Background The economic, psychological, and social impact of pandemics and social distancing measures prompt the urgent need to determine the efficacy of non-pharmaceutical interventions (NPIs), especially those considered most stringent such as stay-at-home and self-isolation mandates. This study focuses specifically on the impact of stay-at-home orders, both nationally and internationally, on the control of COVID-19. Methods We conducted an observational analysis from April to May 2020 and included both countries and US states with known stay-at-home orders. Our primary exposure was the time between the date of the first reported case of COVID-19 to an implemented stay-at-home mandate for each region. Our primary outcomes were the time from the first reported case to the highest number of daily cases and daily deaths. We conducted linear regression analyses, controlling for the case rate of the outbreak in each respective region. Results For countries and US states, a longer period of time between the first reported case and stay-at-home mandates was associated with a longer time to reach both the peak daily case and death counts. The largest effect was among regions classified as the latest 10% to implement a mandate, which in the US, predicted an extra 35.3 days (95% CI: 18.2, 52.5) to the peak number of cases, and 38.3 days (95% CI: 23.6, 53.0) to the peak number of deaths. Conclusions Our study supports the association between the timing of stay-at-home orders and the time to peak case and death counts for both countries and US states. Regions in which mandates were implemented late experienced a prolonged duration to reaching both peak daily case and death counts.
BACKGROUND: The many economic, psychological, and social consequences of pandemics and social distancing measures create an urgent need to determine the efficacy of non-pharmaceutical interventions (NPIs), and especially those considered most stringent, such as stay-at-home and self-isolation mandates. This study focuses specifically on the efficacy of stay-at-home orders, both nationally and internationally, in the control of COVID-19. METHODS: We conducted an observational analysis from April to May 2020 and included countries and US states with known stay-at-home orders. Our primary exposure was the time between the date of the first reported case of COVID-19 to an implemented stay-at-home mandate for each region. Our primary outcomes were the time from the first reported case to the highest number of daily cases and daily deaths. We conducted simple linear regression analyses, controlling for the case rate of the outbreak. RESULTS: For US states and countries, a larger number of days between the first reported case and stay-at-home mandates was associated with a longer time to reach the peak daily case and death counts. The largest effect was among regions classified as the latest 10% to implement a mandate, which in the US, predicted an extra 35.3 days to the peak number of cases (95 % CI: 18.2, 52.5), and 38.3 days to the peak number of deaths (95 % CI: 23.6, 53.0). CONCLUSIONS: Our study supports the potential beneficial effect of earlier stay-at-home mandates, by shortening the time to peak case and death counts for US states and countries. Regions in which mandates were implemented late experienced a prolonged duration to reaching both peak daily case and death counts.
Background: One of the unforeseen impacts of the COVID-19 pandemic has been a decrease in athletes’ confidence to return to their sport after mandates were lifted. Both physical and psychological effects have been implicated. This study aimed to measure the severity of these changes among a group of National Collegiate Athletic Association (NCAA) athletes. Methods: A novel Readiness to Return to Sport Survey, based on the validated ACL-RSI survey, was distributed to Division 1 collegiate athletes. The survey evaluated the psychological readiness of each player to return to sport in the context of the COVID-19 pandemic, utilizing a 1-10 scale (1 = least confident and 10 = most confident). Numerical responses to each survey were summed to create a primary outcome score-an athlete’s Return to Sport Readiness Score . Higher scores indicate higher levels of readiness to return to sport in the nearest coming season. Results: Responses came from 68 athletes representing a variety of sports. Of those with an injury, 14 (82.35%) attributed their injury to changes in their training schedule due to COVID-19 restrictions, and the remaining three (17.65%) did not. Among all athletes, the mean return to sport readiness (RTS) score was 44 (SD 24.76). Those playing a winter sport had the lowest mean RTS score, 35 ± 23, and those playing a fall season sport had the highest mean score, 48 ± 25.97. Overall, competitive athletes on leave from the sport due to collegiate and Division 1 COVID-19 guidelines had lower reported mean RTS scores as compared to athletes outlined in many other anterior cruciate ligament return to sport after injury survey (ACL-RSI) studies. Conclusions: Overall, the athletes surveyed in our study reported much lower levels of readiness to return to sport in the context of COVID-19 than athletes surveyed in other studies, exhibiting COVID-19’s unique impact on their confidence to return to their scheduled sport season. These differences may highlight the COVID-19 pandemic as a more severe detriment to returning to sport readiness among division-one athletes than recovering from injury alone. Given such an impact, more research is needed to elucidate the percentage of these athletes that returned to or abstained from their sport, as well as any motivating, facilitating, or detrimental factors in their choice.
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