State and territorial executive orders, administrative orders, resolutions, proclamations, and other official publicly available government communications are collected from government websites and cataloged and coded using Microsoft Excel by one or more coders with one or more additional coders conducting quality assurance.

Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, proclamations, and other official publicly available government communications related to COVID-19 banning gatherings of various sizes either (1) generally, or specified that the gathering limit applied only when social distancing was not possible, or (2) even if participants practiced social distancing.

These data are derived from on the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly ban gatherings found by the CDC, COVID-19 Community Intervention and Critical Populations Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded, as well as official government communications such as announcements that counties have progressed through new phases of reopening pursuant to an executive order, directive, or other executive branch action, and posted to government websites; news media reports on restrictions were excluded. Recommendations and guidance documents not included or adopted by reference in an order are not included in these data. These data do not include mandatory business closures, curfews, or requirements/recommendations for people to stay in their homes. Due to limitations of the National Environmental Public Health Tracking Network Data Explorer, these data do not include tribes or cities, nor was a distinction made between county orders that applied county-wide versus those that were limited to unincorporated areas of the county. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

We explore the US states' evolving policy responses to the COVID-19 pandemic by examining governors’ decisions to begin easing five types of social distancing policies after the initial case surge in March--April 2020. Applying event history models to original data on state COVID-19 policies, we test the relative influence of health, economic, and political considerations on their decisions. We find no evidence that differences in state economic conditions influenced when governors began easing. Governors of states with larger recent declines in COVID-19 deaths per capita and improving trends in new confirmed cases and test positivity were quicker to ease. However, politics played as powerful a role as epidemiological conditions, driven primarily by governors' party affiliation. Republican governors made the policy U-turn from imposing social distancing measures toward easing those measures a week earlier than Democratic governors, all else equal. Most troubling of all, we find that states with larger Black populations eased their social distancing policies more quickly, despite Black Americans' higher exposure to infection from SARS-CoV-2 and subsequent death from COVID-19.

Citation: Sanchez, JN, GA Reyes, BM Lopez, CK Johnson. 2022. The impact of social distancing on early SARS-CoV-2 transmission in the United States. Zoonoses and Public Health. https://doi. org/10.1111/zph.12909

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a viral pathogen that quickly became a global pandemic in the winter of 2020 – 2021. In response, governments issued social distancing orders to minimize transmission by reducing community contacts. We tested the efficacy of this social distancing at the state level during the first two months of the pandemic in the United States. We utilized data on daily SARS-CoV-2 case numbers and human community mobility (anonymized, aggregated cellphone location data stratified into six categories used as an index of social distancing), the date of government-issued social distancing orders, demographics, urbanization, and public transportation. We implemented cross-correlation to identify lag times between declines in mobility and SARS-CoV-2 cases. Incorporating state-specific lag times, we tested for associations between case counts and mobility metrics using Bayesian multilevel models. Decreased mobility around grocery stores/pharmacies, retail/recreation locations, transit stations, and workplaces were correlated with decreases in SARS-CoV-2 cases with significant lag times of ≥21 days. Social distancing orders were associated with fewer cumulative SARS-CoV-2 cases when they were put in place earlier. Community mobility had already started declining prior to most social distancing orders, especially the more restrictive orders implemented later in the pandemic. Social distancing is an important tool that has been implemented throughout the pandemic to decrease SARS-CoV-2 transmission, although with significant social and economic impacts. Our results suggest that declines in cases were observed several weeks subsequent to implementation of social distancing measures, and that implementing social distancing earlier could potentially minimize the duration of time these policies need to be in effect. Our findings can inform ongoing management of this pandemic and other emerging infectious disease outbreaks by identifying areas where reductions in mobility are associated with reduced disease transmission, and the expected time frame between behavioral changes and measurable population outcomes.

Social distancing measures have been widely adopted to mitigate the COVID-19 pandemic. However, little is known about the timing of measures’ implementation, scope, and duration in relation to their impact. The study aimed to describe the social distancing measures implemented by Brazil’s states and the Federal District, including the types of measures and the timing of their implementation. This is a descriptive study of the measures’ type, chronological and epidemiological timing of the implementation, and scope. The survey of measures used searches in official websites of the government departments and each state’s Government Register. The official number of COVID-19 cases and deaths were obtained from an official a data platform. We considered the following categories of social distancing measures: suspension of events, school closure, quarantine of risk groups, economic lockdown (partial or full), restrictions on transportation, and quarantine of the population. The implementation’s timing considered both the chronological date and the epidemiological timing, based on the time since the 10th case or 1st death from COVID-19 in each state. All the states implemented distancing measures, mostly during the latter half of March 2020. Economic lockdown was implemented early, prior to the 10th case by 67% of the states and prior to the 1st death from COVID-19 by 89% of the states. Early social distancing measures were widely implemented in Brazil, before or in the initial phase of the exponential growth curve of COVID-19 cases and deaths in the great majority of states.

Data was collected via survey that examined the perceptions, behaviors, and impacts surrounding COVID-19 early in the pandemic response. Attitudes toward media, government, and community responses to COVID-19 by political ideology and sociodemographic factors including knowledge, anxieties, and impacts of COVID-19 were assessed. Data is accessible to people who have an OPEN ICPSR account.

This dataset contains dates for the implementations of the following interventions in 50 US states plus Shelby County TN in response to COVID-19. Each intervention date has an associated comment containing sources for that date and a rationale when the decision was not strictly objective. Interventions are valid to 4/25/20 after which some states began to reverse some interventions.

schools_universities

Primary/secondary school closing; partial closing is OK; State university closing if it precedes primary/secondary

travel_restrictions

Out of state travel quarantine restrictions OR state-level guidance to avoid traveling out of state

public_events

Banning of ALL public events of more than 100 participants

sport

Banning/canceling of sporting events. Banning of public events of 1000 or more also qualifies.

lockdown

Definitions vary, but include: banning of non-essential gatherings/business operations, ordering stay at home except for exercise and essential tasks; stay at home/safer at home orders

Lockdown encompasses all other intervensions by definition, so if a state skips multiple interventions and goes to lockdown, the lockdown date is used for those interventions as well.

social_distancing_encouraged

State advice on distancing including: work from home, reduce public transport, avoid non-essential contact; any guidance for maintaining a physical distance from others will also qualify. Mere words "social distancing" do not count unless they are elaborated with what that means in practice. Messaging must be to public and not selected group (e.g. state employees).

self_isolating_if_ill

Strong recommendations/laws about self-isolating if showing COVID like symptoms; Statewide testing implies this, so whichever comes first. Messaging must be to public and not selected group (e.g. state employees).

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when members of the public in states and territories were subject to state and territorial executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require them to wear masks in public. “Members of the public” are defined as individuals operating in a personal capacity. “In public” is defined to mean either (1) anywhere outside the home or (2) both in retail businesses and in restaurants/food establishments. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require individuals to wear masks in public found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program, and Max Gakh, Assistant Professor, School of Public Health, University of Nevada, Las Vegas from April 10, 2020 through July 20, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the dates provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not include data on counties that have opted out of their state mask mandate pursuant to state law. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

Staying home and avoiding unnecessary contact is an important part of the effort to contain COVID-19 and limit deaths. Every state in the United States enacted policies to encourage distancing and some mandated staying home. Understanding how these policies interact with individuals’ voluntary responses to the COVID-19 ep- idemic is a critical initial step in understanding the role of these nonpharmaceutical interventions in transmission dynamics and assessing policy impacts. We use variation in policy responses along with smart device data that measures the amount of time Americans stayed home to disentangle the extent that observed shifts in staying home behavior are induced by policy. We find evidence that stay-at-home orders and voluntary response to locally reported COVID-19 cases and deaths led to behavioral change. For the median county, which implemented a stay-at-home order with about two cases, we find that the response to stay-at-home orders increased time at home as if the county had experienced 29 addi- tional local cases. However, the relative effect of stay-at-home or- ders was much greater in select counties. On the one hand, the mandate can be viewed as displacing a voluntary response to this rise in cases. On the other hand, policy accelerated the response, which likely helped reduce spread in the early phase of the pan- demic. It is important to be able to attribute the relative role of self- interested behavior or policy mandates to understand the limits and opportunities for relying on voluntary behavior as opposed to im- posing stay-at-home orders.

Dataset

This dataset was created by Rodrigo Fracalossi

Contents

Management of the COVID-19 pandemic has proven to be a significant challenge to policy makers. This is in large part due to uneven reporting and the absence of open-access visualization tools to present and analyze local trends as well as infer healthcare needs. Here we report the development of CovidCounties.org, an interactive web application that depicts daily disease trends at the level of US counties using time series plots and maps. This application is accompanied by a manually curated dataset that catalogs all major public policy actions made at the state-level, as well as technical validation of the primary data. Finally, the underlying code for the site is also provided as open source, enabling others to validate and learn from this work.

Federal and local government agencies were quick to issue orders for residents to shelter-in-place in response to the COVID-19 outbreak. This study utilized data collected from Unacast Inc., spanning observations of 3,142 counties across 50 states and the District of Columbia (N = 230,846) from March 8, 2020 to April 13, 2020 (n = 104,930) and from April 14, 2020 to May 24, 2020 (n = 131,912) in a 3-level multilevel model to examine the correlates of social distancing behavior, as measured by the relative reduction in (1) distance traveled and (2) non-essential visitations since baseline pre-COVID-19 times. Results showed that educational attainment and political partisanship were the most consistent correlates of social distancing. State-level indicators of culture appeared to have differentiated effects depending on whether the model outcomes were reduction in general mobility or to non-essential venues. State-level neuroticism was generally positively related to social distancing, but states marked by high neuroticism were slower to engage in such behaviors. Counties and states characterized as already engaging in preventive health measures (e.g., vaccination rates, preparedness for at-risk populations) enjoyed quicker engagement in social distancing. Specific implications of findings and future directions are discussed.

What are the long-run economic impacts of the policy responses to control pandemics? We investigate this question by exploiting state-collected data spanning one of the most consequential global pandemics in centuries, the 1918 influenza pandemic. Specifically, we use a difference-in-differences framework to examine the effects of non-pharmaceutical interventions.

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when bars in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when bars in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen bars found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen restaurants found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

State government responsiveness to COVID-19.

This study aims at quantifying human mobility behavior changes during the COVID-19 outbreak in the United States. We developed the Social Distancing Index (SDI) to evaluate people’s mobility pattern changes along with the spread of COVID-19 at different geographic levels. The SDI scores are based on the five basic mobility metrics derived from mobile device location data.

Both datasets and code used to conduct all analyses in this paper.

This dataset contains information on the strictness of social distancing measures against COVID-19 in the 27 Brazilian states, covering the period from 11th Mar 2020 to 10th Nov 2020 (the whole first wave of the pandemic in Brazil). There are data on individual social distancing measures, divided into six types of restrictions: 1) gatherings, sports, cultural and religious events; 2) non-essential shops; 3) bars and restaurants; 4) non-essential industry; 5) schools; and 6) public transportation. There are also data on mandaotry masking and control variables. These data can be used to replicate findings of the article 'Effects of non-pharmaceutical interventions on social distancing during the COVID-19 pandemic: Evidence from the 27 Brazilian states', to be published in PLOS One.

Introduction

Intensive care has played a pivotal role during the COVID-19 pandemic as many patients developed severe pulmonary complications. The availability of information in pediatric intensive care (PICUs) remains limited. The purpose of this study is to characterize COVID-19 positive admissions (CPAs) in the United States and to determine factors that may impact those admissions.

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Materials and Methods

This is a retrospective cohort study using data from the COVID-19 dashboard virtual pediatric system) containing information regarding respiratory support and comorbidities for all CPAs between March and April 2020. The state level data contained 13 different factors from population density, comorbid conditions and social distancing score. The absolute CPAs count was converted to frequency using the state’s population. Univariate and multivariate regression analyses were performed to assess the association between CPAs frequency and endpoints.

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Results

A total ...

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen restaurants found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.