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Purpose Early COVID-19 mitigation relied on people staying home except for essential trips. The ability to stay home may differ by sociodemographic factors. We analyzed how factors related to social vulnerability impact a community's ability to stay home during a stay-at-home order. Methods Using generalized, linear mixed models stratified by stay-at-home order (mandatory or not mandatory), we analyzed county-level stay-at-home behavior (inferred from mobile devices) during a period when a majority of United States counties had stay-at-home orders (April 7–April 20, 2020) with the Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI). Results Counties with higher percentages of single-parent households, mobile homes, and persons with lower educational attainment were associated with lower stay-at-home behavior compared with counties with lower respective percentages. Counties with higher unemployment, higher percentages of limited-English-language speakers, and more multi-unit housing were associated with increases in stay-at-home behavior compared with counties with lower respective percentages. Stronger effects were found in counties with mandatory orders. Conclusions Sociodemographic factors impact a community's ability to stay home during COVID-19 stay-at-home orders. Communities with higher social vulnerability may have more essential workers without work-from-home options or fewer resources to stay home for extended periods, which may increase risk for COVID-19. Results are useful for tailoring messaging, COVID-19 vaccine delivery, and public health responses to future outbreaks.

Consumption of unpasteurised milk in the United States has presented a public health challenge for decades because of the increased risk of pathogen transmission causing illness outbreaks. We analysed Foodborne Disease Outbreak Surveillance System data to characterise unpasteurised milk outbreaks. Using Poisson and negative binomial regression, we compared the number of outbreaks and outbreak-associated illnesses between jurisdictions grouped by legal status of unpasteurised milk sale based on a May 2019 survey of state laws. During 2013–2018, 75 outbreaks with 675 illnesses occurred that were linked to unpasteurised milk; of these, 325 illnesses (48%) were among people aged 0–19 years. Of 74 single-state outbreaks, 58 (78%) occurred in states where the sale of unpasteurised milk was expressly allowed. Compared with jurisdictions where retail sales were prohibited (n = 24), those where sales were expressly allowed (n = 27) were estimated to have 3.2 (95% CI 1.4–7.6) times greater number of outbreaks; of these, jurisdictions where sale was allowed in retail stores (n = 14) had 3.6 (95% CI 1.3–9.6) times greater number of outbreaks compared with those where sale was allowed on-farm only (n = 13). This study supports findings of previously published reports indicating that state laws resulting in increased availability of unpasteurised milk are associated with more outbreak-associated illnesses and outbreaks.

CDC recommends a combination of evidence-based strategies to reduce transmission of SARS-CoV-2, the virus that causes COVID-19 (1). Because the virus is transmitted predominantly by inhaling respiratory droplets from infected persons, universal mask use can help reduce transmission (1). Starting in April, 39 states and the District of Columbia (DC) issued mask mandates in 2020. Reducing person-to-person interactions by avoiding nonessential shared spaces, such as restaurants, where interactions are typically unmasked and physical distancing (≥6 ft) is difficult to maintain, can also decrease transmission (2). In March and April 2020, 49 states and DC prohibited any on-premises dining at restaurants, but by mid-June, all states and DC had lifted these restrictions. To examine the association of state-issued mask mandates and allowing on-premises restaurant dining with COVID-19 cases and deaths during March 1-December 31, 2020, county-level data on mask mandates and restaurant reopenings were compared with county-level changes in COVID-19 case and death growth rates relative to the mandate implementation and reopening dates. Mask mandates were associated with decreases in daily COVID-19 case and death growth rates 1-20, 21-40, 41-60, 61-80, and 81-100 days after implementation. Allowing any on-premises dining at restaurants was associated with increases in daily COVID-19 case growth rates 41-60, 61-80, and 81-100 days after reopening, and increases in daily COVID-19 death growth rates 61-80 and 81-100 days after reopening. Implementing mask mandates was associated with reduced SARS-CoV-2 transmission, whereas reopening restaurants for on-premises dining was associated with increased transmission. Policies that require universal mask use and restrict any on-premises restaurant dining are important components of a comprehensive strategy to reduce exposure to and transmission of SARS-CoV-2 (1). Such efforts are increasingly important given the emergence of highly transmissible SARS-CoV-2 variants in the United States (3,4).

Trends in the percentages of the US population covered by state-issued nonpharmaceutical interventions (NPIs), including restaurant and bar restrictions, stay-at-home orders, gathering limits, and mask mandates, were examined by using county-specific data sets on state-issued orders for NPIs from March 1, 2020, to August 15, 2021. Most of the population was covered by multiple NPIs early in the pandemic. Most state-issued orders were lifted or relaxed as COVID-19 cases decreased during summer 2020. Few states reimplemented strict NPIs during later surges in US COVID-19 cases over the winter of 2020-2021. The exceptions were mask mandates, which covered about 80% of the population between August 2020 and February 2021, and the most restrictive gathering limits, which covered a maximum of 66% of the population in early 2020 and 68% of the population in winter 2020-2021. Most NPIs were lifted by the end of the analysis period.

Objectives: By the end of 2020, 38 states and the District of Columbia had issued requirements that people wear face masks when in public settings to counter SARS-CoV-2 transmission. To examine the role face mask mandates played in economic recovery, we analyzed the interactive effect of having a state face mask mandate in place on county-level consumer spending after state reopening, adjusting for county rates of new COVID-19 cases and deaths, time trends, and county-specific effects. Methods: We collected county-specific data from state executive orders, consumer spending data from the Opportunity Insights Economic Tracker, and COVID-19 case and death data from the Centers for Disease Control and Prevention COVID-19 tracker. Using an event study approach, we compared county-level changes in consumer spending before and after state-issued closure orders were lifted and assessed the interactive effect of state-issued face mask mandates. Results: The lifting of state-issued closures was associated with an average increase in consumer spending across all counties studied within 1 month. However, the increase was 1.2-1.7 percentage points higher in counties with a state face mask mandate in place than in counties without a state face mask mandate. Conclusions: In addition to their public health benefits, face mask mandates may have assisted economic recovery during the COVID-19 pandemic, suggesting they are a strong public health strategy for policy makers to consider now and for potential future pandemics arising from airborne viruses.

ImportanceSome US states have issued COVID-19 vaccine mandates; however, the association of these mandates with vaccination rates remains unknown.ObjectiveTo examine the association between announcing state-issued COVID-19 vaccine mandates that did not provide a test-out option for workers and the vaccine administration rates in terms of state-level first-dose vaccine administration and series completion coverage.Design, Setting, and ParticipantsThis cross-sectional study used publicly available, state-level aggregated panel data to fit linear regression models with 2-way fixed effects (state and time) estimating vaccine coverage changes 8 weeks before and 8 weeks after a state-issued COVID-19 vaccine mandate was announced. Mandates were announced on or after July 26, 2021, and were included only if they went into effect before December 31, 2021. Data were included from 13 state-level jurisdictions with a vaccine mandate in effect as of December 31, 2021, that did not allow recurring testing in lieu of vaccination (mandate group), and 14 state-level jurisdictions that allowed a test-out option and/or did not restrict vaccine requirements (comparison group).Interventions/ExposuresThe event of interest was the announcement of a state-issued COVID-19 vaccine mandate applicable to specific groups of workers.Main Outcomes and MeasuresThe outcome measures were state-level daily COVID-19 vaccine first-dose administration and series completion coverage, reported as mean percentage point changes.ResultsOf 5 508 539 first-dose administrations in the 8-week postannouncement period, an estimated 634 831 (11.5%) were associated with the mandate announcement. First-dose administration coverage among 13 jurisdictions increased starting at 3 weeks after the mandate announcement, with statistically significant differences of 0.20, 0.33, 0.39, 0.45, 0.49, and 0.59 percentage points higher than the referent category coverage of 62.9%. Increases in vaccine series completion coverage were observed from 5 to 8 weeks after the announcement, but statistically significant differences from the referent category coverage of 56.3% were observed only during weeks 7 and 8 after the announcement (both differed by 0.2 percentage points; P = .05 and P = .02, respectively).Conclusions and RelevanceThe findings of this cross-sectional event study suggest that the announcement of state-issued vaccine mandates may be associated with short-term increases in vaccine uptake. This observed association may be a product of both a direct outcome experienced by groups governed by the mandate as well as the spillover outcome due to a government signaling the importance of vaccination to the general population of the state.

CONTEXT: In response to the COVID-19 pandemic, states across the United States implemented various strategies to mitigate transmission of SARS-CoV-2 (the virus that causes COVID-19). OBJECTIVE: To examine the effect of COVID-19-related state closures on consumer spending, business revenue, and employment, while controlling for changes in COVID-19 incidence and death. DESIGN: The analysis estimated a difference-in-difference model, utilizing temporal and geographic variation in state closure orders to analyze their impact on the economy, while controlling for COVID-19 incidence and death. PARTICIPANTS: State-level data on economic outcomes from the Opportunity Insights data tracker and COVID-19 cases and death data from usafacts.org. INTERVENTIONS: The mitigation strategy analyzed within this study was COVID-19-related state closure orders. Data on these orders were obtained from state government Web sites containing executive or administrative orders. MAIN OUTCOME MEASURES: Outcomes include state-level estimates of consumer spending, business revenue, and employment levels. RESULTS: Analyses showed that although state closures led to a decrease in consumer spending, business revenue, and employment, they accounted for only a small portion of the observed decreases in these outcomes over the first wave of COVID-19. CONCLUSIONS: The impact of COVID-19 on economic activity likely reflects a combination of factors, in addition to state closures, such as individuals' perceptions of risk related to COVID-19 incidence, which may play significant roles in impacting economic activity.

Background and Objective Community mitigation strategies could help reduce COVID-19 incidence, but there are few studies that explore associations nationally and by urbanicity. In a national county-level analysis, we examined the probability of being identified as a county with rapidly increasing COVID-19 incidence (rapid riser identification) during the summer of 2020 by implementation of mitigation policies prior to the summer, overall and by urbanicity. Methods We analyzed county-level data on rapid riser identification during June 1–September 30, 2020 and statewide closures and statewide mask mandates starting March 19 (obtained from state government websites). Poisson regression models with robust standard error estimation were used to examine differences in the probability of rapid riser identification by implementation of mitigation policies (P-value Results Counties in states that closed for 0–59 days were more likely to become a rapid riser county than those that closed for >59 days, particularly in nonmetropolitan areas. The probability of becoming a rapid riser county was 43% lower among counties that had statewide mask mandates at reopening (adjusted prevalence ratio = 0.57; 95% confidence intervals = 0.51–0.63); when stratified by urbanicity, associations were more pronounced in nonmetropolitan areas. Conclusions These results underscore the potential value of community mitigation strategies in limiting the COVID-19 spread, especially in nonmetropolitan areas.