Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK.
Nat Commun. 2024 Jun 24;15(1):5340. doi: 10.1038/s41467-024-49201-4.
Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we used spatio-temporal regression and post-stratification models to UK's national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21 percentage points), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.
需要对特定地理区域在不同时间点的 SARS-CoV-2 感染流行率和抗体水平进行具有代表性的估计，以优化政策应对措施。然而，即使是在全人群中进行的调查，也可能受到不同关键群体参与率差异带来的偏差的影响。在这里，我们使用时空回归和后分层模型对英国国家 COVID-19 感染调查（CIS）进行分析，以获得不同地区、年龄和族裔（2020 年 12 月 7 日至 2022 年 5 月 4 日）的 PCR 阳性率（6,496,052 次检测）和抗体流行率（1,941,333 次检测）的代表性估计。通过后分层不考虑疫苗接种状态会导致 PCR 阳性率的低估，但会对人群中的抗体水平产生更大的高估（高达 21 个百分点），特别是在一般人群中疫苗接种率较低的群体中。不同地区和年龄组对每一波的相对贡献存在明显差异。未来对传染病调查的分析应考虑可能影响参与的重要结果驱动因素，其中疫苗接种是一个需要考虑的重要因素。
