What happens in Vegas, stays in your lungs: an assessment of fine particulate matter in casinos that prohibit and allow smoking in Las Vegas, Nevada, USA.

INTRODUCTION: Despite progress in adoption of smoke-free policies, smoking in casinos is allowed in some US states, including Nevada. In 2020, for the first time, a resort-style casino in Las Vegas prohibited smoking voluntarily. This study is the first to assess air quality in this casino and compare results with similar casinos that allow smoking. METHODS: A real-time personal aerosol monitor evaluated particulate matter with a diameter <2.5 µm (PM2.5), a surrogate for secondhand smoke (SHS). PM2.5 was measured at eight Las Vegas casinos, including the smoke-free casino. Each casino was visited twice, and PM2.5 was assessed in smoking-permitted gaming areas and areas where smoking is otherwise prohibited. RESULTS: Average PM2.5 levels were significantly higher in casinos that allow smoking, for both casino gaming areas and areas where smoking is otherwise prohibited (p<0.05). Mean PM2.5 in gaming areas was 164.9 µg/m3 in casinos that allow smoking and 30.5 µg/m3 in the smoke-free casino. Mean PM2.5 in areas where smoking is otherwise prohibited was 83.2 µg/m3 in casinos which allowed smoking in gaming areas, and 48.1 µg/m3 in the smoke-free casino. CONCLUSION: Despite robust evidence about the harms of SHS, tens of thousands of casino employees and tens of millions of tourists are exposed to high levels of SHS in Las Vegas casinos annually, with PM2.5 levels 5.4 times higher in gaming areas when compared with a smoke-free casino. The only way to protect people from SHS exposure is to prohibit smoking in all indoor areas.

Evaluation of Statewide Restrictions on Flavored e-Cigarette Sales in the US From 2014 to 2020.

Importance: e-Cigarettes are the most commonly used tobacco product among US youths. Flavors are among the most cited reasons for use of e-cigarettes among youths, and therefore, some states have imposed restrictions on flavored e-cigarette sales. To our knowledge, no study has compared e-cigarette sales between states with statewide flavored e-cigarette restrictions and states without such restrictions while controlling for co-occurring events. Objective: To assess whether implementation of statewide restrictions on flavored e-cigarette sales in Massachusetts, New York, Rhode Island, and Washington was associated with a reduction in total e-cigarette unit sales from 2014 to 2020. Design, Setting, and Participants: This cross-sectional study with difference-in-differences analysis used e-cigarette retail sales data from Massachusetts, Rhode Island, and Washington, which implemented restrictions on flavored e-cigarette sales in October 2019; New York, which implemented these restrictions in May 2020; and 35 states without these restrictions (control states). Sales were summed into 4-week periods from August 24, 2014, to December 27, 2020, for a total of 2988 state-period observations. Main Outcomes and Measures: A difference-in-differences analysis was conducted to compare e-cigarette unit sales in the 4 states with flavor restrictions (before and after implementation) with those in the 35 control states. The model controlled for other population-based policies and emergent events (eg, the COVID-19 pandemic). Data on 4-week e-cigarette unit sales were sorted into 4 flavor categories (tobacco, menthol, mint, and other). Unit sales were standardized to reflect the most common package sizes for each product type. Results: Statewide restrictions on non-tobacco-flavored e-cigarette sales were associated with the following reductions in mean 4-week total e-cigarette sales in intervention states compared with control states from October 2019 to December 2020: 30.65% (95% CI, 24.08%-36.66%) in New York, 31.26% (95% CI, 11.94%-46.34%) in Rhode Island, and 25.01% (95% CI, 18.43%-31.05%) in Washington. In Massachusetts, the comprehensive sales prohibition of all e-cigarette products was associated with a 94.38% (95% CI, 93.37%-95.23%) reduction in 4-week sales compared with control states. Except in Massachusetts, where all sales of flavored e-cigarettes decreased, reductions were found only for non-tobacco-flavored e-cigarette sales in the other states with restrictions. Among control states, mean sales decreased by 28.4% from August 2019 to February 2020 but then increased by 49.9% from February through December 2020. Conclusions and Relevance: In this cross-sectional study, statewide restrictions on the sale of flavored e-cigarettes in Massachusetts, New York, Rhode Island, and Washington were associated with a reduction in total e-cigarette sales. These findings suggest that not all e-cigarette users who purchased non-tobacco-flavored e-cigarettes switched to purchasing tobacco-flavored e-cigarettes after policy implementation.

Differences in rapid increases in county-level COVID-19 incidence by implementation of statewide closures and mask mandates - United States, June 1-September 30, 2020.

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< .05); associations were adjusted for county population size. 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.

Timing of State and Territorial COVID-19 Stay-at-Home Orders and Changes in Population Movement - United States, March 1-May 31, 2020.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to spread from person to person primarily by the respiratory route and mainly through close contact (1). Community mitigation strategies can lower the risk for disease transmission by limiting or preventing person-to-person interactions (2). U.S. states and territories began implementing various community mitigation policies in March 2020. One widely implemented strategy was the issuance of orders requiring persons to stay home, resulting in decreased population movement in some jurisdictions (3). Each state or territory has authority to enact its own laws and policies to protect the public's health, and jurisdictions varied widely in the type and timing of orders issued related to stay-at-home requirements. To identify the broader impact of these stay-at-home orders, using publicly accessible, anonymized location data from mobile devices, CDC and the Georgia Tech Research Institute analyzed changes in population movement relative to stay-at-home orders issued during March 1-May 31, 2020, by all 50 states, the District of Columbia, and five U.S. territories.* During this period, 42 states and territories issued mandatory stay-at-home orders. When counties subject to mandatory state- and territory-issued stay-at-home orders were stratified along rural-urban categories, movement decreased significantly relative to the preorder baseline in all strata. Mandatory stay-at-home orders can help reduce activities associated with the spread of COVID-19, including population movement and close person-to-person contact outside the household.

Public Attitudes, Behaviors, and Beliefs Related to COVID-19, Stay-at-Home Orders, Nonessential Business Closures, and Public Health Guidance - United States, New York City, and Los Angeles, May 5-12, 2020.

SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is thought to be transmitted mainly by person-to-person contact (1). Implementation of nationwide public health orders to limit person-to-person interaction and of guidance on personal protective practices can slow transmission (2,3). Such strategies can include stay-at-home orders, business closures, prohibitions against mass gatherings, use of cloth face coverings, and maintenance of a physical distance between persons (2,3). To assess and understand public attitudes, behaviors, and beliefs related to this guidance and COVID-19, representative panel surveys were conducted among adults aged ≥18 years in New York City (NYC) and Los Angeles, and broadly across the United States during May 5-12, 2020. Most respondents in the three cohorts supported stay-at-home orders and nonessential business closures* (United States, 79.5%; New York City, 86.7%; and Los Angeles, 81.5%), reported always or often wearing cloth face coverings in public areas (United States, 74.1%, New York City, 89.6%; and Los Angeles 89.8%), and believed that their state's restrictions were the right balance or not restrictive enough (United States, 84.3%; New York City, 89.7%; and Los Angeles, 79.7%). Periodic assessments of public attitudes, behaviors, and beliefs can guide evidence-based public health decision-making and related prevention messaging about mitigation strategies needed as the COVID-19 pandemic evolves.