13: Demographic Representativeness of the RADx-Up Cohort Compared to the U.S. Census Data

Meri Varkila Co-Author
Stanford Univeristy
 
Nivetha Subramanian Co-Author
Stanford University
 
Julie Parsonnet Co-Author
Stanford Univeristy
 
Shuchi Anand Co-Author
Stanford University
 
Maria Montez-Rath Co-Author
Stanford University
 
Glenn Chertow Co-Author
Stanford University
 
Xue Yu First Author
Stanford University
 
Xue Yu Presenting Author
Stanford University
 
Monday, Aug 4: 2:00 PM - 3:50 PM
2618 
Contributed Posters 
Music City Center 
Wastewater surveillance is a promising tool for tracking COVID-19,but its effectiveness in underserved populations-who may experience disproportionately severe illness-has not been fully established. The NIH-funded RADx-UP program, comprising 144 projects across the U.S., aims to expand COVID-19 testing accessibility, particularly in hard-hit areas. The utility of wastewater surveillance in underserved communities can be assessed by comparing its findings with screening data from RADx-UP, which includes both symptomatic and asymptomatic individuals. However, this assessment requires RADx-UP to be representative of the U.S. population, a criterion that can be evaluated through generalizability analysis. In this study, we report participant characteristics and compute a generalizability score, which quantifies how well a study sample reflects a target population of interest based on demographics and clinical characteristics, at the Federal Information Processing Standard (FIPS) geography code level. With over 350,000 participants in 1005 FIPS, we anticipate major metropolitan areas have sufficient data for generalizable estimates, especially in underserved counties.

Keywords

causal inference study

propensity score model

multiple imputation 

Abstracts


Main Sponsor

Section on Statistics in Epidemiology