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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.

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%

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.