课题基金 / 基金详情

Statistical adjustments of sample representation in community-level estimates of COVID-19 transmission and immunity

Statistical adjustments of sample representation in community-level estimates of COVID-19 transmission and immunity
社区层面 COVID-19 传播和免疫力估计中样本代表性的统计调整
批准号:
10600097
负责人:
Yajuan Si
金额:
$56.21万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-04-01 至 2025-12-31

项目摘要

项目成果

Yajuan Si的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Abstract Throughout the COVID-19 pandemic, government policy and healthcare implementation responses have been guided by reported positivity rates and vaccination rates in the community. The selection bias of these test data questions their validity as measures of the actual viral incidence in the community and as predictors of clinical burden. Publicly available vaccination data are frequently cited as a proxy for population immunity, but this metric ignores the effects of naturally-acquired immunity. The health disparities concerning asymptomatic and symptomatic patients are not yet studied. The proposal develops a valid metric to estimate the true viral incidence and naturally/vaccine-acquired immunity prevalence in the community, examine the health disparities and social inequality, and monitor the epidemic over time as an operational surveillance system. The approach collects routine testing data on SARS-CoV-2 exposure and antibody seropositivity among patients in a hospital system and performs statistical adjustments of sample representation using multilevel regression and poststratification (MRP), which adjusts for measured differences between the sample and population and also yields stable small area estimates. The data collection and analysis procedure can provide information to entire communities with generalizability and focus on burdens within specific demographics, with close attention to vulnerable populations on disparities across health outcomes, social determinants, and behaviors. In particular, the research will yield group-specific estimates of disparities with respect to asymptomatic and symptomatic patients and how these discrepancies may impact the socio-demographically dependent spread of disease and its subsequent treatment. The MRP adjustment will be made publicly accessible via a web interface and promote broad investigations with integrated data sources toward a national study.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Novel Approaches to Adjusting for Population Heterogeneity and Representation in Neuroimaging Studies
Novel Approaches to Adjusting for Population Heterogeneity and Representation in Neuroimaging Studies
Profiling missing data in electronic health records for diabetes care research
  • 批准号:
    9169147
  • 项目类别:
  • 资助金额:
    $22.31万
  • 财政年份:
    2016
  • 负责人:
    Yajuan Si
  • 依托单位:
海外基金