High-Quality Masks Reduce Covid-19 Infections and Death in the US

The objective is to evaluate the widespread adoption of masks on community transmission of SARS-CoV2. We employed an agent-based stochastic network simulation model and a variant of a SEIR disease model with one million agents in census tracts representing a population of 10.5 million. We evaluated scenarios with 25% to 90% mask-related reduction in viral transmission (mask efficacy). An individual wears a mask with a discrete probability values in [0-100%] (mask adherence). A mask order was initiated 3.5 months after the first confirmed case, with temporary state-wide distancing and voluntary quarantining of households. If 50% of the population wears masks that are 50% effective, this decreases the cumulative infection attack rate (CAR) by 27%, the peak prevalence by 54%, and the population mortality by 29%. If 90% wear masks that are 50% effective, this decreases the CAR by 38%, the peak prevalence by 75%, and the population mortality by 55%. © 2021 IEEE.

Association between overcrowded households, multigenerational households, and COVID-19: a cohort study.

OBJECTIVES: The role of overcrowded and multigenerational households as a risk factor for COVID-19 remains unmeasured. The objective of this study is to examine and quantify the association between overcrowded and multigenerational households and COVID-19 in New York City (NYC). STUDY DESIGN: Cohort study. METHODS: We conducted a Bayesian ecological time series analysis at the ZIP Code Tabulation Area (ZCTA) level in NYC to assess whether ZCTAs with higher proportions of overcrowded (defined as the proportion of the estimated number of housing units with more than one occupant per room) and multigenerational households (defined as the estimated percentage of residences occupied by a grandparent and a grandchild less than 18 years of age) were independently associated with higher suspected COVID-19 case rates (from NYC Department of Health Syndromic Surveillance data for March 1 to 30, 2020). Our main measure was an adjusted incidence rate ratio (IRR) of suspected COVID-19 cases per 10,000 population. Our final model controlled for ZCTA-level sociodemographic factors (median income, poverty status, White race, essential workers), the prevalence of clinical conditions related to COVID-19 severity (obesity, hypertension, coronary heart disease, diabetes, asthma, smoking status, and chronic obstructive pulmonary disease), and spatial clustering. RESULTS: 39,923 suspected COVID-19 cases were presented to emergency departments across 173 ZCTAs in NYC. Adjusted COVID-19 case rates increased by 67% (IRR 1.67, 95% CI = 1.12, 2.52) in ZCTAs in quartile four (versus one) for percent overcrowdedness and increased by 77% (IRR 1.77, 95% CI = 1.11, 2.79) in quartile four (versus one) for percent living in multigenerational housing. Interaction between both exposures was not significant (ßinteraction = 0.99, 95% CI: 0.99-1.00). CONCLUSIONS: Overcrowdedness and multigenerational housing are independent risk factors for suspected COVID-19. In the early phase of the surge in COVID cases, social distancing measures that increase house-bound populations may inadvertently but temporarily increase SARS-CoV-2 transmission risk and COVID-19 disease in these populations.