scholarly journals Mining and Validating Social Media for COVID-19-Related Human Behaviors between January and July; An Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Ashlynn R. Daughton ◽  
Courtney Diane Shelley ◽  
Martha Barnard ◽  
Dax Gerts ◽  
Chrysm Watson Ross ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Ground Truth ◽  
The United States ◽  
Training Data ◽  
Long Term Effects ◽  
Social Distancing ◽  
Human Behaviors ◽  
Mobility Data ◽  
The Impact

BACKGROUND Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging is also important for minimizing long term effects of an outbreak. OBJECTIVE We used social media data to identify human behaviors relevant to COVID-19 transmission and the perceived impacts of COVID-19 on individuals as a first step toward real time monitoring of public perceptions to inform public health communications. METHODS We develop a coding schema for 6 categories and 11 subcategories, which includes both a wide number of behaviors, as well codes focused on the impacts of the pandemic (e.g., economic and mental health impacts). We use this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that perform adequately are applied to our remaining corpus and temporal and geospatial trends are assessed. We compare the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. RESULTS We apply our labeling schema to ~7200 tweets. The worst performing classifiers have F1 scores of only 0.18-0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, are much stronger with F1 scores of 0.64-0.66. We applied the social distancing classifiers to over 228 million tweets. We show temporal patterns consistent with real-world events, and show correlations of up to -0.5 between social distancing signals on Twitter and ground-truth mobility throughout the United States. CONCLUSIONS Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior as well as informing public health communication strategies by describing awareness of and compliance with suggested behaviors. CLINICALTRIAL N/A

scholarly journals Mining Google and Apple mobility data: temporal anatomy for COVID-19 social distancing

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Corentin Cot ◽  
Giacomo Cacciapaglia ◽  
Francesco Sannino
Keyword(s):  
Infection Rate ◽  
The United States ◽  
Strong Decrease ◽  
Social Distancing ◽  
Mobility Data ◽  
Actual Measure ◽  
The Us ◽  
The Impact ◽  
Political Decisions ◽  
Mobility Reduction

AbstractWe employ the Google and Apple mobility data to identify, quantify and classify different degrees of social distancing and characterise their imprint on the first wave of the COVID-19 pandemic in Europe and in the United States. We identify the period of enacted social distancing via Google and Apple data, independently from the political decisions. Our analysis allows us to classify different shades of social distancing measures for the first wave of the pandemic. We observe a strong decrease in the infection rate occurring two to five weeks after the onset of mobility reduction. A universal time scale emerges, after which social distancing shows its impact. We further provide an actual measure of the impact of social distancing for each region, showing that the effect amounts to a reduction by 20–40% in the infection rate in Europe and 30–70% in the US.

scholarly journals Socioeconomic Disparities in Social Distancing During the COVID-19 Pandemic in the United States: Observational Study (Preprint)

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R Benetka ◽  
John Kraemer ◽  
Shweta Bansal
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Control Measures ◽  
Mobility Patterns ◽  
Poverty Level ◽  
Social Distancing ◽  
Mobility Data ◽  
Black Populations ◽  
The Impact

BACKGROUND Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic. OBJECTIVE We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations. METHODS We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density. RESULTS We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations. CONCLUSIONS Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts.

scholarly journals Socio-economic disparities in social distancing during the COVID-19 pandemic in the United States

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R. Benetka ◽  
John Kraemer ◽  
Shweta Bansal
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Control Measures ◽  
Mobility Patterns ◽  
Poverty Level ◽  
Social Distancing ◽  
Mobility Data ◽  
Black Populations ◽  
The Impact

AbstractImportanceEliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic.ObjectiveTo assess how mobility patterns have varied across the United States during the COVID-19 pandemic, and identify associations with socio-economic factors of populations.Design, Setting, and ParticipantsWe used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level between February and May 2020. Using linear mixed models, we assessed the associations between social distancing and socio-economic variables, including the proportion of people below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density.Main outcomes and ResultsWe find that the speed, depth, and duration of social distancing in the United States is heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; and in contrast, that social distancing is intense in counties with higher population densities and larger Black populations.Conclusions and relevanceSocio-economic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of COVID-19 in communities across the United States. This is likely to amplify existing health disparities, and needs to be addressed to ensure the success of ongoing pandemic mitigation efforts.

scholarly journals Expected Health Effects of Reduced Air Pollution from COVID-19 Social Distancing

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 951
Author(s):  
Steve Cicala ◽  
Stephen P. Holland ◽  
Erin T. Mansur ◽  
Nicholas Z. Muller ◽  
Andrew J. Yates
Keyword(s):  
Air Pollution ◽  
Health Effects ◽  
Electricity Consumption ◽  
The United States ◽  
Time Frame ◽  
Social Distancing ◽  
Mobility Data ◽  
Premature Deaths ◽  
The Impact ◽  
At Home

The COVID-19 pandemic resulted in stay-at-home policies and other social distancing behaviors in the United States in spring of 2020. This paper examines the impact that these actions had on emissions and expected health effects through reduced personal vehicle travel and electricity consumption. Using daily cell phone mobility data for each U.S. county, we find that vehicle travel dropped about 40% by mid-April across the nation. States that imposed stay-at-home policies before March 28 decreased travel slightly more than other states, but travel in all states decreased significantly. Using data on hourly electricity consumption by electricity region (e.g., balancing authority), we find that electricity consumption fell about 6% on average by mid-April with substantial heterogeneity. Given these decreases in travel and electricity use, we estimate the county-level expected improvements in air quality, and, therefore, expected declines in mortality. Overall, we estimate that, for a month of social distancing, the expected premature deaths due to air pollution from personal vehicle travel and electricity consumption declined by approximately 360 deaths, or about 25% of the baseline 1500 deaths. In addition, we estimate that CO2 emissions from these sources fell by 46 million metric tons (a reduction of approximately 19%) over the same time frame.

scholarly journals Impacts of social distancing policies on mobility and COVID-19 case growth in the US

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gregory A. Wellenius ◽  
Swapnil Vispute ◽  
Valeria Espinosa ◽  
Alex Fabrikant ◽  
Thomas C. Tsai ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Infection Control ◽  
State Level ◽  
The United States ◽  
Social Consequences ◽  
Social Distancing ◽  
Mobility Data ◽  
The Us ◽  
Public Health Officials

AbstractSocial distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.

scholarly journals The impact of ethnic segregation on neighbourhood-level social distancing in the United States amid the early outbreak of COVID-19

Urban Studies ◽  
2021 ◽  
pp. 004209802110501
Author(s):  
Wei Zhai ◽  
Xinyu Fu ◽  
Mengyang Liu ◽  
Zhong-Ren Peng
Keyword(s):  
Public Health ◽  
United States ◽  
Ethnic Minorities ◽  
Diversity Index ◽  
The United States ◽  
Ethnic Segregation ◽  
Minority Communities ◽  
Social Distancing ◽  
Neighbourhood Level ◽  
The Impact

The COVID-19 pandemic has been argued to be the ‘great equaliser’, but, in fact, ethnically and racially segregated communities are bearing a disproportionate burden from the disease. Although more people have been infected and died from the disease among these minority communities, still fewer people in these communities are complying with the suggested public health measures like social distancing. The factors contributing to these ramifications remain a long-lasting debate, in part due to the contested theories between ethnic stratification and ethnic community. To offer empirical evidence to this theoretical debate, we tracked public social-distancing behaviours from mobile phone devices across urban census tracts in the United States and employed a difference-in-difference model to examine the impact of racial/ethnic segregation on these behaviours. Specifically, we focussed on non-Hispanic Black and Hispanic communities at the neighbourhood level from three principal dimensions of ethnic segregation, namely, evenness, exposure, and concentration. Our results suggest that (1) the high ethnic diversity index can decrease social-distancing behaviours and (2) the high dissimilarity between ethnic minorities and non-Hispanic Whites can increase social-distancing behavior; (3) the high interaction index can decrease social-distancing behaviours; and (4) the high concentration of ethnic minorities can increase travel distance and non-home time but decrease work behaviours. The findings of this study shed new light on public health behaviours among minority communities and offer empirical knowledge for policymakers to better inform just and evidence-based public health orders.

scholarly journals Experience with Social Distancing Early in the COVID-19 Pandemic in the United States: Implications for Public Health Messaging

2020 ◽  
Author(s):  
Ryan C. Moore ◽  
Angela Lee ◽  
Jeffrey T. Hancock ◽  
Meghan Halley ◽  
Eleni Linos
Keyword(s):  
Public Health ◽  
Language Processing ◽  
Compliance Rate ◽  
Age Groups ◽  
The United States ◽  
Free Text ◽  
Social Distancing ◽  
Aged People ◽  
Natural Language Processing Tool ◽  
The Impact

Our goal is to inform ongoing public health policy on the design and communication of COVID-19 social distancing measures to maximize compliance. We assessed the US public’s early experience with the COVID-19 crisis during the period when shelter-in-place orders were widely implemented to understand non-compliance with those orders, sentiment about the crisis, and to compare across age categories associated with different levels of risk. We posted our survey on Twitter, Facebook, and NextDoor on March 14th to March 23rd that included 21 questions including demographics, impact on daily life, actions taken, and difficulties faced.1 We analyzed the free-text responses to the impact question using LIWC, a computational natural language processing tool2, and performed a thematic content analysis of the reasons people gave for non-compliance with social distancing orders. Stanford University’s IRB approved the study.In 9 days, we collected a total of 20,734 responses. 6,573 individuals provided a response (≥30 words) to the question, “Tell us how the coronavirus crisis is impacting your life.” Our data (Figure 1) show that younger people (18-31) are more emotionally negative, self-centered, and less concerned with family, while middle-aged people are group-oriented (32-44) and focused on family (32-64) (all p values < .05 corrected for multiple comparisons). Unsurprisingly, the oldest and most at-risk group (65+) are more focused on biological terms (e.g., health-related topics), but were surprisingly low in anxiety and high in emotionally positive terms relative to those at lower risk.We also content-analyzed 7,355 responses (kappa’s > .75) to the question, “What are the reasons you are not self-isolating more?” Of these participants, 39.8% reported not being compliant, with the youngest group (18-31) having the lowest compliance rate (52.4%) compared to the other age groups (all > 60%; all p values < .01). Table 1 describes the seven primary themes for non-compliance. Non-essential work requirements, concerns about mental and physical health, and the belief that other precautions were sufficient were the most common reasons, although other rationales included wanting to continue everyday activities and beliefs that society is over-reacting. Childcare was an important concern for a subset of respondents.Overall, our findings suggest that public health messages should focus on young people and 1) address their negative affect, 2) refocus their self-orientation by emphasizing the importance of individual behavior to group-level health outcomes, and 3) target the specific rationales that different people have regarding the pandemic to maximize compliance with social distancing.

scholarly journals Dual MD–MPH Degree Students in the United States: Moving the Medical Workforce Toward Population Health

2021 ◽  
pp. 003335492097842
Author(s):  
Jo Marie Reilly ◽  
Christine M. Plepys ◽  
Michael R. Cousineau
Keyword(s):  
Public Health ◽  
United States ◽  
Population Health ◽  
Health Care Policy ◽  
The United States ◽  
Extensive Literature ◽  
Master Of Public Health ◽  
Telephone Interviews ◽  
Public Health Training ◽  
The Impact

Objective A growing need exists to train physicians in population health to meet the increasing need and demand for physicians with leadership, health data management/metrics, and epidemiology skills to better serve the health of the community. This study examines current trends in students pursuing a dual doctor of medicine (MD)–master of public health (MPH) degree (MD–MPH) in the United States. Methods We conducted an extensive literature review of existing MD–MPH databases to determine characteristics (eg, sex, race/ethnicity, MPH area of study) of this student cohort in 2019. We examined a trend in the MD community to pursue an MPH career, adding additional public health and health care policy training to the MD workforce. We conducted targeted telephone interviews with 20 admissions personnel and faculty at schools offering MD–MPH degrees in the United States with the highest number of matriculants and graduates. Interviews focused on curricula trends in medical schools that offer an MD–MPH degree. Results No literature describes the US MD–MPH cohort, and available MD–MPH databases are limited and incomplete. We found a 434% increase in the number of students pursuing an MD–MPH degree from 2010 to 2018. The rate of growth was greater than the increase in either the number of medical students (16%) or the number of MPH students (65%) alone. Moreover, MD–MPH students as a percentage of total MPH students more than tripled, from 1.1% in 2010 to 3.6% in 2018. Conclusions As more MD students pursue public health training, the impact of an MPH degree on medical school curricula, MD–MPH graduates, and MD–MPH career pursuits should be studied using accurate and comprehensive databases.

scholarly journals More Than Shelter: Housing for Urban Maternal and Infant Health

2021 ◽  
Vol 18 (7) ◽  
pp. 3331
Author(s):  
Jason Reece
Keyword(s):  
Public Health ◽  
Maternal Health ◽  
Health Outcomes ◽  
City Planning ◽  
Infant Health ◽  
The United States ◽  
Housing Quality ◽  
Housing Discrimination ◽  
Maternal Health Outcomes ◽  
The Impact

Housing quality, stability, and affordability have a direct relationship to socioemotional and physical health. Both city planning and public health have long recognized the role of housing in health, but the complexity of this relationship in regard to infant and maternal health is less understood. Focusing on literature specifically relevant to U.S. metropolitan areas, I conduct a multidisciplinary literature review to understand the influence of housing factors and interventions that impact infant and maternal health. The paper seeks to achieve three primary goals. First, to identify the primary “pathways” by which housing influences infant and maternal health. Second, the review focuses on the role and influence of historical housing discrimination on maternal health outcomes. Third, the review identifies emergent practice-based housing interventions in planning and public health practice to support infant and maternal health. The literature suggests that the impact of housing on infant health is complex, multifaceted, and intergenerational. Historical housing discrimination also directly impacts contemporary infant and maternal health outcomes. Policy interventions to support infant health through housing are just emerging but demonstrate promising outcomes. Structural barriers to housing affordability in the United States will require new resources to foster greater collaboration between the housing and the health sectors.

scholarly journals The Effects of Social Distancing Policies on non-SARS-CoV-2 Respiratory Pathogens

2021 ◽  
Author(s):  
Jeff Nawrocki ◽  
Katherine Olin ◽  
Martin C Holdrege ◽  
Joel Hartsell ◽  
Lindsay Meyers ◽  
...  
Keyword(s):  
Public Health ◽  
Influenza A ◽  
Detection Rate ◽  
Respiratory Illness ◽  
Respiratory Pathogens ◽  
Public Health Response ◽  
Mixed Effect ◽  
Detection Rates ◽  
Social Distancing ◽  
The Impact

Abstract Background The initial focus of the US public health response to COVID-19 was the implementation of numerous social distancing policies. While COVID-19 was the impetus for imposing these policies, it is not the only respiratory disease affected by their implementation. This study aimed to assess the impact of social distancing policies on non-SARS-CoV-2 respiratory pathogens typically circulating across multiple US states. Methods Linear mixed-effect models were implemented to explore the effects of five social distancing policies on non-SARS-CoV-2 respiratory pathogens across nine states from January 1 through May 1, 2020. The observed 2020 pathogen detection rates were compared week-by-week to historical rates to determine when the detection rates were different. Results Model results indicate that several social distancing policies were associated with a reduction in total detection rate, by nearly 15%. Policies were associated with decreases in pathogen circulation of human rhinovirus/enterovirus and human metapneumovirus, as well as influenza A, which typically decrease after winter. Parainfluenza viruses failed to circulate at historical levels during the spring. Total detection rate in April 2020 was 35% less than historical average. Many of the pathogens driving this difference fell below historical detection rate ranges within two weeks of initial policy implementation. Conclusion This analysis investigated the effect of multiple social distancing policies implemented to reduce transmission of SARS-CoV-2 on non-SARS-CoV-2 respiratory pathogens. These findings suggest that social distancing policies may be used as an impactful public health tool to reduce communicable respiratory illness.

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