Layered Screening and Contact-Limiting Interventions Are Necessary to Reduce SARS-Cov-2 Outbreak Risks in Large Urban Jails

Abstract

Highly transmissible infections with short serial intervals, such as SARS-Cov-2 and influenza, can quickly overwhelm healthcare resources in institutional settings such as jails. We assessed the impact of intake screening measures on the risk of SARS-CoV-2 outbreaks in this setting. We identified which elements of the intake process created the largest reductions in caseload. We implemented an individual-based simulation representative of SARS-Cov-2 transmission in a large urban jail utilizing testing at entry, quarantine, and post-quarantine testing to protect its general population from mass infection. We tracked the caseload under each scenario and quantified the impact of screening steps by varying quarantine duration, removing testing, and using a range of test sensitivities. We repeated the simulations under a range of transmissibility and community prevalence levels to evaluate the sensitivity of our results. We found that brief quarantine of newly incarcerated individuals separate from the existing population of the jail to permit pre-quarantine and end-of-quarantine tests reduced SARS-CoV-2 caseload 30-70% depending on test sensitivity. These results were robust to variation in the transmissibility. Further quarantine (up to 14 days) on average created only a 5% further reduction in caseload. A multilayered intake process is necessary to limit the spread of highly transmissible pathogens with short serial intervals. The pre-symptomatic phase means that no single strategy can be effective. We also show that shorter durations of quarantine combined with testing can be nearly as effective at preventing spread as longer-duration quarantine up to 14 days.

Figure 1.

Flow diagram of the intake screening process for newly incarcerated people. This diagram represents the sequence of screening steps undertaken between an individual’s initial detention and his or her entry into the general population of the jail. Boxes in the figure represent stages of the intake screening process, conditional on an individual’s infection state as measured by viral testing and symptomatic screening. Circles represent specific screening steps used. Solid lines indicate the most common transitions in the model, whereas dashed lines indicate a subset of transitions between states experienced only by individuals who tested positive for SARS-CoV-2.

Figure 2.

Expected number of in-jail infections for varying sensitivities of intake and end-of-quarantine testing. Rows indicate different rates of within-facility transmissibility, increasing from low-transmissibility (R₀ = 1.1) to high transmission (R₀ = 5) from top to bottom. Columns indicate different levels of prevalence among individuals admitted to the facility, showing both the low-prevalence (1%, left) and high-prevalence (10%, right) scenarios. Points are a subsample of incidence from individual simulation replicates, and lines in each panel show the association between quarantine duration (2, 4, 7, or 14 days) and the expected number of within-facility infections (y axis). Solid lines show the relationship between quarantine duration and incidence under a control scenario in which there is no intake or end-of-quarantine testing. Dashed and dotted lines indicate different sensitivities of both the intake and end-of-quarantine test.

Figure 3.

Expected number of in-jail infections with only intake testing and no end-of-quarantine testing. Rows indicate different rates of within-facility transmissibility, increasing from low transmissibility (R₀ = 1.1) to high transmission (R₀ = 5) from top to bottom. Columns indicate different levels of prevalence among individuals admitted to the facility, with low-prevalence (1%, left) and high-prevalence (10%, right) scenarios. Points indicate (jittered) incidence from a subsample of individual simulation replicates, and lines in each panel show the association between quarantine duration (2, 4, 7, or 14 days) and the expected number of within-facility infections (y axis). Solid lines show the relationship between quarantine duration and incidence under a control scenario in which there is no intake or end-of-quarantine testing. Dashed and dotted lines indicate different sensitivities of the intake test.

Figure 4.

Expected number of in-jail infections with only end-of-quarantine testing and no intake testing. Rows indicate different rates of within-facility transmissibility, increasing from low transmissibility (R₀ = 1.1) to high transmission (R₀ = 5) from top to bottom. Columns indicate different levels of prevalence among individuals admitted to the facility, with low-prevalence (1%, left) and high-prevalence (10%, right) scenarios. Points indicate (jittered) outcomes from subsamples of individual simulation replicates, and lines in each panel show the association between quarantine duration (2, 4, 7, or 14 days) and the expected number of within-facility infections (y axis). Solid lines show the relationship between quarantine duration and incidence under a control scenario in which there is no intake or end-of-quarantine testing. Dashed and dotted lines indicate different sensitivities of the end-of-quarantine test.