Postacute sequelae of SARS-CoV-2 infection, commonly known as long COVID, is estimated to affect 10% to 80% of COVID-19 survivors. We examined the prevalence and predictors of long COVID from a sample of 1,338 COVID-19 cases among university members in Washington, DC, USA, during July 2021‒March 2022. Cases were followed up after 30 days of the initial positive result with confidential electronic surveys including questions about long COVID. The prevalence of long COVID was 36%. Long COVID was more prevalent among those who had underlying conditions, who were not fully vaccinated, who were female, who were former/current smokers, who experienced acute COVID-19 symptoms, who reported higher symptom counts, who sought medical care, or who received antibody treatment. Understanding long COVID among university members is imperative to support persons who have ongoing symptoms and to strengthen existing services or make referrals to other services, such as mental health, exercise programs, or long-term health studies.

BACKGROUND COVID-19 isolation recommendations have evolved over the course of the pandemic. Rapid antigen tests (RATs) are a tool that can be used to shorten isolation periods. OBJECTIVE The purpose of this analysis is to report on the experience of implementing RAT policies, examine the number of days that isolation was reduced via RAT testing, determine the factors that predicted uploading a RAT, and determine RAT positivity rates to illustrate the utility of using RATs to end isolation. METHODS In this study, 880 individuals in COVID-19 isolation at a university in Washington, DC uploaded 887 RATs between February 21 and April 14, 2022. Daily positivity rates were calculated and multiple logistic regression analysis examined the odds of uploading a RAT by campus residential living status (on/off-campus), student/employee designation, age, and days in isolation. RESULTS Seventy-six percent (669/880) of individuals in isolation uploaded a RAT during the study period. Overall, 38.6% (342/887) of uploaded RATs were positive. Positivity rates for RATs were 45.6% (118/259) at day 5, 45.4% (55/121) at day 6, 47.1% (99/210) at day 7, and 11.1% (7/63) at day 10 or above. Adjusted logistic regression modeling indicated cases living on-campus had increased odds of uploading a RAT (OR 2.54, 95% CI 1.64-3.92), whereas primary student affiliation (OR 0.29, 95% CI 0.12-0.69), and days in isolation (OR 0.45, 95% CI 0.39-0.52) had decreased odds of uploading a RAT. Of the 545 cases with a negative RAT, 477 were cleared prior to day 10 of their isolation due to a lack of symptoms and timely submission, resulting in a total of 1,547 days of lost productivity saved compared to all being in isolation for 10 days. CONCLUSIONS Future isolation policies should be guided by similar protocols and research to reduce the spread of COVID-19 and minimize lost productivity and disruption to individuals’ lives.

Background COVID-19 isolation recommendations have evolved over the course of the pandemic. Initially, the US Centers for Disease Control and Prevention required 10 days of isolation after a positive test result. In December 2021, this was reduced to a minimum of 5 days with symptom improvement, followed by 5 days of mask wearing. As a result, several institutions of higher education, including the George Washington University, required persons testing positive for COVID-19 to either submit a negative rapid antigen test (RAT) with symptom resolution to leave isolation after 5 days or to maintain a 10-day isolation period in the absence of a negative RAT and the presence of continued symptoms. RATs are tools that can be used both to shorten isolation periods and to ensure that persons testing positive for COVID-19 remain in isolation if infectious. Objective The purpose of this analysis is to report on the experience of implementing RAT policies, examine the number of days that isolation was reduced via RAT testing, determine the factors that predicted uploading a RAT, and determine RAT positivity percentages to illustrate the utility of using RATs to end isolation. Methods In this study, 880 individuals in COVID-19 isolation at a university in Washington, DC, uploaded 887 RATs between February 21 and April 14, 2022. Daily positivity percentages were calculated, and multiple logistic regression analyses examined the odds of uploading a RAT by campus residential living status (ie, on or off campus), student or employee designation, age, and days in isolation. Results A total of 76% (669/880) of individuals in isolation uploaded a RAT during the study period. Overall, 38.6% (342/887) of uploaded RATs were positive. Uploaded RATs were positive 45.6% (118/259) of the time on day 5; 45.4% (55/121) on day 6; 47.1% (99/210) on day 7; and 11.1% (7/63) on day 10 or beyond. Adjusted logistic regression modeling indicated cases living on campus had increased odds of uploading a RAT (odds ratio [OR] 2.54, 95% CI 1.64-3.92), whereas primary student affiliation (OR 0.29, 95% CI 0.12-0.69) and days in isolation (OR 0.45, 95% CI 0.39-0.52) had decreased odds of uploading a RAT. Of the 545 cases with a negative RAT, 477 were cleared prior to day 10 of their isolation due to lack of symptoms and timely submission, resulting in a total of 1547 days of lost productivity saved compared to all being in isolation for 10 days. Conclusions RATs are beneficial, as they can support a decision to release individuals from isolation when they have recovered and maintain isolation for people who may still be infectious. Future isolation policies should be guided by similar protocols and research to reduce the spread of COVID-19 and minimize lost productivity and disruption to individuals’ lives.