scholarly journals Policy and Environmental Predictors of Park Visits During the First Months of the COVID-19 Pandemic: Getting Out While Staying in

2021 ◽  
pp. 001391652110311
Author(s):  
David S. Curtis ◽  
Alessandro Rigolon ◽  
Dorothy L. Schmalz ◽  
Barbara B. Brown
Keyword(s):  
Growth Rate ◽  
Human Health ◽  
Cell Phone ◽  
Environmental Predictors ◽  
School Closures ◽  
Park Use ◽  
Location Data ◽  
At Home ◽  
Recreation And Leisure

The COVID-19 pandemic may have altered visitation patterns to parks, with potential effects on human health. Little is known about park use early in the pandemic, how park availability influenced use, and whether park visits accelerated COVID-19 spread. Using weekly cell phone location data for 620 U.S. counties, we show park visits decreased by an average 26% between March 15 and May 9, 2020. Net of weekly trends, park visits were 2.2% lower when stay-at-home orders were in effect, yet increased by 8.4% with school closures and 4.4% with business closures. Park visits decreased less during the pandemic in counties where park availability was high. Levels of park visits were not associated with COVID-19 growth rate or incidence in the following weeks. Thus, parks served as recreation and leisure outlets when schools and businesses closed, especially where parks were more available, with no evidence of park use increasing COVID-19 spread.

scholarly journals Getting out while staying in: Policy and environmental predictors of park visits during the first months of the COVID-19 pandemic

2020 ◽  
Author(s):  
David Stuart Curtis ◽  
Alessandro Rigolon ◽  
Dorothy L Schmalz ◽  
Barbara Brown
Keyword(s):  
Growth Rate ◽  
Well Being ◽  
Public Spaces ◽  
After School ◽  
Environmental Predictors ◽  
School Closures ◽  
Park Use ◽  
Weekly Sample ◽  
Metropolitan Counties ◽  
Health And Well Being

The spread of COVID-19 altered use of public spaces, such as parks, with potential effects on human health and well-being. Little is known about park use during the pandemic, how local features (e.g, park availability) influence use, and whether park visits accelerate COVID-19 spread. Using weekly panel data for 620 U.S. counties, we show park visits decreased by 10% beginning March 15, and by 17-35% through May 9, 2020. Net of weekly sample trends, park visits decreased by 2.3% when stay-at-home orders were in effect, yet increased by 8.3% after school closures and 4.1% after business closures. Park visits decreased less during the pandemic in metropolitan counties or where park availability was high. Higher park visits were weakly associated with COVID-19 case growth rate but not incidence. Thus, parks may serve as alternatives for recreation when schools and businesses close, especially where parks are available, with no-to-little influence on COVID-19 spread.

scholarly journals Association of cell phone location data and trends in COVID-19 infections during loosening of stay-at-home restrictions

2020 ◽  
Vol 27 (8) ◽  
Author(s):  
Shiv T Sehra ◽  
Louis J Kishfy ◽  
Alexander Brodski ◽  
Michael D George ◽  
Douglas J Wiebe ◽  
...  
Keyword(s):  
Cell Phone ◽  
Location Data ◽  
At Home

scholarly journals Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction

2020 ◽  
Author(s):  
Phebo Wibbens ◽  
Wesley Wu-Yi Koo ◽  
Anita M. McGahan
Keyword(s):  
Growth Rate ◽  
Bayesian Analysis ◽  
Large Scale ◽  
Control Strategies ◽  
Relative Effectiveness ◽  
International Travel ◽  
School Closures ◽  
Information Campaigns ◽  
Public Events ◽  
At Home

AbstractThis paper reports the results of a Bayesian analysis on large-scale empirical data to assess the effectiveness of eleven types of COVID-control policies that have been implemented at various levels of intensity in 40 countries and U.S. states since the onset of the pandemic. The analysis estimates the marginal impact of each type and level of policy as implemented in concert with other policies. The purpose is to provide policymakers and the general public with an estimate of the relative effectiveness of various COVID-control strategies. We find that a set of widely implemented core policies reduces the spread of virus but not by enough to contain the pandemic except in a few highly compliant jurisdictions. The core policies include the cancellation of public events, restriction of gatherings to fewer than 100 people, recommendation to stay at home, recommended restrictions on internal movement, implementation of a partial international travel ban, and coordination of information campaigns. For the median jurisdiction, these policies reduce growth rate in new infections from an estimated 270% per week to approximately 49% per week, but this impact is insufficient to prevent eventual transmission throughout the population because containment occurs only when a jurisdiction reduces growth in COVID infection to below zero. Most jurisdictions must also implement additional policies, each of which has the potential to reduce weekly COVID growth rate by 10 percentage points or more. The slate of these additional high-impact policies includes targeted or full workplace closings for all but essential workers, stay-at-home requirements, and targeted school closures.

scholarly journals Which COVID policies are most effective? A Bayesian analysis of COVID-19 by jurisdiction

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244177
Author(s):  
Phebo D. Wibbens ◽  
Wesley Wu-Yi Koo ◽  
Anita M. McGahan
Keyword(s):  
Growth Rate ◽  
Bayesian Analysis ◽  
Large Scale ◽  
Control Strategies ◽  
Relative Effectiveness ◽  
International Travel ◽  
School Closures ◽  
Information Campaigns ◽  
Public Events ◽  
At Home

This paper reports the results of a Bayesian analysis on large-scale empirical data to assess the effectiveness of eleven types of COVID-control policies that have been implemented at various levels of intensity in 40 countries and U.S. states since the onset of the pandemic. The analysis estimates the marginal impact of each type and level of policy as implemented in concert with other policies. The purpose is to provide policymakers and the general public with an estimate of the relative effectiveness of various COVID-control strategies. We find that a set of widely implemented core policies reduces the spread of virus but not by enough to contain the pandemic except in a few highly compliant jurisdictions. The core policies include the cancellation of public events, restriction of gatherings to fewer than 100 people, recommendation to stay at home, recommended restrictions on internal movement, implementation of a partial international travel ban, and coordination of information campaigns. For the median jurisdiction, these policies reduce growth rate in new infections from an estimated 270% per week to approximately 49% per week, but this impact is insufficient to prevent eventual transmission throughout the population because containment occurs only when a jurisdiction reduces growth in COVID infection to below zero. Most jurisdictions must also implement additional policies, each of which has the potential to reduce weekly COVID growth rate by 10 percentage points or more. The slate of these additional high-impact policies includes targeted or full workplace closings for all but essential workers, stay-at-home requirements, and targeted school closures.

scholarly journals The Impact of Policy Measures on Human Mobility, COVID-19 Cases, and Mortality in the US: A Spatiotemporal Perspective

2021 ◽  
Vol 18 (3) ◽  
pp. 996
Author(s):  
Yun Li ◽  
Moming Li ◽  
Megan Rice ◽  
Haoyuan Zhang ◽  
Dexuan Sha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Human Mobility ◽  
Public Information ◽  
Key Factors ◽  
Information Campaigns ◽  
Rapid Spread ◽  
The Us ◽  
Policy Measures ◽  
The Impact ◽  
At Home

Social distancing policies have been regarded as effective in containing the rapid spread of COVID-19. However, there is a limited understanding of policy effectiveness from a spatiotemporal perspective. This study integrates geographical, demographical, and other key factors into a regression-based event study framework, to assess the effectiveness of seven major policies on human mobility and COVID-19 case growth rates, with a spatiotemporal emphasis. Our results demonstrate that stay-at-home orders, workplace closures, and public information campaigns were effective in decreasing the confirmed case growth rate. For stay-at-home orders and workplace closures, these changes were associated with significant decreases (p < 0.05) in mobility. Public information campaigns did not see these same mobility trends, but the growth rate still decreased significantly in all analysis periods (p < 0.01). Stay-at-home orders and international/national travel controls had limited mitigation effects on the death case growth rate (p < 0.1). The relationships between policies, mobility, and epidemiological metrics allowed us to evaluate the effectiveness of each policy and gave us insight into the spatiotemporal patterns and mechanisms by which these measures work. Our analysis will provide policymakers with better knowledge regarding the effectiveness of measures in space–time disaggregation.

scholarly journals Cooking at Home, Fast Food, Meat Consumption, and Dietary Carbon Footprint among US Adults

2022 ◽  
Vol 19 (2) ◽  
pp. 853
Author(s):  
Julia A. Wolfson ◽  
Amelia M. Willits-Smith ◽  
Cindy W. Leung ◽  
Martin C. Heller ◽  
Donald Rose
Keyword(s):  
Human Health ◽  
Carbon Footprint ◽  
Diet Quality ◽  
Environmental Sustainability ◽  
Fast Food ◽  
Dietary Recall ◽  
Health And Nutrition ◽  
Recall Data ◽  
Eating Fast ◽  
At Home

Shifting consumer behavior towards more sustainable diets can benefit environmental sustainability and human health. Although more frequent home cooking is associated with a better diet quality and fast-food consumption with worse diet quality, the environmental impact of diets based on frequency of cooking or eating fast food is not well understood. The objective of this study was to investigate whether the frequency of cooking dinner at home or eating fast food is associated with dietary greenhouse gas emissions (GHGE). We linked 24-h dietary recall data from adult respondents in the 2007–2010 National Health and Nutrition Examination Survey (NHANES) (N = 11,469) to a database of GHGE factors to obtain a measure of dietary GHGE (kgCO2-eq/2000 kcal) (the sum of emissions released in the production of food for an individual’s diet), adjusted by energy intake (kgCO2-eq/2000 kcal). We examined associations between frequency of cooking dinner (the only meal for which cooking frequency was measured), frequency of eating fast food, and dietary GHGE and protein sources (beef, pork, poultry, other meat, and fish and seafood (g/2000 kcal)) using generalized linearized regression models that controlled for age, sex, and other socio-economic characteristics. Greater cooking frequency was associated with higher dietary GHGE. In fully adjusted models, cooking 5–6 times/week was associated with an additional 0.058 kgCO2-eq/2000 kcal (SE 0.033) and cooking 7 times/week was associated with an additional 0.057 kgCO2-eq/2000 kcal (SE 0.027) when compared to cooking 0–2 times/week. Individuals in households who cooked dinner more frequently consumed significantly more meat, poultry, and fish (cooking 7 times/week: 148.7 g/2000 kcal vs. cooking 0–2 times/week: 135.4 g/2000 kcal, p-trend = 0.005), which could explain the association with a higher carbon footprint diet. There were few associations of note between fast-food frequency and GHGE. Policies and interventions that reduce consumption of meat and increase consumption of plants when both cooking meals at home and eating meals out are needed to shift toward diets that will be beneficial for both human health and the health of the planet.

scholarly journals A Spatio-Temporal Investigation of the Growth Rate of COVID-19 Incidents in Ohio, USA, Early in the Pandemic

2021 ◽  
Vol 121 (2) ◽  
pp. 33-47
Author(s):  
Alessandro M. Selvitella ◽  
Liam Carolan ◽  
Justin Smethers ◽  
Christopher Hernandez ◽  
Kathleen L. Foster
Keyword(s):  
Growth Rate ◽  
Transmission Rate ◽  
Time Lag ◽  
Early Period ◽  
Mitigation Strategies ◽  
Initial Growth ◽  
School Closures ◽  
Policy Makers ◽  
Susceptible Population ◽  
Spatio Temporal

Understanding the initial growth rate of an epidemic is important for epidemiologists and policy makers as it can impact their mitigation strategies such as school closures, quarantines, or social distancing. Because the transmission rate depends on the contact rate of the susceptible population with infected individuals, similar growth rates might be experienced in nearby geographical areas. This research determined the growth rate of cases and deaths associated with COVID-19 in the early period of the 2020 pandemic in Ohio, United States. The evolution of cases and deaths was modeled through a Besag-York-Molliè model with linear- and power-type deterministic time dependence. The analysis showed that the growth rate of the time component of the model was subexponential in both cases and deaths once the time-lag across counties of the appearance of the first COVID-19 case was considered. Moreover, deaths in the northeast counties in Ohio were strongly related to the deaths in nearby counties.

scholarly journals Time Spent on School-Related Activities at Home During the Pandemic: A Longitudinal Analysis of Social Group Inequality Among Secondary School Students

2021 ◽  
Vol 12 ◽  
Author(s):  
Sabine Zinn ◽  
Michael Bayer
Keyword(s):  
Educational Inequality ◽  
Economic Status ◽  
Policy Implications ◽  
Educational Inequalities ◽  
School Students ◽  
Theoretical Assumption ◽  
School Closures ◽  
Parental Educational Attainment ◽  
Group Inequality ◽  
At Home

Substantial educational inequalities have been documented in Germany for decades. In this article, we examine whether educational inequalities among children have increased or remained the same since the school closures of spring 2020 due to the COVID-19 pandemic. Our perspective is longitudinal: We compare the amount of time children in secondary schools spent on school-related activities at home before the pandemic, during school closures, and immediately after returning to in-person learning. We operationalize family socio-economic status using the highest parental educational attainment. Based on the theoretical assumption that the pandemic affected everyone equally, we formulate a hypothesis of equalization during the first period of school closures. For the period thereafter, however, we assume that parents with a low level of education had more difficulties bearing the additional burden of supervising and supporting their children’s learning activities. Thus, for that period, we postulate an increase in educational inequality. To study our hypotheses, we use data from the 2019 wave of the SOEP and the SOEP-CoV study, both of which are probability samples. The SOEP-CoV study provides a unique database, as it was conducted during the lockdown of spring 2020 and in the following month. For statistical analysis, we use probit regressions at three measurement points (in 2019, in 2020 during the school closures, and in the month after closures). The comparison of these three time points makes our analysis and findings unique in the research on education during the COVID-19 pandemic, in particular with regard to Germany-wide comparisons. Our results confirm the hypothesis of equalization during the first school closures and the hypothesis of an increase in educational in the subsequent period. Our findings have direct policy implications regarding the need to further expand support systems for children.

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