Additional file 1 of Comparison of infection control strategies to reduce COVID-19 outbreaks in homeless shelters in the United States: a simulation study
Creators: name: Chapman, Lloyd A. C.
name: Kushel, Margot
name: Cox, Sarah N.
name: Scarborough, Ashley
name: Cawley, Caroline
name: Nguyen, Trang Q.
name: Rodriguez-Barraquer, Isabel
name: Greenhouse, Bryan
name: Imbert, Elizabeth
name: Lo, Nathan C.
Publisher: name: figshare
Year: 2021
Subjects: subject: Medicine
subject: Biotechnology
subject: Ecology
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: Cancer
subject: Science Policy
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: FOS: Health sciences
subject: Computational Biology

description: Additional file 1: Supplementary methods and results. Details of the model and model calibration. Table S1. Definition of states in the transmission model. Table S2. Risk of clinical symptoms and hospitalization by age group and co-morbidity status. Table S3. Numbers of PCR-positive individuals by day of test result and daily new symptom onsets in San Francisco shelter March 28–April 10, 2020. Table S4. Numbers of residents and staff PCR tested and PCR positive at three shelters in Seattle during two testing events March 30–April 1, 2020 and April 7–8, 2020. Table S5: Input parameters for microsimulation of COVID-19 transmission in homeless shelters. Table S6. Different intervention strategies tested. Table S7. Estimated epidemiologic parameters based on observed outbreak data from homeless shelters in Seattle, Boston and San Francisco. Table S8. Estimated cumulative infection incidence at the end of the PCR testing period in homeless shelters in Seattle, Boston and San Francisco. Table S9. Probability of averting an outbreak over a 30-day period in a generalized homeless shelter with simulated infection control strategies for different background infection rates in the community outside the shelter. Table S10. Reductions in the total number of infections and symptomatic cases over a 30-day period in a generalized homeless shelter with simulated infection control strategies for different background infection rates in the community outside the shelter. Table S11. Numbers of PCR tests used under each infection control strategy. Figure S1. Structure of stochastic individual-level susceptible-exposed-infectious-recovered ( S $$ \Big(\mathcal{S} $$ - E $$ \mathcal{E} $$ - I $$ \mathcal{I} $$ - R $$ \mathcal{R} $$ ) model of COVID-19 transmission in homeless shelter. Figure S2. Daily numbers of residents by risk group present in the San Francisco shelter March 29–April 10, 2020. Figure S3. Distribution of duration of detectable viral load from start of late infectious stage. Figure S4. Calibration of microsimulation to observed PCR testing data from outbreaks in homeless shelters in Seattle, Boston and San Francisco. Figure S5. Calibration of microsimulation to additional data from San Francisco shelter outbreak. Figure S6. Outbreak size distributions 30 days after introduction of infection in a generalized homeless shelter under different infection control strategies for R0 = 1.5 (low-risk setting). Figure S7. Outbreak size distributions 30 days after introduction of infection in a generalized homeless shelter under different infection control strategies for R0 = 2.9 (Seattle). Figure S8. Outbreak size distributions 30 days after introduction of infection in a generalized homeless shelter under different infection control strategies for R0 = 6.2 (San Francisco). Figure S9. Spider diagrams showing the sensitivity of the estimated probability of averting an outbreak to variation in key natural history and intervention parameters for different R0 values. Figure S10. Posterior distributions and pairwise correlation plots for calibrated model parameters – R0, E0 and T – for (A)-(C) Seattle shelters A–C, (D) Boston shelter and (E) San Francisco shelter.