scholarly journals The Effect of Stay-at-Home Orders on COVID-19 Infections in the United States

2020 ◽  
Author(s):  
James H. Fowler ◽  
Seth J. Hill ◽  
Remy Levin ◽  
Nick Obradovich
Keyword(s):  
United States ◽  
Temporal Variation ◽  
Fixed Effects ◽  
National Level ◽  
The United States ◽  
Spatial And Temporal Variation ◽  
Full Potential ◽  
County Level ◽  
Fixed Effects Model ◽  
At Home

SummaryBackgroundIn March and April 2020, public health authorities in the United States acted to mitigate transmission of and hospitalizations from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). These actions were not coordinated at the national level, which raises the question of what might have happened if they were. It also creates an opportunity to use spatial and temporal variation to measure their effect with greater accuracy.MethodsWe combine publicly available data sources on the timing of stay-at-home orders and daily confirmed COVID-19 cases at the county level in the United States (N = 124,027). We then derive from the classic SIR model a two-way fixed-effects model and apply it to the data with controls for unmeasured differences between counties and over time. This enables us to estimate the effect of stay-at-home orders while accounting for local variation in factors like health systems and demographics, and temporal variation in national mitigation actions, access to tests, or exposure to media reports that could influence the course of the disease.FindingsMean county-level daily growth in COVID-19 infections peaked at 17.2% just before stay-at-home orders were issued. Two way fixed-effects regression estimates suggest that orders were associated with a 3.9 percentage point (95% CI 1.2 to 6.6) reduction in the growth rate after one week and a 6.9 percentage point (2.4 to 11.5) reduction after two weeks. By day 27 the reduction (22.6 percentage points, 14.8 to 30.5) had surpassed the growth at the peak, indicating that growth had turned negative and the number of new daily infections was beginning to decline. A hypothetical national stay-at-home order issued on March 13, 2020 when a national emergency was declared might have reduced cumulative infections by 63.3%, and might have helped to reverse exponential growth in the disease by April 10.InterpretationAlthough stay-at-home orders impose great costs to society, delayed responses and piecemeal application of these orders generate similar costs without obtaining the full potential benefits suggested by this analysis. The results here suggest that a coordinated nationwide stay-at-home order might have reduced by hundreds of thousands the current number of infections and by tens of thousands the total number of deaths from COVID-19. Future efforts in the United States and elsewhere to control pandemics should coordinate stay-at-home orders at the national level, especially for diseases for which local spread has already occurred and testing availability is delayed. Since stay-at-home orders reduce infection growth rates, early implementation when infection counts are still low would be most beneficial.FundingNone.

scholarly journals Stay-at-home orders associate with subsequent decreases in COVID-19 cases and fatalities in the United States

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0248849
Author(s):  
James H. Fowler ◽  
Seth J. Hill ◽  
Remy Levin ◽  
Nick Obradovich
Keyword(s):  
United States ◽  
Temporal Variation ◽  
National Level ◽  
Local Variation ◽  
The United States ◽  
Spatial And Temporal Variation ◽  
Difference In Differences ◽  
Contagious Diseases ◽  
Incident Cases ◽  
At Home

Governments issue “stay-at-home” orders to reduce the spread of contagious diseases, but the magnitude of such orders’ effectiveness remains uncertain. In the United States these orders were not coordinated at the national level during the coronavirus disease 2019 (COVID-19) pandemic, which creates an opportunity to use spatial and temporal variation to measure the policies’ effect. Here, we combine data on the timing of stay-at-home orders with daily confirmed COVID-19 cases and fatalities at the county level during the first seven weeks of the outbreak in the United States. We estimate the association between stay-at-home orders and alterations in COVID-19 cases and fatalities using a difference-in-differences design that accounts for unmeasured local variation in factors like health systems and demographics and for unmeasured temporal variation in factors like national mitigation actions and access to tests. Compared to counties that did not implement stay-at-home orders, the results show that the orders are associated with a 30.2 percent (11.0 to 45.2) average reduction in weekly incident cases after one week, a 40.0 percent (23.4 to 53.0) reduction after two weeks, and a 48.6 percent (31.1 to 61.7) reduction after three weeks. Stay-at-home orders are also associated with a 59.8 percent (18.3 to 80.2) average reduction in weekly fatalities after three weeks. These results suggest that stay-at-home orders might have reduced confirmed cases by 390,000 (170,000 to 680,000) and fatalities by 41,000 (27,000 to 59,000) within the first three weeks in localities that implemented stay-at-home orders.

scholarly journals Spatial and Temporal Variation in PM 2.5 Chemical Composition in the United States for Health Effects Studies

2007 ◽  
Vol 115 (7) ◽  
pp. 989-995 ◽  
Author(s):  
Michelle L. Bell ◽  
Francesca Dominici ◽  
Keita Ebisu ◽  
Scott L. Zeger ◽  
Jonathan M. Samet
Keyword(s):  
United States ◽  
Chemical Composition ◽  
Temporal Variation ◽  
Health Effects ◽  
The United States ◽  
Spatial And Temporal Variation ◽  
Pm 2.5

scholarly journals Is There a Male Marital Wage Premium? New Evidence from the United States

2018 ◽  
Vol 83 (4) ◽  
pp. 744-770 ◽  
Author(s):  
Volker Ludwig ◽  
Josef Brüderl
Keyword(s):  
United States ◽  
Panel Data ◽  
Fixed Effects ◽  
Causal Effect ◽  
Empirical Test ◽  
Wage Growth ◽  
The United States ◽  
Wage Premium ◽  
Fixed Effects Model ◽  
Married Men

This study reconsiders the phenomenon that married men earn more money than unmarried men, a key result of the research on marriage benefits. Many earlier studies have found such a “male marital wage premium.” Recent studies using panel data for the United States conclude that part of this premium is due to selection of high earners into marriage. Nevertheless, a substantial effect of marriage seems to remain. The current study investigates whether the remaining premium is really a causal effect. Using conventional fixed-effects models, previous studies statistically controlled for selection based on wage levels only. We suggest a more general fixed-effects model that allows for higher wage growth of to-be-married men. The empirical test draws on panel data from the National Longitudinal Survey of Youth (1979 to 2012). We replicate the main finding of the literature: a wage premium remains after controlling for selection on individual wage levels. However, the remaining effect is not causal. The results show that married men earn more because selection into marriage operates not only on wage levels but also on wage growth. Hence, men on a steep career track are especially likely to marry. We conclude that arguments postulating a wage premium for married men should be discarded.

Individualistic culture increases economic mobility in the United States

2021 ◽  
Vol 118 (37) ◽  
pp. e2107273118
Author(s):  
Bryan Leonard ◽  
Steven M. Smith
Keyword(s):  
United States ◽  
Fixed Effects ◽  
Causal Effect ◽  
The United States ◽  
County Level ◽  
Growing Up ◽  
Formal Policy ◽  
Modern Economic ◽  
Rugged Individualism ◽  
The 19Th Century

Where an individual grows up has large implications for their long-term economic outcomes, including earnings and intergenerational mobility. Even within the United States, the “causal effect of place” varies greatly and cannot be fully explained by socioeconomic conditions. Across different nations, variation in growth and mobility have been linked to more individualistic cultures. We assess how variation of historically driven individualism within the United States affects mobility. Areas in the United States that were isolated on the frontier for longer periods of time during the 19th century have a stronger culture of “rugged individualism” [S. Bazzi, M. Fiszbein, M. Gebresilasse, Econometrica 88, 2329–2368 (2020)]. We combine county-level measures of frontier experience with modern measures of the causal effect of place on mobility—the predicted percentage change in an individual’s earnings at age 26 y associated with “growing up” in a particular county [R. Chetty, N. Hendren, Q. J. Econ. 133, 1163–1228 (2018)]. Using commuting zone fixed effects and a suite of county-level controls to absorb regional variation in frontier experience and modern economic conditions, we find an additional decade of frontier experience results in 25% greater modern-day income mobility for children of parents in the 25th percentile of income and 14% for those born to parents in the 75th percentile. We use mediation analysis to present suggestive evidence that informal manifestations of “rugged individualism”—those embodied by the individuals themselves—are more strongly associated with upward mobility than formal policy or selective migration.

Obesity Is Inversely Associated With Natural Amenities and Recreation Facilities Per Capita

2013 ◽  
Vol 10 (7) ◽  
pp. 1032-1038 ◽  
Author(s):  
Stephanie B. Jilcott Pitts ◽  
Michael B. Edwards ◽  
Justin B. Moore ◽  
Kindal A. Shores ◽  
Katrina Drowatzky DuBose ◽  
...  
Keyword(s):  
United States ◽  
National Level ◽  
The United States ◽  
Economic Research ◽  
United States Department ◽  
County Level ◽  
Obesity Prevalence ◽  
Natural Amenities ◽  
Per Capita ◽  
Recreation Facilities

Background:Little is known about the associations between natural amenities, recreation facility density, and obesity, at a national level. Therefore, the purpose of this paper was to examine associations between county-level natural amenities, density of recreation facilities, and obesity prevalence among United States counties.Methods:Data were obtained from a compilation of sources within the United States Department of Agriculture Economic Research Service Food Environment Atlas. Independent variables of interest were the natural amenities scale and recreation facilities per capita. The dependent variable was county-level obesity prevalence. Potential covariates included a measure of county-level percent Black residents, percent Hispanic residents, median age, and median household income. All models were stratified by population loss, persistent poverty, and metro status. Multilevel linear regression models were used to examine the association between obesity and natural amenities and recreation facilities, with “state” as a random effects second level variable.Results:There were statistically significant negative associations between percent obesity and 1) natural amenities and 2) recreation facilities per capita.Conclusions:Future research should examine environmental and policy changes to increase recreation facilities and enhance accessible natural amenities to decrease obesity rates.

scholarly journals County-level exposures to greenness and associations with COVID-19 incidence and mortality in the United States

2020 ◽  
Author(s):  
Jochem O Klompmaker ◽  
Jaime E Hart ◽  
Isabel Holland ◽  
M Benjamin Sabath ◽  
Xiao Wu ◽  
...  
Keyword(s):  
United States ◽  
Population Density ◽  
Vegetation Index ◽  
Negative Binomial ◽  
The United States ◽  
Systems Science ◽  
County Level ◽  
Incidence And Mortality ◽  
The Us ◽  
At Home

AbstractBackgroundCOVID-19 is an infectious disease that has killed more than 246,000 people in the US. During a time of social distancing measures and increasing social isolation, green spaces may be a crucial factor to maintain a physically and socially active lifestyle while not increasing risk of infection.ObjectivesWe evaluated whether greenness is related to COVID-19 incidence and mortality in the United States.MethodsWe downloaded data on COVID-19 cases and deaths for each US county up through June 7, 2020, from Johns Hopkins University, Center for Systems Science and Engineering Coronavirus Resource Center. We used April-May 2020 Normalized Difference Vegetation Index (NDVI) data, to represent the greenness exposure during the initial COVID-19 outbreak in the US. We fitted negative binomial mixed models to evaluate associations of NDVI with COVID-19 incidence and mortality, adjusting for potential confounders such as county-level demographics, epidemic stage, and other environmental factors. We evaluated whether the associations were modified by population density, proportion of Black residents, median home value, and issuance of stay-at-home order.ResultsAn increase of 0.1 in NDVI was associated with a 6% (95% Confidence Interval: 3%, 10%) decrease in COVID-19 incidence rate after adjustment for potential confounders. Associations with COVID-19 incidence were stronger in counties with high population density and in counties with stay-at-home orders. Greenness was not associated with COVID-19 mortality in all counties; however, it was protective in counties with higher population density.DiscussionExposures to NDVI had beneficial impacts on county-level incidence of COVID-19 in the US and may have reduced county-level COVID-19 mortality rates, especially in densely populated counties.

scholarly journals Quantifying the mortality impact of the 1935 old-age assistance

2021 ◽  
Author(s):  
Gregori Galofré-Vilà ◽  
Martin McKee ◽  
David Stuckler
Keyword(s):  
United States ◽  
Old Age ◽  
Event Study ◽  
Fixed Effects ◽  
Older Persons ◽  
The Elderly ◽  
The United States ◽  
County Level ◽  
Level Data ◽  
Old Age Assistance

Abstract In 1935, the United States introduced the old-age assistance (OAA) program, a means-tested program to help the elderly poor. The OAA improved retirement conditions and aimed to enable older persons to live independently. We use the transition from early elderly plans to OAA and the large differences in payments and eligibility across states to show that OAA reduced mortality by between 30 and 39 percent among those older than 65 years. This finding, based on an event study design, is robust to a range of specifications, a range of fixed effects, placebo tests, and a border-pair policy discontinuity design using county-level data. The largest mortality reductions came from drops in communicable and infectious diseases, such as influenza and nephritis, and mostly affected white citizens.

The Effect of Temperature on the Incidence Rate of COVID19

2021 ◽  
Author(s):  
Emanuele Massetti ◽  
Eric Dobbie ◽  
Wei Yang ◽  
Kamran Paynabar
Keyword(s):  
United States ◽  
Incidence Rate ◽  
National Level ◽  
The United States ◽  
Effect Of Temperature ◽  
County Level ◽  
Weather Variables ◽  
Us States ◽  
Monthly Average ◽  
Lower Incidence Rate

Abstract In this paper, we exploit random variation of daily temperature in the United States at both state and county level, from March 1st to October 31st 2020, to study if temperature has a significant effect on COVID19 incidence rate. We find that warmer than average days lead to a lower incidence rate, seven days later. A week in which temperature is consistently one standard deviation above the monthly average in all US states causes 17,754 fewer cases at national level, seven days later. Other weather variables do not have a significant and robust effect on the incidence rate. The effect of temperature is heterogeneous over space and time.

scholarly journals Prekindergarten and Kindergarten Center-based Child Care and Students’ Early Schooling Outcomes

2015 ◽  
Vol 117 (11) ◽  
pp. 1-28 ◽  
Author(s):  
Michael A. Gottfried
Keyword(s):  
United States ◽  
Child Care ◽  
Fixed Effects ◽  
Research Question ◽  
National Level ◽  
Empirical Work ◽  
The United States ◽  
Self Control ◽  
Achievement Outcomes ◽  
Socioemotional Outcomes

Background/Context In the United States, there has been an increased trend in parents’ utilization of center-based child care. Yet, though research has examined the effects of attending prekindergarten center-based care or the effects of attending center-based care during the kindergarten school year, little is known about the effects of having attended both. Purpose/Objective This study asks three questions: (a) Do children who attend both prekin-dergarten and kindergarten center-based care have different achievement outcomes, measured at the end of kindergarten? (b) Do children who attend both prekindergarten and kindergarten center-based care have different socioemotional outcomes, measured at the end of kindergarten? (c) Do these relationships differ by individual socio-demographic characteristics? Population/Participants This study utilizes data from the newly released Early Childhood Longitudinal Study – Kindergarten Class of 2011 (ECLS-K:2011). The ECLS-K:2011 represents the most contemporary national-level data available to study the educational experiences of young students in the United States. Information was first collected from kindergartners (as well as parents, teachers, and school administrators) from U.S. kindergarten programs in the year 2010–2011. Research Design This study combines secondary data analyses and quasi-experimental methods. There are two achievement outcomes: reading and math. There are five socioemotional outcomes: externalizing behaviors, internalizing behaviors, self-control, approaches to learning, and interpersonal skills. The study begins with a baseline, linear regression model. To address issues pertaining to omitted variable bias, the study employs various fixed-effects models. Findings The findings for the first research question indicated that academic outcomes do not differ for children in both years of center-based care compared to children who attended only one year of center-based care or none at all. As for the second research question, the findings show that multiple years of center-based care is related to increases in problem behaviors and decreases in prosocial behaviors—outcomes that are worsened by the number of years of center-based care attendance. The findings for the third research question suggest some minor differences between boys and girls in zero, one, or two years of center-based care. Conclusions/Recommendations This study has brought to surface new ways that center-based care attendance might influence children's short-term outcomes. Therefore, researchers, policymakers, and practitioners must base future questions on empirical work concerning how to address children's outcomes across multiple years of care, rather than simply focus exclusively on one year's influence.

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