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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. [ABSTRACT FROM AUTHOR]

Many public institutions and settings have taken action to limit exposure to and slow the spread of the novel coronavirus (COVID-19). We sought to characterize the impact of stay-at-home orders on our study of cerebral autoregulation and its association with developmental delays in infants with congenital heart disease compared with healthy controls. We calculated the number of participants recruited (i.e., not enrolled in the study) and assessed (i.e., currently enrolled) before March 2020 (pre-COVID-19) and the number of participants that we could not recruit or assess between March and July 2020 (missed due to COVID-19), separately for congenital heart disease and healthy control infants, in reference to the impacts of COVID-19. We used negative binomial regressions to determine incidence rate ratios which compared participants recruited and assessed pre-COVID-19 and missed due to COVID-19. Recruitment and assessments significantly decreased following the pandemic, i.e., participants were more likely to be recruited or be assessed pre-COVID-19 compared to during the pandemic. Study participants were 3.3 times as likely to have assessments performed pre-COVID-19 compared to during the COVID-19 pandemic (p < 0.001). Clinical research teams may consider making protocol modifications such as virtual visits or video recordings explaining the study, for example, to adjust to the restrictions caused by COVID-19. The COVID-19 pandemic drastically reduced recruitment and assessments completed in our study. Study teams will need to continue to modify procedures for recruitment and assessments that align with COVID-19 regulations to facilitate research progress during the pandemic. • We describe the impact of the COVID-19 pandemic on pediatric clinical research at a single tertiary institution. • The COVID-19 pandemic drastically reduced our participant recruitment and assessments. • Study modifications, such as virtual visits, must be implemented to adjust to COVID-19 precautions. • Emphasis on our institution and study's COVID-19 safeguards have helped family's return for follow-up assessments. [ABSTRACT FROM AUTHOR]

Road traffic accidents are one of the leading causes of death for the young segment of the population. Prevention strategies can mitigate the occurrence of road accidents, and successful actions should take into account the most relevant causes of accidents. We use a comprehensive dataset which reports information from police records on all road traffic accidents with injures and/or deaths in Italy between 2014 and 2020 to explore the relationships among economic forces, driving behaviours and accident frequency and severity. More specifically, the natural experiment setting provided by the 2020 COVID-19-related movement restrictions allows to capture the effect of traffic intensity and other factors on the frequency of serious accidents and mortality. The empirical findings confirm a direct relationship between the level of economic activity and the frequency of accidents, whereas there is no clear link with their severity. Instead, lockdown periods are associated with a relatively higher occurrence of fatal road traffic accidents, due to both riskier driving behaviours at times of reduced traffic, and changes in transportation habits reflected by a higher probability of accidents involving bicycles and motorcycles. • Economic variables are a major determinant of road traffic accidents (RTAs) in Italy. • RTA frequency follows the economic cycle, but mortality is unrelated. • COVID-19-related stay-at-home orders reduced the number of RTAs, injuries and deaths. • Lockdown periods were associated with a higher rate of fatal accidents. • Road safety strategies should consider behavioral responses to movement restrictions. [ABSTRACT FROM AUTHOR]

• Child maltreatment reporting dropped by as much as 31 percent in Colorado during the pandemic. • Counterfactual estimates predict thousands of referrals and victims went unreported. • Victims of neglect were most likely being missed. • Data and clever techniques to measure child maltreatment need to be readily available. As a result of the COVID-19 pandemic, schools closed abruptly in March 2020, and Colorado issued a stay-at-home order during the month of April. Subsequently, child maltreatment reporting dropped by 31 percent. This article documents the decline in referrals and reports during 2020 and 2021 in Colorado and predicts counterfactual estimates using two strategies. One strategy assumes the underlying behavior for child maltreatment was unchanged from 2019 to 2020 and 2021, while the second strategy assumes the economic distress and protective factors brought about by the pandemic altered the underlying prevalence of child maltreatment. Consequently, these two approaches yield similar results when investigating referrals, but they differ when investigating screened-in referrals and substantiated reports. I find that the largest reduction in reporting comes from the stay-at-home order, followed by school closings. Lastly, counterfactual estimates suggest that these missed children were suffering from neglect and not abuse. These findings quantify another hardship brought about by the pandemic, underreporting child maltreatment, and underscore the role mandatory reporters play in detecting child maltreatment. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, strict stay-at-home orders have been implemented in many Chinese universities in virus-hit regions. While changes in electricity consumption in the residential sector caused by COVID-19 have been thoroughly analysed, there is a lack of insight into the impact of the stay-at-home order on electricity consumption in university dormitory buildings. Based on questionnaire survey results, this study adopted the statistical Kaplan–Meier survival analysis to analyse the energy-use behaviours of university students in dormitories during the COVID-19 pandemic. The electricity load profiles of the dormitory buildings before and during the implementation of the stay-at-home order were generated and compared to quantitatively analyse the influence of COVID-19 pandemic on the energy-use behaviours of university students, and the proposed load forecasting method was validated by comparing the forecasting results with monitoring data on electricity consumption. The results showed that: 1) during the implementation of the stay-at-home order, electricity consumption in the university dormitory buildings increased by 41.05%; 2) due to the increased use of illuminating lamps, laptops, and public direct drinking machines, the daily electricity consumption increased most significantly from 13:00 to 18:00, with an increase rate of 97.15%; and 3) the morning peak shifted backward and the evening peak shifted forward, demonstrating the effect of implementing the stay-at-home order on reshaping load profiles. [ABSTRACT FROM AUTHOR]

Using the 8th wave of the SHARE and the SHARE Corona Survey, we investigated whether the disruption of parent–adult child contacts due to social distancing restrictions increased the symptoms of depression among old age individuals during the first wave of the COVID-19 pandemic. We model the relationship between the disruption of parent–adult child contacts and the mental health of the elderly using a recursive simultaneous equation model for binary variables. Our findings show that the likelihood of disruption of parent–adult child contacts was higher with adult children who do not live with or close to their parents (i.e., in the same household or in the same building) for whom contact disruption increases about 15 %. The duration of restrictions to movement and lockdowns also has a positive and significant effect on parent-child contact disruption: an additional week of lockdown significantly increases the probability of parent-child contact disruption, by about 1.5 %. The interventions deemed essential to reduce the spread of the pandemic, such as the "stay-at-home" order, necessarily disrupted personal parent–child contacts and the social processes that facilitate psychological well-being, increasing the probability of suffering from a deepening depressed mood by about 17 % for elderly parents. • We explore whether the disruption of the parent–child contacts, because of lockdown, increases depression in older persons. • We use a joint model of contacts disruption and mental health to takes into account for unobserved heterogeneity. • Our evidence reflects that parent-adult child contacts disruption due to COVID‐19's worsens mental health of older people. • Our study provides additional insights into the psychological status and strain on older during the COVID-19 outbreak. [ABSTRACT FROM AUTHOR]

In response to the COVID-19 pandemic, a growing number of states, counties and cities in the United States issued mandatory stay-at-home orders as part of their efforts to slow down the spread of the virus. We argue that the consequences of this one-size-fits-all order will be differentially distributed among economic groups. In this paper, we examine social distance behavior changes for lower income populations. We conduct a comparative analysis of responses between lower-income and upper-income groups and assess their relative exposure to COVID-19 risks. Using a difference-in-difference-in-differences analysis of 3140 counties, we find social distance policy effect on the lower-income group is smaller than that of the upper-income group, by as much as 46% to 54%. Our explorations of the mechanisms behind the disparate effects suggest that for the work-related trips the stay-at-home orders do not significantly reduce low income work trips and this result is statistically significant. That is, the share of essential business defined by stay-at-home orders is significantly negatively correlated with income at county level. In the non-work-related trips, we find that both the lower-income and upper-income groups reduced visits to retail, recreation, grocery, and pharmacy visits after the stay-at-home order, with the upper-income group reducing trips more compared to lower-income group. [ABSTRACT FROM AUTHOR]