {http://dx.doi.org/10.1093/cid/ciz678},
volume = {70},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - BackgroundThe 2013-2016 West African Ebola epidemic has been the largest to date with more than 11,000 deaths in the affected countries. The data collected have provided more insight than ever before into the case fatality ratio (CFR) and how it varies with age and other characteristics. However, the accuracy and precision of the naïve CFR remain limited because 44% of survival outcomes were unreported.MethodsUsing a Boosted Regression Tree (BRT) model, we imputed survival outcomes (i.e. 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.ResultsThe out-of-sample performances of our model were good: sensitivity=69.7% (95% CI 52.5%-75.6%), specificity=69.8% (95% CI 54.1%-75.6%), percentage correctly classified=69.9% (95% CI 53.7%-75.5%) and area under the ROC curve= 76.0% (95% CI 56.8%-82.1%). The adjusted CFR estimates for the 2013-2016 West African epidemic were 82.8% (95% CI 45%.6-85.6%) overall and 89.1% (95% CI 40.8%-91.6%) , 65.6% (95% CI 61.3%-69.6%) and 79.2% (95% CI 45.4-84.1) for Sierra Leone, Guinea and Liberia, respectively. We found that district, hospitalisation status, age, case classification and quarter explained 93.6% of the variance in the naïve CFR.ConclusionsThe adjusted CFR estimates improved the naïve 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 epidemic, and help better allocate resources and evaluate the effectiveness of future inventions.
AU  - Forna,A
AU  - Nouvellet,P
AU  - Dorigatti,I
AU  - Donnelly,C
DO  - cid/ciz678
EP  - 2483
PY  - 2020///
SN  - 1058-4838
SP  - 2476
TI  - Case fatality ratio estimates for the 2013 – 2016 West African Ebola epidemic: application of Boosted Regression Trees for imputation
T2  - Clinical Infectious Diseases
UR  - http://dx.doi.org/10.1093/cid/ciz678
UR  - http://hdl.handle.net/10044/1/72313
VL  - 70
ER  -
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