Project description:Use of face coverings has been shown to reduce transmission of SARS-CoV-2. Despite encouragements from the CDC and other public health entities, resistance to usage of masks remains, forcing government entities to create mandates to compel use. The state of Oklahoma did not create a state-wide mask mandate, but numerous municipalities within the state did. This study compares case rates in communities with mandates to those without mandates, at the same time and in the same state (thus keeping other mitigation approaches similar). Diagnosed cases of COVID-19 were extracted from the Oklahoma State Department of Health reportable disease database. Daily case rates were established based upon listed city of residence. The daily case rate difference between each locality with a mask mandate were compared to rates for the portions of the state without a mandate. All differences were then set to a d0 point of reference (date of mandate implementation). Piecewise linear regression analysis of the difference in SARS-CoV-2 infection rates between mandated and non-mandated populations before and after adoption of mask mandates was then done. Prior to adopting mask mandates, those municipalities that eventually adopted mandates had higher transmission rates than the rest of the state, with the mean case rate difference per 100,000 people increasing by 0.32 cases per day (slope of difference = 0.32; 95% CI 0.13 to 0.51). For the post-mandate time period, the differences are decreasing (slope of -0.24; 95% CI -0.32 to -0.15). The pre- and post- mandate slopes differed significantly (p<0.001). The change in slope direction (-0.59; 95% CI -0.80 to -0.37) shows a move toward reconvergence in new case diagnoses between the two populations. Compared to rates in communities without mask mandates, transmission rates of SARS-CoV-2 slowed notably in those communities that adopted a mask mandate. This study suggests that government mandates may play a role in reducing transmission of SARS-CoV-2, and other infectious respiratory conditions.
Project description:We extend previous studies on the impact of masks on COVID-19 outcomes by investigating an unprecedented breadth and depth of health outcomes, geographical resolutions, types of mask mandates, early versus later waves and controlling for other government interventions, mobility testing rate and weather. We show that mask mandates are associated with a statistically significant decrease in new cases (-3.55 per 100K), deaths (-0.13 per 100K), and the proportion of hospital admissions (-2.38 percentage points) up to 40 days after the introduction of mask mandates both at the state and county level. These effects are large, corresponding to 14% of the highest recorded number of cases, 13% of deaths, and 7% of admission proportion. We also find that mask mandates are linked to a 23.4 percentage point increase in mask adherence in four diverse states. Given the recent lifting of mandates, we estimate that the ending of mask mandates in these states is associated with a decrease of -3.19 percentage points in mask adherence and 12 per 100K (13% of the highest recorded number) of daily new cases with no significant effect on hospitalizations and deaths. Lastly, using a large novel survey dataset of 847 thousand responses in 69 countries, we introduce the novel results that community mask adherence and community attitudes towards masks are associated with a reduction in COVID-19 cases and deaths. Our results have policy implications for reinforcing the need to maintain and encourage mask-wearing by the public, especially in light of some states starting to remove their mask mandates.
Project description:ImportanceTo help prevent the spread of SARS-CoV-2, government-instituted nonpharmaceutical interventions (eg, social distancing, mask use, isolating), a provincewide government-instituted mask mandate occurred on December 8, 2020, in Alberta, Canada, although some local jurisdictions implemented an earlier mask mandate. There remains a limited understanding of the association between government-implemented public health measures and individual health behaviors of children.ObjectiveTo examine the association between government mask mandates and mask use among children in Alberta, Canada.Design, setting, and participantsA cohort of children from Alberta, Canada, was recruited to examine longitudinal SARS-CoV-2 serologic factors. Parents were prospectively asked about their child's mask use in public places every 3 months (5-point Likert scale: never to always) from August 14, 2020, to June 24, 2022. A multivariable logistic generalized estimating equation was used to examine government mandatory masking mandates and child mask use. Child mask use was operationalized into a single composite dichotomous outcome by grouping parents who reported their child often or always wore a mask vs those who reported their child never, rarely, or occasionally wore a mask.ExposuresThe primary exposure variable was the government masking mandate (began on different dates in 2020). The secondary exposure variable was government private indoor and outdoor gathering restrictions.Main outcomes and measuresThe primary outcome was parent report of child mask use.ResultsA total of 939 children participated (467 female [49.7%]; mean [SD] age, 10.61 [1.6] years). The odds of parents' report of child mask use (often or always) was 18.3 times higher (95% CI, 5.7-58.6; P < .001; risk ratio, 1.7; 95% CI, 1.5-1.8; P < .001) with the mask mandate on compared with the mask mandate off. There was no significant change in mask use over the course of the mask mandate due to time. In contrast, each day with the mask mandate off was associated with a 1.6% decrease in mask use (odds ratio, 0.98; 95% CI, 0.98-0.99; P < .001).Conclusions and relevanceThe results of this study suggest that government-mandated mask use and providing the public with up-to-date health information (eg, case counts) is associated with increased parent-reported child mask use, while increasing time without a mask mandate is associated with decreased mask use.
Project description:Face masks are an important component in controlling COVID-19, and policy orders to wear masks are common. However, behavioral responses are seldom additive, and exchanging one protective behavior for another could undermine the COVID-19 policy response. We use SafeGraph smart device location data and variation in the date that US states and counties issued face mask mandates as a set of natural experiments to investigate risk compensation behavior. We compare time at home and the number of visits to public locations before and after face mask orders conditional on multiple statistical controls. We find that face mask orders lead to risk compensation behavior. Americans subject to the mask orders spend 11-24 fewer minutes at home on average and increase visits to some commercial locations-most notably restaurants, which are a high-risk location. It is unclear if this would lead to a net increase or decrease in transmission. However, it is clear that mask orders would be an important part of an economic recovery if people otherwise overestimate the risk of visiting public places.
Project description:BackgroundFace mask use has been associated with declines in COVID-19 incidence rates worldwide. A handful of studies have examined the factors associated with face mask use in North America during the COVID-19 pandemic; however, much less is known about the patterns of face mask use and the impact of mask mandates during this time. This information could have important policy implications, now and in the event of future pandemics.ObjectiveTo address existing knowledge gaps, we assessed face mask usage patterns among British Columbia COVID-19 Population Mixing Patterns (BC-Mix) survey respondents and evaluated the impact of the provincial mask mandate on these usage patterns.MethodsBetween September 2020 and July 2022, adult British Columbia residents completed the web-based BC-Mix survey, answering questions on the circumstances surrounding face mask use or lack thereof, movement patterns, and COVID-19-related beliefs. Trends in face mask use over time were assessed, and associated factors were evaluated using multivariable logistic regression. A stratified analysis was done to examine effect modification by the provincial mask mandate.ResultsOf the 44,301 respondents, 81.9% reported wearing face masks during the 23-month period. In-store and public transit mask mandates supported monthly face mask usage rates of approximately 80%, which was further bolstered up to 92% with the introduction of the provincial mask mandate. Face mask users mostly visited retail locations (51.8%) and travelled alone by car (49.6%), whereas nonusers mostly traveled by car with others (35.2%) to their destinations-most commonly parks (45.7%). Nonusers of face masks were much more likely to be male than female, especially in retail locations and restaurants, bars, and cafés. In a multivariable logistic regression model adjusted for possible confounders, factors associated with face mask use included age, ethnicity, health region, mode of travel, destination, and time period. The odds of face mask use were 3.68 times greater when the provincial mask mandate was in effect than when it was not (adjusted odds ratio [aOR] 3.68, 95% CI 3.33-4.05). The impact of the mask mandate was greatest in restaurants, bars, or cafés (mandate: aOR 7.35, 95% CI 4.23-12.78 vs no mandate: aOR 2.81, 95% CI 1.50-5.26) and in retail locations (mandate: aOR 19.94, 95% CI 14.86-26.77 vs no mandate: aOR 7.71, 95% CI 5.68-10.46).ConclusionsStudy findings provide added insight into the dynamics of face mask use during the COVID-19 pandemic. Mask mandates supported increased and sustained high face mask usage rates during the first 2 years of the pandemic, having the greatest impact in indoor public locations with limited opportunity for physical distancing targeted by these mandates. These findings highlight the utility of mask mandates in supporting high face mask usage rates during the COVID-19 pandemic.
Project description:Wearing masks reduces the spread of COVID-19, but compliance with mask mandates varies across individuals, time, and space. Accurate and continuous measures of mask wearing, as well as other health-related behaviors, are important for public health policies. This article presents a novel approach to estimate mask wearing using geotagged Twitter image data from March through September, 2020 in the United States. We validate our measure using public opinion survey data and extend the analysis to investigate county-level differences in mask wearing. We find a strong association between mask mandates and mask wearing-an average increase of 20%. Moreover, this association is greatest in Republican-leaning counties. The findings have important implications for understanding how governmental policies shape and monitor citizen responses to public health crises.
Project description:Using a population-based, representative telephone survey, ~930 000 New York City residents had COVID-19 illness beginning 20 March-30 April 2020, a period with limited testing. For every 1000 persons estimated with COVID-19 illness, 141.8 were tested and reported as cases, 36.8 were hospitalized, and 12.8 died, varying by demographic characteristics.
Project description:We quantify the effect of statewide mask mandates in the United States in 2020. Our regression discontinuity design exploits county-level variation in COVID-19 outcomes across the border between states with and without mandates. State mask mandates reduced new weekly COVID-19 cases, hospital admissions, and deaths by 55, 11, and 0.7 per 100,000 inhabitants on average. The effect depends on political leaning with larger effects in Democratic-leaning counties. Our results imply that statewide mandates saved 87,000 lives through December 19, 2020, while a nationwide mandate could have saved 57,000 additional lives. This suggests that mask mandates can help counter pandemics, particularly if widely accepted.
Project description:Evidence shows that chronic diseases are associated with COVID-19 severity and death. This study aims to estimate the fraction of hospitalizations and deaths from COVID-19 attributable to chronic diseases associated to poor nutrition and smoking among adults who tested positive to COVID-19 in Mexico. We analyzed 1,006,541 adults aged ≥20 who tested positive for COVID-19 from March 23 to December 5, 2020. Six chronic diseases were considered: obesity, chronic obstructive pulmonary disease (COPD), hypertension, diabetes, cardiovascular disease, and chronic kidney disease (CKD). We calibrated the database using a bias quantification method to consider undiagnosed disease cases. To estimate the total impact of multiple diseases, we defined a multimorbidity variable according to the number of diseases. Risks of hospitalization and death were estimated with Poisson regression models and used to calculate population attributable fractions (PAFs). Chronic diseases accounted for to 25.4% [95% CI: 24.8%-26.1%], 28.3% (95% CI: 27.8%-28.7%) and 15.3% (95% CI: 14.9%-15.7%) of the hospitalizations among adults below 40, 40-59, and 60 years and older, respectively. For COVID-19-related deaths, 50.1% (95% CI: 48.6%-51.5%), 40.5% (95% CI: 39.7%-41.3%), and 18.7% (95% CI, 18.0%-19.5%) were attributable to chronic diseases in adults under 40, 40-59, and 60 years and older, respectively. Chronic diseases linked to poor nutrition and smoking could have contributed to a large burden of hospitalization and deaths from COVID-19 in Mexico, particularly among younger adults. Medical and structural interventions to curb chronic disease incidence and facilitate disease control are urgently needed.