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Updated: Feb 5, 2026
Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
Published on: February 16, 2022
Multilevel regression and poststratification interface: an application to track community-level COVID-19 viral
Yajuan Si1, Toan Tran2, Jonah Gabry3
1Institute for Social Research, University of Michigan, 426 Thompson St., Ann Arbor, 48104, MI, USA. yajuan@umich.edu.
Purpose:
Public health surveillance systems require high-quality data to represent the population. In the absence of comprehensive or random testing throughout the COVID-19 pandemic, we have developed a proxy method for synthetic random sampling to estimate the actual community-level viral incidence, based on viral testing of patients who are asymptomatic and present for elective procedures within a hospital system.
Methods:
The approach collects routine testing data on SARS-CoV-2 exposure among outpatients and performs statistical adjustments of sample representation using multilevel regression and poststratification (MRP), a procedure that adjusts for nonrepresentativeness of the sample and yields stable small group estimates. We extend MRP to accommodate time-varying data and granular geography.
Results:
We have developed an open-source, user-friendly MRP interface for public implementation of the Bayesian analysis workflow. We illustrate the MRP interface with an application to track community-level COVID-19 viral transmission in Michigan. We present the estimated infection rate over time for the targeted population and across demographic and geographic subpopulations.
Conclusion:
The interface provides timely, substantive insights into population health trends and serves as a valuable surveillance tool for future epidemic preparedness. Beyond monitoring COVID-19, the MRP interface can analyze a wide range of health and social science data, making it broadly applicable to diverse research areas with reproducibility and scientific rigor.
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