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Objective: The COVID-19 pandemic has disrupted people's lives around the world, including college students. This cross-sectional study aimed to 1) describe psychological distress, coping, and expectancies of undergraduates during COVID-19 "stay-at-home" orders and 2) examine the associations among these variables. Participants and methods: Midwestern US undergraduates (N = 186) completed measures of psychological distress, coping behaviors, and expectancies in March-April 2020 during the initial round of "stay-at-home" orders. Results: Students engaged in approach coping and disease prevention behaviors and had low expectations for contracting COVID-19. Most students reported clinically significant depression or anxiety. Adherence to disease prevention behaviors was associated with less stress but more anxiety. Positive expectancies and approach coping were associated with less distress. Avoidance coping was associated with more distress. Conclusions: This study describes the toll that COVID-19 has had on college students. Continued attention to the mental health of college students during the pandemic is imperative.

BackgroundTo slow the spread of the COVID-19 virus, governments across the globe instituted stay-at-home orders leading to increased stress and social isolation. Not surprisingly, alcohol sales increased during this period. While most studies primarily focused on alcohol consumption among college students or adults, this study investigates alcohol misuse among marginalized youth in the USA. We examined risk factors associated with hazardous alcohol use and binge drinking including risk behaviors, life stressors and demographic characteristics.MethodsIn October 2020, youth living with or at high risk for acquiring human immunodeficiency virus (HIV), participating in community-based research to improve HIV prevention and care, were invited to complete an online survey to assess the impact of the stay-at-home orders on multiple aspects of their daily life.ResultsRespondents (n = 478) were on average 23 years old; cisgender (84%), not-heterosexual (86.6%), Latino or Black/African American (73%) and assigned male at birth (83%); 52% reported being employed and 14% reported living with HIV. White participants and those who use drugs had higher odds of hazardous alcohol use and binge drinking, compared with other race categories and non-drug users, respectively.ConclusionContrary to findings from adult studies, we did not observe an increase in hazardous or binge drinking among youth at risk for HIV. Hazardous alcohol use and binge drinking was more likely among White participants, those who use drugs and those who were hazardous/binge drinkers prior to the COVID-19 lockdown, which points to the importance of identifying and treating youth who misuse alcohol early to prevent future alcohol misuse.

Epidemiological models projected that, without effective mitigation strategies, upwards of 2 million Americans were at risk of death from the COVID-19 pandemic. Heeding the warning, in mid-March 2020, state and local officials in the United States began issuing Stay-at-Home (SAH) orders, instructing people to remain at home except to do essential tasks or to do work deemed essential. By April 4th, 2020, nearly 95% of the U.S. population was under such orders. Over the same three week period, initial claims for unemployment spiked to unprecedented levels. In this paper, we use the high-frequency, decentralized implementation of SAH orders, along with high-frequency unemployment insurance (UI) claims, to disentangle the relative effect of SAH orders from the general economic disruption wrought by the pandemic that affected all regions similarly. We find that, all else equal, each week of Stay-at-Home exposure increased a state’s weekly initial UI claims by 1.9% of its employment level relative to other states. Ignoring cross-regional spillovers, a back-of-the-envelope calculation implies that, of the 17 million UI claims made between March 14 and April 4, only 4 million were attributable to the Stay-at-Home orders. This evidence suggests that the direct effect of SAH orders accounted for a substantial, but minority share, of the overall initial rise in unemployment claims. We present a stylized currency union model to provide conditions under which this estimate represents an upper or lower bound for aggregate employment losses attributable to SAH orders.

In response to COVID-19, states implemented stay-at-home orders, affecting two key correlates of recidivism: housing and employment. In this study, we examine how a programme that sought to facilitate successful reintegration through paid transitional housing was impacted by stay-at-home orders. Specifically, we evaluate the impact of an RCT where formerly incarcerated individuals were provided with paid transitional housing before and during a stay-at-home order. Results indicate no difference in the likelihood of the treatment group and control group to be employed or return to prison prior to the stay-at-home order. After the implementation of the stay-at-home order, however, individuals in the treatment group were more likely to be employed and less likely to return to prison. Our findings suggest that the relationship between housing, employment, and re-incarceration was further exacerbated during the pandemic. The findings illustrate the benefits of paid transitional housing for those returning home during the pandemic. With the economic and social consequences of COVID-19 likely to persist, finding ways to set up formerly incarcerated individuals for success is imperative. Results suggest that paid transitional housing and additional housing assistance may be one avenue to accomplish this goal. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Policy responses to the COVID-19 pandemic, such as the NY on Pause stay-at-home order (March 22 - June 8, 2020), substantially reduced traffic and traffic-related air pollution (TRAP) in New York City (NYC). We evaluated the magnitude of TRAP decreases and examined the role of modifying factors such as weekend/weekday, road proximity, location, and time-of-day. METHODS: Hourly nitrogen dioxide (NO2) concentrations from January 1, 2018 through June 8, 2020 were obtained from the Environmental Protection Agencys Air Quality System for all six hourly monitors in the NYC area. We used an interrupted time series design to determine the impact of NY on Pause on NO2 concentrations, using a mixed effects model with random intercepts for monitor location, adjusted for meteorology and long-term trends. We evaluated effect modification through stratification. RESULTS: NO2 concentrations decreased during NY on Pause by 19% (-3.2 ppb, 95% confidence interval [CI]: -3.5, -3.0), on average, compared to pre-Pause time trends. We found no evidence for modification by weekend/weekday, but greater decreases in NO2 at non-roadside monitors and weak evidence for modification by location. For time-of-day, we found the largest decreases for 5 am (27%, -4.5 ppb, 95% CI: -5.7, -3.3) through 7 am (24%, -4.0 ppb, 95% CI: -5.2, -2.8), followed by 6 pm and 7 pm (22%, -3.7 ppb, 95% CI: -4.8, -2.6 and 22%, -4.8, -2.5, respectively), while the smallest decreases occurred at 11 pm and 1 am (both: 11%, -1.9 ppb, 95% CI: -3.1, -0.7). CONCLUSION: NY on Pauses impact on TRAP varied greatly diurnally. Decreases during early morning and evening time periods are likely due to decreases in traffic. Our results may be useful for planning traffic policies that vary by time of day, such as congestion tolling policies.

IntroductionCOVID-19 has rapidly spread across the world. In March 2020, shortly after the first confirmed case of COVID-19 in Ethiopia in March 2020, the government of Ethiopia took several measures.PurposeThis study aims to explore how stay-at-home orders during the COVID-19 pandemic hinder engagement with HIV/AIDS care in public hospitals in Southwest Ethiopia. Additionally, we aim to explore the psychosocial challenges faced in accessing services during stay-at-home orders.MethodsA descriptive qualitative study was conducted from 20 May to 3 June 2020, using semi-structured, in-depth interviews. In total, 27 study participants were recruited from purposively selected people living with HIV/AIDS (PLWHA) who had experienced delays, declines, or discontinuation of care after COVID-19 was confirmed in Ethiopia on 13 March 2020. The participants were interviewed over the phone and their responses were audio-recorded. Data were transcribed verbatim, translated, and analyzed using inductive thematic analysis in the Atlas ti.7.1 software package.ResultsThe main themes and sub-themes that emerged were psychosocial issues (such as depression, hopelessness, and fear), risk perception (including high risk, susceptibility, and severity), forceful enforcement of stay-at-home orders (such as police beatings, community leaders disgracing, and influence of families and relatives), socioeconomic factors (such as stigma, religion, and transportation costs), misinformation about COVID-19 (such as lockdowns and ART stock-outs), and healthcare factors (such as inadequate health information and long distances to healthcare facilities).ConclusionOverall, these findings were similar to the challenges experienced by PLWHA in adhering to the recommended continuum of care. However, there are additional factors due to COVID-19, such as misinformation and the forceful implementation of the stay-at-home-orders, that impede the continuum of care. Therefore, it is important to strengthen information, education, and communication.

Purpose – This study seeks to determine the effects of stay-at-home orders in Spring 2020 on COVID-19 cases and deaths in the Central USA by comparing counties and health service areas that were and that were not subject to statewide orders. Design/methodology/approach – This study estimates the effects of statewide stay-at-home orders on new COVID-19 cases and deaths within 19 central states, of which 14 had stay-at-home orders. It uses synthetic control analysis and nearest neighbor matching to estimate the effects at two geographic levels: counties and health service areas. Findings – Statewide stay-at-home orders significantly reduced the number of new COVID-19 cases in the Central USA starting about three weeks after their effective dates; during the fourth week after their effective dates, the orders reduced the number of new cases per capita by 31%–57%. Statewide stay-at-home orders did not reduce the number of new COVID-19 deaths in the Central USA. Social implications – The main purpose of stay-at-home orders in Spring 2020 was to “flatten the curve” so that hospitalizations would not exceed capacity. It is likely that stay-at-home orders in the Central USA reduced hospitalizations to some extent, although the effect on hospitalizations was likely smaller than the effect on cases. Originality/value – This is the first study of stay-at-home orders in the USA to limit the population to a group of interior states. All coastal states had statewide stay-at-home orders and comparing coastal states with orders to interior states without them may be problematic.

The COVID-19 pandemic has led public health departments to issue several orders and recommendations to reduce COVID-19-related morbidity and mortality. However, for various reasons, including lack of ability to sufficiently monitor and influence behavior change, adherence to these health orders and recommendations has been suboptimal. Starting April 29, 2020, during the initial stay-at-home orders issued by various state governors, we conducted an intervention that sent online website and mobile application advertisements to people's mobile phones to encourage them to adhere to stay-at-home orders. Adherence to stay-at-home orders was monitored using individual-level cell phone mobility data, from April 29, 2020 through May 10, 2020. Mobile devices across 5 regions in the United States were randomly-assigned to either receive advertisements from our research team advising them to stay at home to stay safe (intervention group) or standard advertisements from other advertisers (control group). Compared to control group devices that received only standard corporate advertisements (i.e., did not receive public health advertisements to stay at home), the (intervention group) devices that received public health advertisements to stay at home demonstrated objectively-measured increased adherence to stay at home (i.e., smaller radius of gyration, average travel distance, and larger stay-at-home ratios). Results suggest that 1) it is feasible to use mobility data to assess efficacy of an online advertising intervention, and 2) online advertisements are a potentially effective method for increasing adherence to government/public health stay-at-home orders.

Background: At the beginning of the COVID-19 pandemic, non-pharmaceutical interventions (NPIs) of unprecedented scope and duration were implemented to limit community spread of COVID-19. There remains limited evidence about how these measures impacted the lived experience of affected communities. This study captured the early impacts and coping strategies implemented in King County, Washington, one of the first U.S. communities impacted by COVID-19. Methods: We conducted a cross-sectional web-based survey of 793 English- and Spanish-speaking adult King County residents from March 18, 2020 –May 30, 2020, using voluntary response sampling. The survey included close- and open-ended questions on participant demographics, wellbeing, protective actions, and COVID-19-related concerns, including a freeform narrative response to describe the pandemic's individual-, family- and community-level impacts and associated coping strategies. Descriptive statistics were used to analyze close-ended questions, and qualitative content analysis methods were used to analyze free-form narrative responses. Results: The median age of participants was 45 years old, and 74% were female, 82% were White, and 6% were Hispanic/Latinx; 474 (60%) provided a qualitative narrative. Quantitative findings demonstrated that higher percentages of participants engaged in most types of COVID-19 protective behaviors after the stay-at-home order was implemented and schools and community spaces were closed, relative to before, and that participants tended to report greater concern about the pandemic's physical health or healthcare access impacts than the financial or social impacts. Qualitative data analysis described employment or financial impacts (56%) and vitality coping strategies (65%), intended to support health or positive functioning. Conclusions: This study documented early impacts of the COVID-19 pandemic and the NPIs implemented in response, as well as strategies employed to cope with those impacts, which can inform early-stage policy formation and intervention strategies to mitigate the negative impacts. Future research should explore the endurance and evolution of the early impacts and coping strategies throughout the multiyear pandemic. [ABSTRACT FROM AUTHOR]

To evaluate the occurrence and outcome of open globe injury during state-mandated COVID-19 stay-at-home orders compared to historical averages at a tertiary medical center in Portland, Oregon. Open globe injury between January 1, 2015 and December 31, 2020 was identified using relevant procedure codes. The number of injuries, mechanism of trauma, and short-term outcomes of globes repaired during the study period of March 23, 2020 to July 6, 2020 when stay-at-home orders were in effect were compared to a cohort from the same 15-week time frame in 2015–2019. We also evaluated injuries occurring throughout 2020 as compared to the prior 5 years. 263 consecutive open globe injuries were identified between January 2015 and December 2020. While Oregon's stay-at-home orders were in effect, we observed a significant increase in the number of open globe injuries treated compared to the prior 5 years (p =.004). Twenty-four cases identified during the study period represent a 2-fold increase over the 2015–2019 average of 11.8 globe repairs during the same 15-week time period. Visual acuity < 20/200 at 6 months (p =.008) and secondary enucleation (p <.001) were more frequent during stay-at-home orders, and severity of injury as calculated by the Ocular Trauma Scores (OTS) was higher. Time-to-repair was similar between the two cohorts. At our center, there was an increased number and severity of open globe injury during the period of mandatory COVID-19 stay-at-home orders. Visual acuity outcomes and risk for secondary enucleation were poorer compared to the reference cohort. Abbreviations: Ocular Trauma Score (OTS), Open globe injury (OGI), Emergency department (ED), Oregon Health and Science University (OHSU) [ABSTRACT FROM AUTHOR]

This study aimed to better understand the inequitable impact of the pandemic by examining the associations between stay-at-home orders and indoor smoking in public housing, measured by ambient particulate matter at the 2.5-micron threshold, a marker for secondhand smoke. Particulate matter at the 2.5-micron threshold was measured in 6 public-housing buildings in Norfolk, VA from 2018 to 2022. Multilevel regression was used to compare the 7-week period of the Virginia stay-at-home order in 2020 with that period in other years. Indoor particulate matter at the 2.5-micron threshold was 10.29 μg/m3 higher in 2020 (95% CI=8.51, 12.07) than in the same period in 2019, a 72% increase. Although particulate matter at the 2.5-micron threshold improved in 2021 and 2022, it remained elevated relative to the level in 2019. Stay-at-home orders likely led to increased indoor secondhand smoke in public housing. In light of evidence linking air pollutants, including secondhand smoke, with COVID-19, these results also provide further evidence of the disproportionate impact of the pandemic on socioeconomically disadvantaged communities. This consequence of the pandemic response is unlikely to be isolated and calls for a critical examination of the COVID-19 experience to avoid similar policy failures in future public health crises. [ABSTRACT FROM AUTHOR]

Author(s): Molly M. McLay [sup.1] Author Affiliations: (1) grid.4367.6, 0000 0001 2355 7002, Brown School, Washington University in St. Louis, , Campus Box 1196, One Brookings Drive, 63130, Saint Louis, [...], This study explored the COVID-19 pandemic&apos;s impacts on domestic violence (DV) with the following research questions: 1) Did DV occurring during the pandemic differ on certain variables from cases occurring on a typical day the previous year? 2) Did DV occurring after the implementation of shelter-in-place orders differ (on these same variables) from cases occurring prior to shelter-in-place orders? Two logistic regression models were developed to predict DV case differences before and during the pandemic. DV reports (N = 4618) were collected from the Chicago Police Department. Cases from March 2019 and March 2020 were analyzed based on multiple variables. One model was set to predict case differences since the pandemic began, and another model was set to predict case differences during the shelter-in-place period later that month. Both models were significant with multiple significant predictors. During the pandemic period, cases with arrests were 20% less likely to have occurred, and cases at residential locations were 22% more likely to have occurred. During the shelter-in-place period, cases at residential locations were 64% more likely to have occurred, and cases with child victims were 67% less likely to have occurred. This study offers a rapid analysis of DV case differences since the pandemic and shelter-in-place began. Additional variables and data sources could improve model explanatory power. Research, policy, and practice in this area must pivot to focus on protecting children whose access to mandated reporters has decreased and moving victims out of dangerous living situations into safe spaces.

Objectives: Evidence is limited on differences in cesarean rates for nulliparous, term, singleton, vertex (NTSV) births across racial and ethnic groups at the national and state level during the COVID-19 pandemic. We assessed changes in levels and trends of NTSV cesarean rates before and after stay-at-home orders (SAHOs) were implemented in the United States (1) overall, (2) by racial and ethnic groups, and (3) by 50 US states from January 2017 through December 2021. Methods: We used birth certificate data from 2017 through 2021, restricted to hospital births, to calculate monthly NTSV cesarean rates for the United States and for racial and ethnic groups and to calculate quarterly NTSV cesarean rates for the 50 states. We used interrupted time-series analysis to measure changes in NTSV cesarean rates before and after implementation of SAHOs (March 1 through May 31, 2020). Results: Of 6 022 552 NTSV hospital births, 1 579 645 (26.2%) were cesarean births. Before implementation of SAHOs, NTSV cesarean rates were declining in the United States overall; were declining among births to non-Hispanic Asian, non-Hispanic Black, Hispanic, and non-Hispanic White women; and were declining in 6 states. During the first month of implementation of SAHOs in May 2020, monthly NTSV rates increased in the United States by 0.55%. Monthly NTSV rates increased by 1.20% among non-Hispanic Black women, 0.90% among Hispanic women, and 0.28% among non-Hispanic White women; quarterly NTSV rates increased in 6 states. Conclusion: In addition to emergency preparedness planning, hospital monitoring, and reporting of NTSV cesarean rates to increase provider awareness, reallocation and prioritization of resources may help to identify potential strains on health care systems during public health emergencies such as the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: Stay-at-home orders were one of the controversial interventions to curb the spread of COVID-19 in the United States. The stay-at-home orders, implemented in 51 states and territories between March 7 and June 30, 2020, impacted the lives of individuals and communities and accelerated the heavy usage of web-based social networking sites. Twitter sentiment analysis can provide valuable insight into public health emergency response measures and allow for better formulation and timing of future public health measures to be released in response to future public health emergencies. Objective: This study evaluated how stay-at-home orders affect Twitter sentiment in the United States. Furthermore, this study aimed to understand the feedback on stay-at-home orders from groups with different circumstances and backgrounds. In addition, we particularly focused on vulnerable groups, including older people groups with underlying medical conditions, small and medium enterprises, and low-income groups. Methods: We constructed a multiperiod difference-in-differences regression model based on the Twitter sentiment geographical index quantified from 7.4 billion geo-tagged tweets data to analyze the dynamics of sentiment feedback on stay-at-home orders across the United States. In addition, we used moderated effects analysis to assess differential feedback from vulnerable groups. Results: We combed through the implementation of stay-at-home orders, Twitter sentiment geographical index, and the number of confirmed cases and deaths in 51 US states and territories. We identified trend changes in public sentiment before and after the stay-at-home orders. Regression results showed that stay-at-home orders generated a positive response, contributing to a recovery in Twitter sentiment. However, vulnerable groups faced greater shocks and hardships during the COVID-19 pandemic. In addition, economic and demographic characteristics had a significant moderating effect. Conclusions: This study showed a clear positive shift in public opinion about COVID-19, with this positive impact occurring primarily after stay-at-home orders. However, this positive sentiment is time-limited, with 14 days later allowing people to be more influenced by the status quo and trends, so feedback on the stay-at-home orders is no longer positively significant. In particular, negative sentiment is more likely to be generated in states with a large proportion of vulnerable groups, and the policy plays a limited role. The pandemic hit older people, those with underlying diseases, and small and medium enterprises directly but hurt states with cross-cutting economic situations and more complex demographics over time. Based on large-scale Twitter data, this sociological perspective allows us to monitor the evolution of public opinion more directly, assess the impact of social events on public opinion, and understand the heterogeneity in the face of pandemic shocks. [ABSTRACT FROM AUTHOR]