Dynamics of Respiratory Infectious Diseases in Incarcerated and Free-Living Populations: A Simulation Modeling Study.

BACKGROUND: Historically, correctional facilities have had large outbreaks of respiratory infectious diseases like COVID-19. Hence, importation and exportation of such diseases from correctional facilities raises substantial concern. METHODS: We developed a stochastic simulation model of transmission of respiratory infectious diseases within and between correctional facilities and the community. We investigated the infection dynamics, key governing factors, and relative importance of different infection routes (e.g., incarcerations and releases versus correctional staff). We also developed machine-learning meta-models of the simulation model, which allowed us to examine how our findings depended on different disease, correctional facility, and community characteristics. RESULTS: We find a magnification-reflection dynamic: a small outbreak in the community can cause a larger outbreak in the correction facility, which can then cause a second, larger outbreak in the community. This dynamic is strongest when community size is relatively small as compared with the size of the correctional population, the initial community R-effective is near 1, and initial prevalence of immunity in the correctional population is low. The timing of the correctional magnification and community reflection peaks in infection prevalence are primarily governed by the initial R-effective for each setting. Because the release rates from prisons are low, our model suggests correctional staff may be a more important infection entry route into prisons than incarcerations and releases; in jails, where incarceration and release rates are much higher, our model suggests the opposite. CONCLUSIONS: We find that across many combinations of respiratory pathogens, correctional settings, and communities, there can be substantial magnification-reflection dynamics, which are governed by several key factors. Our goal was to derive theoretical insights relevant to many contexts; our findings should be interpreted accordingly. HIGHLIGHTS: We find a magnification-reflection dynamic: a small outbreak in a community can cause a larger outbreak in a correctional facility, which can then cause a second, larger outbreak in the community.For public health decision makers considering contexts most susceptible to this dynamic, we find that the dynamic is strongest when the community size is relatively small, initial community R-effective is near 1, and the initial prevalence of immunity in the correctional population is low; the timing of the correctional magnification and community reflection peaks in infection prevalence are primarily governed by the initial R-effective for each setting.We find that correctional staff may be a more important infection entry route into prisons than incarcerations and releases; however, for jails, the relative importance of the entry routes may be reversed.For modelers, we combine simulation modeling, machine-learning meta-modeling, and interpretable machine learning to examine how our findings depend on different disease, correctional facility, and community characteristics; we find they are generally robust.

Effectiveness of Coronavirus Disease 2019 (COVID-19) Vaccines Among Incarcerated People in California State Prisons: Retrospective Cohort Study.

BACKGROUND: Prisons and jails are high-risk settings for coronavirus disease 2019 (COVID-19). Vaccines may substantially reduce these risks, but evidence is needed on COVID-19 vaccine effectiveness for incarcerated people, who are confined in large, risky congregate settings. METHODS: We conducted a retrospective cohort study to estimate effectiveness of messenger RNA (mRNA) vaccines, BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna), against confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among incarcerated people in California prisons from 22 December 2020 through 1 March 2021. The California Department of Corrections and Rehabilitation provided daily data for all prison residents including demographic, clinical, and carceral characteristics, as well as COVID-19 testing, vaccination, and outcomes. We estimated vaccine effectiveness using multivariable Cox models with time-varying covariates, adjusted for resident characteristics and infection rates across prisons. RESULTS: Among 60 707 cohort members, 49% received at least 1 BNT162b2 or mRNA-1273 dose during the study period. Estimated vaccine effectiveness was 74% (95% confidence interval [CI], 64%-82%) from day 14 after first dose until receipt of second dose and 97% (95% CI, 88%-99%) from day 14 after second dose. Effectiveness was similar among the subset of residents who were medically vulnerable: 74% (95% CI, 62%-82%) and 92% (95% CI, 74%-98%) from 14 days after first and second doses, respectively. CONCLUSIONS: Consistent with results from randomized trials and observational studies in other populations, mRNA vaccines were highly effective in preventing SARS-CoV-2 infections among incarcerated people. Prioritizing incarcerated people for vaccination, redoubling efforts to boost vaccination, and continuing other ongoing mitigation practices are essential in preventing COVID-19 in this disproportionately affected population.

Dependence of COVID-19 Policies on End-of-Year Holiday Contacts in Mexico City Metropolitan Area: A Modeling Study.

Background. Mexico City Metropolitan Area (MCMA) has the largest number of COVID-19 (coronavirus disease 2019) cases in Mexico and is at risk of exceeding its hospital capacity in early 2021. Methods. We used the Stanford-CIDE Coronavirus Simulation Model (SC-COSMO), a dynamic transmission model of COVID-19, to evaluate the effect of policies considering increased contacts during the end-of-year holidays, intensification of physical distancing, and school reopening on projected confirmed cases and deaths, hospital demand, and hospital capacity exceedance. Model parameters were derived from primary data, literature, and calibrated. Results. Following high levels of holiday contacts even with no in-person schooling, MCMA will have 0.9 million (95% prediction interval 0.3-1.6) additional COVID-19 cases between December 7, 2020, and March 7, 2021, and hospitalizations will peak at 26,000 (8,300-54,500) on January 25, 2021, with a 97% chance of exceeding COVID-19-specific capacity (9,667 beds). If MCMA were to control holiday contacts, the city could reopen in-person schools, provided they increase physical distancing with 0.5 million (0.2-0.9) additional cases and hospitalizations peaking at 12,000 (3,700-27,000) on January 19, 2021 (60% chance of exceedance). Conclusion. MCMA must increase COVID-19 hospital capacity under all scenarios considered. MCMA's ability to reopen schools in early 2021 depends on sustaining physical distancing and on controlling contacts during the end-of-year holiday.

The Household Secondary Attack Rate of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): A Rapid Review.

BACKGROUND: Although much of the public health effort to combat coronavirus disease 2019 (COVID-19) has focused on disease control strategies in public settings, transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within households remains an important problem. The nature and determinants of household transmission are poorly understood. METHODS: To address this gap, we gathered and analyzed data from 22 published and prepublished studies from 10 countries (20 291 household contacts) that were available through 2 September 2020. Our goal was to combine estimates of the SARS-CoV-2 household secondary attack rate (SAR) and to explore variation in estimates of the household SAR. RESULTS: The overall pooled random-effects estimate of the household SAR was 17.1% (95% confidence interval [CI], 13.7-21.2%). In study-level, random-effects meta-regressions stratified by testing frequency (1 test, 2 tests, >2 tests), SAR estimates were 9.2% (95% CI, 6.7-12.3%), 17.5% (95% CI, 13.9-21.8%), and 21.3% (95% CI, 13.8-31.3%), respectively. Household SARs tended to be higher among older adult contacts and among contacts of symptomatic cases. CONCLUSIONS: These findings suggest that SARs reported using a single follow-up test may be underestimated, and that testing household contacts of COVID-19 cases on multiple occasions may increase the yield for identifying secondary cases.

Outbreaks of COVID-19 variants in US prisons: a mathematical modelling analysis of vaccination and reopening policies.

BACKGROUND: Residents of prisons have experienced disproportionate COVID-19-related health harms. To control outbreaks, many prisons in the USA restricted in-person activities, which are now resuming even as viral variants proliferate. This study aims to use mathematical modelling to assess the risks and harms of COVID-19 outbreaks in prisons under a range of policies, including resumption of activities. METHODS: We obtained daily resident-level data for all California state prisons from Jan 1, 2020, to May 15, 2021, describing prison layouts, housing status, sociodemographic and health characteristics, participation in activities, and COVID-19 testing, infection, and vaccination status. We developed a transmission-dynamic stochastic microsimulation parameterised by the California data and published literature. After an initial infection is introduced to a prison, the model evaluates the effect of various policy scenarios on infections and hospitalisations over 200 days. Scenarios vary by vaccine coverage, baseline immunity (0%, 25%, or 50%), resumption of activities, and use of non-pharmaceutical interventions (NPIs) that reduce transmission by 75%. We simulated five prison types that differ by residential layout and demographics, and estimated outcomes with and without repeated infection introductions over the 200 days. FINDINGS: If a viral variant is introduced into a prison that has resumed pre-2020 contact levels, has moderate vaccine coverage (ranging from 36% to 76% among residents, dependent on age, with 40% coverage for staff), and has no baseline immunity, 23-74% of residents are expected to be infected over 200 days. High vaccination coverage (90%) coupled with NPIs reduces cumulative infections to 2-54%. Even in prisons with low room occupancies (ie, no more than two occupants) and low levels of cumulative infections (ie, <10%), hospitalisation risks are substantial when these prisons house medically vulnerable populations. Risks of large outbreaks (>20% of residents infected) are substantially higher if infections are repeatedly introduced. INTERPRETATION: Balancing benefits of resuming activities against risks of outbreaks presents challenging trade-offs. After achieving high vaccine coverage, prisons with mostly one-to-two-person cells that have higher baseline immunity from previous outbreaks can resume in-person activities with low risk of a widespread new outbreak, provided they maintain widespread NPIs, continue testing, and take measures to protect the medically vulnerable. FUNDING: Horowitz Family Foundation, National Institute on Drug Abuse, Centers for Disease Control and Prevention, National Science Foundation, Open Society Foundation, Advanced Micro Devices.

COVID-19 in the California State Prison System: an Observational Study of Decarceration, Ongoing Risks, and Risk Factors.

BACKGROUND: Correctional institutions nationwide are seeking to mitigate COVID-19-related risks. OBJECTIVE: To quantify changes to California's prison population since the pandemic began and identify risk factors for COVID-19 infection. DESIGN: For California state prisons (March 1-October 10, 2020), we described residents' demographic characteristics, health status, COVID-19 risk scores, room occupancy, and labor participation. We used Cox proportional hazard models to estimate the association between rates of COVID-19 infection and room occupancy and out-of-room labor, respectively. PARTICIPANTS: Residents of California state prisons. MAIN MEASURES: Changes in the incarcerated population's size, composition, housing, and activities. For the risk factor analysis, the exposure variables were room type (cells vs. dormitories) and labor participation (any room occupant participating in the prior 2 weeks) and the outcome variable was incident COVID-19 case rates. KEY RESULTS: The incarcerated population decreased 19.1% (119,401 to 96,623) during the study period. On October 10, 2020, 11.5% of residents were aged ≥60, 18.3% had high COVID-19 risk scores, 31.0% participated in out-of-room labor, and 14.8% lived in rooms with ≥10 occupants. Nearly 40% of residents with high COVID-19 risk scores lived in dormitories. In 9 prisons with major outbreaks (6,928 rooms; 21,750 residents), dormitory residents had higher infection rates than cell residents (adjusted hazard ratio [AHR], 2.51 95% CI, 2.25-2.80) and residents of rooms with labor participation had higher rates than residents of other rooms (AHR, 1.56; 95% CI, 1.39-1.74). CONCLUSION: Despite reductions in room occupancy and mixing, California prisons still house many medically vulnerable residents in risky settings. Reducing risks further requires a combination of strategies, including rehousing, decarceration, and vaccination.