, JAMA Network Open, 2023 Jan 23
Investigators
Kristen Azar, R.N., BSN, MSN/MPH, Investigator
Abstract
IntroductionTimely SARS-CoV-2 testing is critical to reducing transmission. Throughout the COVID-19 pandemic, COVID-19 test sites have been required to report SARS-CoV-2 test results to local or state public health departments,1and these data are used for detecting new surges of transmission. With increasing availability of home antigen tests, however, it is unclear how to interpret time trends in officially reported case counts and test positivity.Methods
The COVID-19 Citizen Science Study was approved by the institutional review board at the University of California, San Francisco, and was launched in March 2020 to gather patient-reported data about the COVID-19 pandemic.2This cohort study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies. Participants were invited by word of mouth or social media or from our recruitment partners via email, telephone, or patient portal message and then provided informed consent and baseline demographic information. Race and ethnicity were self-reported by the participants and were analyzed in this study to understand differences in unreported test frequency and test positivity. Each week, we asked participants about recent COVID-19 testing and test results. In March 2022, a question was added to distinguish tests conducted with a “Fully at-home test kit, with my own sample collection and reading of my own results” vs tests where “a healthcare provider collected my sample” or that were “sent to a clinical lab.”
To compare with SARS-CoV-2 testing reported nationally, we downloaded data from the Johns Hopkins Coronavirus Resource Center3on August 15, 2022, and plotted smoothed 7-day moving averages of total daily tests and test positivity. With COVID-19 Citizen Science Study data, we fit mixed logistic models with a random intercept for each participant and fixed effects for time and demographic characteristics. We analyzed data using Stata statistical software version 17 (StataCorp), using 2-sided tests with α = .05 for hypothesis testing.
ResultsOf 102?591 US participants enrolled, 18?642 (18%) reported completing at least 1 SARS-CoV-2 test from March 16, 2022, to August 15, 2022; 18?546 participants also had complete demographic information. Most were female (12?568 participants [67.8%]) and non-Hispanic White (15?231 participants [82.1%]), with a mean (SD) age of 55 (14) years. During this time period, the proportion of SARS-CoV-2 testing conducted at home increased from approximately 60% to more than 80% (Figure) (P < .001 for time trend). The percentage test positivity on home tests was similar to officially reported tests3through June, but then started to diverge with lower positivity in home tests (P < .001 for interaction of official test positivity and time). Female, non-Hispanic White, younger, and higher social status participants were more likely to test at home. Male participants and young adults were more likely to test positive on home tests (Table).
DiscussionIn this cohort study, we found home testing to be increasingly common through spring and into summer 2022, most recently comprising more than 80% of all SARS-CoV-2 testing reported. Home test positivity appears to track closely with national data from reported tests, but these trends are starting to diverge. Home testing patterns differ by demographic subgroup, as previously shown,4perhaps because of differential COVID-19 worry or availability and cost of test kits. Our study has limitations. Home testing may be conducted repeatedly during an illness episode, may be less common in the US population than in our engaged participants, and may sometimes be officially reported despite being conducted at home (eg, via employers), all of which could bias our estimates of test positivity and the proportion of tests that are unreported.
Our findings confirm common wisdom5,6that official COVID-19 case counts increasingly underestimate the number of people who test positive and vastly underestimate the number of true infections. The percentage test positivity in officially reported tests appears to reflect home test positivity, though these trends may be diverging.