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Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study.
Chapman, Lloyd A C; Kushel, Margot; Cox, Sarah N; Scarborough, Ashley; Cawley, Caroline; Nguyen, Trang Q; Rodriguez-Barraquer, Isabel; Greenhouse, Bryan; Imbert, Elizabeth; Lo, Nathan C.
  • Chapman LAC; Department of Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA. Lloyd.Chapman@ucsf.edu.
  • Kushel M; Center for Vulnerable Populations, Zuckerberg San Francisco General Hospital and Trauma Center, University of California, San Francisco, San Francisco, CA, USA.
  • Cox SN; San Francisco Department of Public Health, San Francisco, CA, USA.
  • Scarborough A; San Francisco Department of Public Health, San Francisco, CA, USA.
  • Cawley C; Department of Emergency Medicine, University of California, San Francisco, San Francisco, CA, USA.
  • Nguyen TQ; San Francisco Department of Public Health, San Francisco, CA, USA.
  • Rodriguez-Barraquer I; Department of Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA.
  • Greenhouse B; Department of Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA.
  • Imbert E; Division of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco, CA, USA.
  • Lo NC; Department of Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA. Nathan.Lo@ucsf.edu.
BMC Med ; 19(1): 116, 2021 05 07.
Article in English | MEDLINE | ID: covidwho-1219073
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ABSTRACT

BACKGROUND:

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.

METHODS:

We developed a microsimulation model of SARS-CoV-2 transmission in a homeless shelter and calibrated it to data from cross-sectional polymerase chain reaction (PCR) surveys conducted during COVID-19 outbreaks in five homeless shelters in three US cities from March 28 to April 10, 2020. We estimated the probability of averting a COVID-19 outbreak when an exposed individual is introduced into a representative homeless shelter of 250 residents and 50 staff over 30 days under different infection control strategies, including daily symptom-based screening, twice-weekly PCR testing, and universal mask wearing.

RESULTS:

The proportion of PCR-positive residents and staff at the shelters with observed outbreaks ranged from 2.6 to 51.6%, which translated to the basic reproduction number (R0) estimates of 2.9-6.2. With moderate community incidence (~ 30 confirmed cases/1,000,000 people/day), 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 respectively 0.35, 0.13, and 0.04 for daily symptom-based screening; 0.53, 0.20, and 0.09 for twice-weekly PCR testing; 0.62, 0.27, and 0.08 for universal masking; and 0.74, 0.42, and 0.19 for these strategies in combination. The probability of averting an outbreak diminished with higher transmissibility (R0) within the simulated shelter and increasing incidence in the local community.

CONCLUSIONS:

In high-risk homeless shelter environments and locations with high community incidence of COVID-19, even intensive infection control strategies (incorporating daily symptom screening, frequent PCR testing, and universal mask wearing) are unlikely to prevent outbreaks, suggesting a need for non-congregate housing arrangements for people experiencing homelessness. In lower-risk environments, combined interventions should be employed to reduce outbreak risk.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Ill-Housed Persons / Disease Outbreaks / Infection Control / COVID-19 Nucleic Acid Testing / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America Language: English Journal: BMC Med Journal subject: Medicine Year: 2021 Document Type: Article Affiliation country: S12916-021-01965-y

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Ill-Housed Persons / Disease Outbreaks / Infection Control / COVID-19 Nucleic Acid Testing / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America Language: English Journal: BMC Med Journal subject: Medicine Year: 2021 Document Type: Article Affiliation country: S12916-021-01965-y