Estimating the epidemiology of chronic Hepatitis B Virus (HBV) infection in the UK: what do we know and what are we missing?

估算英国慢性乙型肝炎病毒 (HBV) 感染的流行病学:我们了解什么,又缺少什么?

阅读:1

Abstract

Background: HBV is the leading global cause of cirrhosis and primary liver cancer. However, the UK HBV population has not been well characterised, and estimates of UK HBV prevalence and/or incidence vary widely between sources. We aimed to i) extract and summarise existing national HBV prevalence estimates, ii) add a new estimate based on primary care data, and; iii) critique data sources from which estimates were derived. Methods: We undertook a narrative review, searching for national estimates of CHB case numbers in the UK (incorporating incidence, prevalence and/or test positivity data) across a range of overlapping sources, including governmental body reports, publications from independent bodies (including medical charities and non-governmental organisations) and articles in peer-reviewed scientific journals.  An alternative proxy for population prevalence was obtained via the UK antenatal screening programme which achieves over 95% coverage of pregnant women. We also searched for diagnoses of HBV in the QResearch primary care database based on laboratory tests and standardised coding. Results: We identified six CHB case number estimates, of which three reported information concerning population subgroups, including number of infected individuals across age, sex and ethnicity categories. Estimates among sources reporting prevalence varied from 0.27% to 0.73%, congruent with an estimated antenatal CHB prevalence of <0.5%. Our estimate, based on QResearch data, suggests a population prevalence of ~0.05%, reflecting a substantial underestimation based on primary care records. Discussion: Estimates varied by sources of error, bias and missingness, data linkage, and "blind spots" in HBV diagnoses testing/registration. The UK HBV burden is likely to be concentrated in vulnerable populations who may not be well represented in existing datasets including those experiencing socioeconomic deprivation and/or homelessness, ethnic minorities and people born in high-prevalence countries. This could lead to under- or over-estimation of population prevalence estimation. Multi-agency collaboration is required to fill evidence gaps.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。