hysical distancing has been the primary strategy to limit the spread of COVID-19 in the United States. Physical distancing (also called 'social distancing') entails reducing contacts between non-household members to reduce opportunities for transmission from infected to susceptible individuals. To promote physical distancing, most US states closed schools, mandated business closures, and issued 'stay-at-home' orders directing residents to avoid unnecessary trips. These measures have been essential to prevent worst-case scenarios involving millions of deaths 1-3. Although there is evidence that new cases of COVID-19 declined as people stayed home 2 , evidence suggests unequal declines in the burden of COVID-19. While case data disaggregated by income are not available, COVID-19 case and death rates have risen fastest in low-income communities 4,5. An association between lower neighbourhood income and COVID-19 risk is also consistent with data showing higher COVID-19 mortality among racial and ethnic minorities 6 , whose socioeconomic position is systematically lower, on average, than that of white Americans and who disproportionately reside in low-income neighbourhoods due to a long history of discriminatory housing policy 7,8. Financial constraints to physical distancing may have been an important factor contributing to higher COVID-19 burden among economically marginalized populations 4. At businesses that have remained open during the pandemic, low-income workers have reported less ability to work from home relative to higher wage earners 9. At these workplaces, most workers were not eligible for unemployment insurance unless they could document a COVID-19 diagnosis or exposure 10. Although many states began closing businesses and ordering residents to stay home in the second half of March, businesses deemed essential remained open, and staffed predominantly by low-wage workers 11,12. It was not until mid-April that some states began requiring people to wear masks in public spaces to reduce COVID-19 transmission, and some states still have not done so 10. In this context, low-income workers have had to choose between staying home and losing their income or going to work and risking exposure to COVID-19 for themselves and their households and neighbours. Given that those in low-income households typically have little savings 13 , losing income could bring other health and safety risks, including homelessness and food insecurity. Previous work 14 has found that residents of low-income neighbourhoods were less likely than residents of higher-income neighbourhoods to stay home in response to COVID-19. In this article, we test two main hypotheses. First, we proposed that this gap in physical distancing was explained by work-related demands (hypothesis 1a) and not by visits to places other than work (hypothesis 1b). Second, we proposed that state policies that ordered non-essential businesses to close, and for residents to stay at home, increased the gap in physical distancing between low-and high-income neighbourhoo...

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The spread of COVID-19 is not evenly distributed. Neighborhood environments may structure risks and resources that produce COVID-19 disparities. Neighborhood built environments that allow greater flow of people into an area or impede social distancing practices may increase residents’ risk for contracting the virus. We leveraged Google Street View (GSV) images and computer vision to detect built environment features (presence of a crosswalk, non-single family home, single-lane roads, dilapidated building and visible wires). We utilized Poisson regression models to determine associations of built environment characteristics with COVID-19 cases. Indicators of mixed land use (non-single family home), walkability (sidewalks), and physical disorder (dilapidated buildings and visible wires) were connected with higher COVID-19 cases. Indicators of lower urban development (single lane roads and green streets) were connected with fewer COVID-19 cases. Percent black and percent with less than a high school education were associated with more COVID-19 cases. Our findings suggest that built environment characteristics can help characterize community-level COVID-19 risk. Sociodemographic disparities also highlight differential COVID-19 risk across groups of people. Computer vision and big data image sources make national studies of built environment effects on COVID-19 risk possible, to inform local area decision-making.

IMPORTANCEPublic health measures instituted to reduce the spread of COVID-19 led to severe disruptions to the structure of daily life, and the resultant social and financial impact may have contributed to an increase in violence. OBJECTIVE To examine the trends in violent penetrating injuries during the first COVID-19 pandemic year compared with previous years. DESIGN, SETTING, AND PARTICIPANTS This retrospective cross-sectional study was performed to compare the prevalence of violent penetrating injuries during the first COVID-19 pandemic year, March 2020 to February 2021, with the previous 5 years, March 2015 to February 2020. This study was performed among all patients with a violent penetrating injury presenting at Boston Medical Center, an urban, level I trauma center that is the largest safety-net hospital and busiest trauma center in New England. Data were analyzed from January 4 to November 29, 2021. MAIN OUTCOMES AND MEASURES The primary outcomes were the incidence and timing of emergency department presentation for violent penetrating injuries during the first year of the COVID-19 pandemic compared with the previous 5 years. Patient demographics and injury characteristics were also assessed. RESULTS A total of 2383 patients (median [IQR] age, 29.5 [23.4-39.3] years; 2032 [85.4%] men and 351 [14.6%] women) presenting for a violent penetrating injury were evaluated, including 1567 Black patients (65.7%), 448 Hispanic patients (18.8%), and 210 White patients (8.8%). There was an increase in injuries during the first pandemic year compared with the previous 5 years, with an increase in shootings (mean [SD], 0.61 [0.89] injuries per day vs 0.46 [0.76] injuries per day; P = .002) but not stabbings (mean [SD], 0.60 [0.79] injuries per day vs 0.60 [0.82] injuries per day; P = .78). This surge in firearm violence began while Massachusetts was still under a stay-at-home advisory and before large-scale racial justice protests began. Patients presenting with violent penetrating injuries in the pandemic surge months (April-October 2020) compared with the same period in previous years were disproportionately male (153 patients [93.3%] vs 510 patients [87.6%]; P = .04), unemployed (70 patients [57.4%] vs 221 patients [46.6%]; P = .03), and Hispanic (40 patients [26.0%] vs 99 patients [17.9%]; P = .009), with a concurrent decrease in White patients (0 patients vs 26 patients [4.7%]), and were more likely to have no previous history of violent penetrating injury (146 patients [89.0%] vs 471 patients [80.9%]; P = .02). CONCLUSIONS AND RELEVANCEThese findings suggest that unprecedented measures implemented to mitigate the spread of COVID-19 were associated with an increase in gun violence.As the pandemic abates, efforts at community violence prevention and intervention must be redoubled to defend communities against the epidemic of violence.

Jonathan Quick and colleagues discuss how women's health world-wide can be improved through universal health coverage. Please see later in the article for the Editors' Summary

AIMS:To explore men's and women's experiences of weight change in adulthood, body image preferences and beliefs about the health consequences of overweight and to inform the development of a primary care intervention to prevent obesity. SAMPLE: Seventy-two men and women aged 35 -55, with a range of BMIs from 22 to 29.9, were identified from two UK general practice registers and invited to participate in an interview about experiences of weight change in adulthood. METHODS: Audio tape recorded, semi-structured interviews were conducted in respondents' homes by trained researchers. Open-ended questions were used to collect experiences of weight change since early adulthood and views about weight change in middle age. Illustrations of a range of men's and women's body shapes were used to prompt discussion of respondents' preferences for male and female body shapes and their perspectives of the health, social and practical problems associated with underweight and overweight. The data were analysed using both quantitative and qualitative methods. RESULTS: Some 87% (33=38) of the women and 59% (20=34) of the men said that they had ever tried to lose weight. At least one instance of successful weight loss was reported by 58% of the women and 47% of the men, although many of these attempts were relatively short-lived and often motivated by specific goals such as a holiday or a wedding. Respondents were sceptical of the possibility of controlling weight without considerable personal sacrifice. Explanations for middle-age weight gain included a sedentary lifestyle, as well as several gender-specific reasons, including hormonal changes and comfort eating for women and beer drinking for men. Nearly all (97%) respondents associated heart disease with overweight, while diabetes was mentioned by only 22% and none mentioned cancer. CONCLUSION: People who have gained weight in middle age may be deterred from trying to prevent further gain by pessimism about the effort required. The efficacy of interventions to encourage relatively small substitutions and changes to diet and physical activity need to be tested. Interventions to help prevent weight gain in middle age could include information about the less widely known health risks such as diabetes and cancer.

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