Imperial College London

ProfessorSalmanRawaf

Faculty of MedicineSchool of Public Health

Director of WHO Collaborating Centre
 
 
 
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Contact

 

+44 (0)20 7594 8814s.rawaf

 
 
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Assistant

 

Ms Ela Augustyniak +44 (0)20 7594 8603

 
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Location

 

311Reynolds BuildingCharing Cross Campus

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Summary

 

Publications

Citation

BibTex format

@article{GBD:2022:10.1016/S2468-1253(22)00124-8,
author = {GBD, 2019 Hepatitis B Collaborators},
doi = {10.1016/S2468-1253(22)00124-8},
journal = {The Lancet Gastroenterology & Hepatology},
pages = {796--829},
title = {Global, regional, and national burden of hepatitis B, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019},
url = {http://dx.doi.org/10.1016/S2468-1253(22)00124-8},
volume = {7},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - BACKGROUND: Combating viral hepatitis is part of the UN Sustainable Development Goals (SDGs), and WHO has put forth hepatitis B elimination targets in its Global Health Sector Strategy on Viral Hepatitis (WHO-GHSS) and Interim Guidance for Country Validation of Viral Hepatitis Elimination (WHO Interim Guidance). We estimated the global, regional, and national prevalence of hepatitis B virus (HBV), as well as mortality and disability-adjusted life-years (DALYs) due to HBV, as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. This included estimates for 194 WHO member states, for which we compared our estimates to WHO elimination targets. METHODS: The primary data sources were population-based serosurveys, claims and hospital discharges, cancer registries, vital registration systems, and published case series. We estimated chronic HBV infection and the burden of HBV-related diseases, defined as an aggregate of cirrhosis due to hepatitis B, liver cancer due to hepatitis B, and acute hepatitis B. We used DisMod-MR 2.1, a Bayesian mixed-effects meta-regression tool, to estimate the prevalence of chronic HBV infection, cirrhosis, and aetiological proportions of cirrhosis. We used mortality-to-incidence ratios modelled with spatiotemporal Gaussian process regression to estimate the incidence of liver cancer. We used the Cause of Death Ensemble modelling (CODEm) model, a tool that selects models and covariates on the basis of out-of-sample performance, to estimate mortality due to cirrhosis, liver cancer, and acute hepatitis B. FINDINGS: In 2019, the estimated global, all-age prevalence of chronic HBV infection was 4·1% (95% uncertainty interval [UI] 3·7 to 4·5), corresponding to 316 million (284 to 351) infected people. There was a 31·3% (29·0 to 33·9) decline in all-age prevalence between 1990 and 2019, with a more marked decline of 76·8% (76·2 to 77·5) in prevalence in childr
AU - GBD,2019 Hepatitis B Collaborators
DO - 10.1016/S2468-1253(22)00124-8
EP - 829
PY - 2022///
SN - 2468-1253
SP - 796
TI - Global, regional, and national burden of hepatitis B, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019
T2 - The Lancet Gastroenterology & Hepatology
UR - http://dx.doi.org/10.1016/S2468-1253(22)00124-8
UR - https://www.ncbi.nlm.nih.gov/pubmed/35738290
UR - https://www.sciencedirect.com/science/article/pii/S2468125322001248?via%3Dihub
UR - http://hdl.handle.net/10044/1/102219
VL - 7
ER -