Incidence of SARS-CoV-2 infection and associated risk factors among staff and residents at homeless shelters in King County, Washington: an active surveillance study (preprint)

Homeless shelter residents and staff may be at higher risk of SARS-CoV-2 infection. However, SARS-CoV-2 infection estimates in this population have been reliant on cross-sectional or outbreak investigation data. We conducted routine surveillance and outbreak testing in 23 homeless shelters in King County, Washington to estimate the occurrence of laboratory-confirmed SARS-CoV-2 infection and risk factors during 1/1/2020-5/31/2021. Symptom surveys and nasal swabs were collected for SARS-CoV-2 testing by RT-PCR for residents aged 3 months and older and staff. We collected 12,915 specimens from 2,930 unique participants. We identified 4.74 (95% CI 4.00-5.58) SARS-CoV-2 infections per 100 individuals (residents: 4.96, 95% CI 4.12-5.91; staff: 3.86, 95% CI 2.43-5.79). Most infections were asymptomatic at time of detection (74%) and detected during routine surveillance (73%). Outbreak testing yielded higher test positivity compared to routine surveillance (2.7% vs. 0.9%). Among those infected, residents were less likely to report symptoms than staff. Participants who were vaccinated against seasonal influenza and were current smokers had lower odds of having an infection detected. Active surveillance that includes SARS-CoV-2 testing of all persons is essential in ascertaining the true burden of SARS-CoV-2 infections among residents and staff of congregate settings.

Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study (preprint)

Background: Multiple COVID-19 outbreaks have occurred in homeless shelters across the US, highlighting an urgent need to identify the most effective infection control strategy to prevent future outbreaks. Objective: To estimate the probability of averting outbreaks in homeless shelters under different infection control strategies. Design: Microsimulation model of COVID-19 transmission in a representative homeless shelter over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly polymerase-chain-reaction (PCR) testing and universal mask wearing. Setting: A shelter of 250 residents and 50 staff. Patients: Residents and staff of homeless shelters in the US. Model calibrated to data from cross-sectional PCR surveys during COVID-19 outbreaks in five shelters in three US cities. Measurements: Probability of averting a COVID-19 outbreak ([≥]3 infections in 14 days). Results: Basic reproduction number (R0) estimates for the observed outbreaks ranged from 2.9 to 6.2. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing transmission intensity in the local community. With moderate transmission intensity in the local community, the estimated probabilities of averting an outbreak in a low-risk (R0=1.5), moderate-risk (R0=2.9), and high-risk (R0=6.2) shelter were: 0.33, 0.11 and 0.03 for daily symptom-based screening; 0.52, 0.27, and 0.04 for twice-weekly PCR testing; 0.47, 0.20 and 0.06 for universal masking; and 0.68, 0.40 and 0.08 for these strategies combined. Limitations: R0 values calibrated to reported outbreaks may be higher than for average shelter due to smaller outbreaks going unreported. Conclusion: In high-risk homeless shelter environments and locations with high community incidence of COVID-19 most infection control strategies are unlikely to prevent outbreaks. In lower-risk environments, combined interventions should be adopted to reduce outbreak risk. Primary Funding Source: University of California, San Francisco; UCSF Benioff Homelessness and Housing Initiative.

How Efficacious Must a COVID-19 Coronavirus Vaccine be to Prevent or Stop an Epidemic by Itself (preprint)

Background: Given the continuing coronavirus disease 2019 (COVID-19) pandemic and much of the U.S. implementing social distancing due to the lack of alternatives, there has been a push to develop a vaccine to eliminate the need for social distancing. Methods: In 2020, we developed a computational model of the U.S. simulating the spread of COVID-19 coronavirus and vaccination. Results: Simulation experiments revealed that when vaccine efficacy exceeded 70%, coverage exceeded 60%, and vaccination occurred on day 1, the attack rate dropped to 22% with daily cases not exceeding 3.2 million (reproductive rate, R0, 2.5). When R0 was 3.5, the attack rate dropped to 41% with daily cases not exceeding 14.4 million. Increasing coverage to 75% when vaccination occurred by day 90 resulted in 5% attack rate and daily cases not exceeding 258,029when R0 was 2.5 and a 26% attack rate and maximum daily cases of 22.6 million when R0 was 3.5. When vaccination did not occur until day 180, coverage (i.e., those vaccinated plus those otherwise immune) had to reach 100%. A vaccine with an efficacy between 40% and 70% could still obviate the need for other measures under certain circumstances such as much higher, and in some cases, potentially unachievable, vaccination coverages. Conclusion: Our study found that to either prevent or largely extinguish an epidemic without any other measures (e.g., social distancing), the vaccine has to have an efficacy of at least 70%.