Statistical adjustments of sample representation in community-level estimates of COVID-19 transmission and immunity
- Funded by National Institutes of Health (NIH)
- Total publications:0 publications
Grant number: 5U01MD017867-04
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Key facts
Disease
COVID-19Start & end year
20222025Known Financial Commitments (USD)
$524,486Funder
National Institutes of Health (NIH)Principal Investigator
RESEARCH ASSOCIATE PROFESSOR Yajuan SiResearch Location
United States of AmericaLead Research Institution
UNIVERSITY OF MICHIGAN AT ANN ARBORResearch Priority Alignment
N/A
Research Category
Epidemiological studies
Research Subcategory
Disease susceptibility
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Unspecified
Vulnerable Population
Unspecified
Occupations of Interest
Unspecified
Abstract
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.