scholarly journals Socio-economic disparities in social distancing during the COVID-19 pandemic in the United States : an observational study (Preprint)

Author(s):  
Romain Garnier ◽  
Jan R Benetka ◽  
John Kraemer ◽  
Shweta Bansal
2020 ◽  
Author(s):  
Joseph Younis ◽  
Harvy Freitag ◽  
Jeremy S Ruthberg ◽  
Jonathan P Romanes ◽  
Craig Nielsen ◽  
...  

BACKGROUND  The magnitude and time course of the COVID-19 epidemic in the United States depends on early interventions to reduce the basic reproductive number to below 1. It is imperative, then, to develop methods to actively assess where quarantine measures such as social distancing may be deficient and suppress those potential resurgence nodes as early as possible. OBJECTIVE We ask if social media is an early indicator of public social distancing measures in the United States by investigating its correlation with the time-varying reproduction number (R<sub>t</sub>) as compared to social mobility estimates reported from Google and Apple Maps. METHODS  In this observational study, the estimated R<sub>t</sub> was obtained for the period between March 5 and April 5, 2020, using the EpiEstim package. Social media activity was assessed using queries of “social distancing” or “#socialdistancing” on Google Trends, Instagram, and Twitter, with social mobility assessed using Apple and Google Maps data. Cross-correlations were performed between R<sub>t</sub> and social media activity or mobility for the United States. We used Pearson correlations and the coefficient of determination (ρ) with significance set to <i>P</i>&lt;.05. RESULTS Negative correlations were found between Google search interest for “social distancing” and R<sub>t</sub> in the United States (<i>P</i>&lt;.001), and between search interest and state-specific R<sub>t</sub> for 9 states with the highest COVID-19 cases (<i>P</i>&lt;.001); most states experienced a delay varying between 3-8 days before reaching significance. A negative correlation was seen at a 4-day delay from the start of the Instagram hashtag “#socialdistancing” and at 6 days for Twitter (<i>P</i>&lt;.001). Significant correlations between R<sub>t</sub> and social media manifest earlier in time compared to social mobility measures from Google and Apple Maps, with peaks at –6 and –4 days. Meanwhile, changes in social mobility correlated best with R<sub>t</sub> at –2 days and +1 day for workplace and grocery/pharmacy, respectively. CONCLUSIONS Our study demonstrates the potential use of Google Trends, Instagram, and Twitter as epidemiological tools in the assessment of social distancing measures in the United States during the early course of the COVID-19 pandemic. Their correlation and earlier rise and peak in correlative strength with R<sub>t</sub> when compared to social mobility may provide proactive insight into whether social distancing efforts are sufficiently enacted. Whether this proves valuable in the creation of more accurate assessments of the early epidemic course is uncertain due to limitations. These limitations include the use of a biased sample that is internet literate with internet access, which may covary with socioeconomic status, education, geography, and age, and the use of subtotal social media mentions of social distancing. Future studies should focus on investigating how social media reactions change during the course of the epidemic, as well as the conversion of social media behavior to actual physical behavior.


10.2196/21340 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e21340 ◽  
Author(s):  
Joseph Younis ◽  
Harvy Freitag ◽  
Jeremy S Ruthberg ◽  
Jonathan P Romanes ◽  
Craig Nielsen ◽  
...  

Background  The magnitude and time course of the COVID-19 epidemic in the United States depends on early interventions to reduce the basic reproductive number to below 1. It is imperative, then, to develop methods to actively assess where quarantine measures such as social distancing may be deficient and suppress those potential resurgence nodes as early as possible. Objective We ask if social media is an early indicator of public social distancing measures in the United States by investigating its correlation with the time-varying reproduction number (Rt) as compared to social mobility estimates reported from Google and Apple Maps. Methods  In this observational study, the estimated Rt was obtained for the period between March 5 and April 5, 2020, using the EpiEstim package. Social media activity was assessed using queries of “social distancing” or “#socialdistancing” on Google Trends, Instagram, and Twitter, with social mobility assessed using Apple and Google Maps data. Cross-correlations were performed between Rt and social media activity or mobility for the United States. We used Pearson correlations and the coefficient of determination (ρ) with significance set to P<.05. Results Negative correlations were found between Google search interest for “social distancing” and Rt in the United States (P<.001), and between search interest and state-specific Rt for 9 states with the highest COVID-19 cases (P<.001); most states experienced a delay varying between 3-8 days before reaching significance. A negative correlation was seen at a 4-day delay from the start of the Instagram hashtag “#socialdistancing” and at 6 days for Twitter (P<.001). Significant correlations between Rt and social media manifest earlier in time compared to social mobility measures from Google and Apple Maps, with peaks at –6 and –4 days. Meanwhile, changes in social mobility correlated best with Rt at –2 days and +1 day for workplace and grocery/pharmacy, respectively. Conclusions Our study demonstrates the potential use of Google Trends, Instagram, and Twitter as epidemiological tools in the assessment of social distancing measures in the United States during the early course of the COVID-19 pandemic. Their correlation and earlier rise and peak in correlative strength with Rt when compared to social mobility may provide proactive insight into whether social distancing efforts are sufficiently enacted. Whether this proves valuable in the creation of more accurate assessments of the early epidemic course is uncertain due to limitations. These limitations include the use of a biased sample that is internet literate with internet access, which may covary with socioeconomic status, education, geography, and age, and the use of subtotal social media mentions of social distancing. Future studies should focus on investigating how social media reactions change during the course of the epidemic, as well as the conversion of social media behavior to actual physical behavior.


2021 ◽  
pp. 014616722110241
Author(s):  
Shai Davidai ◽  
Jesse Walker

What do people know about racial disparities in “The American Dream”? Across six studies ( N = 1,761), we find that American participants consistently underestimate the Black–White disparity in economic mobility, believing that poor Black Americans are significantly more likely to move up the economic ladder than they actually are. We find that misperceptions about economic mobility are common among both White and Black respondents, and that this undue optimism about the prospect of mobility for Black Americans results from a narrow focus on the progress toward equality that has already been made. Consequently, making economic racial disparities salient, or merely reflecting on the unique hardships that Black Americans face in the United States, calibrates beliefs about economic mobility. We discuss the importance of these findings for understanding lay beliefs about the socioeconomic system, the denial of systemic racism in society, and support for policies aimed at reducing racial economic disparities.


Author(s):  
Kyra B. Phillips ◽  
Kelly N. Byrne ◽  
Branden S. Kolarik ◽  
Audra K. Krake ◽  
Young C. Bui ◽  
...  

Since COVID-19 transmission accelerated in the United States in March 2020, guidelines have recommended that individuals wear masks and limit close contact by remaining at least six feet away from others, even while outdoors. Such behavior is important to help slow the spread of the global pandemic; however, it may require pedestrians to make critical decisions about entering a roadway in order to avoid others, potentially creating hazardous situations for both themselves and for drivers. In this survey study, we found that while overall patterns of self-reported pedestrian activity remained largely consistent over time, participants indicated increased willingness to enter active roadways when encountering unmasked pedestrians since the COVID-19 pandemic began. Participants also rated the risks of encountering unmasked pedestrians as greater than those associated with entering a street, though the perceived risk of passing an unmasked pedestrian on the sidewalk decreased over time.


PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0205924 ◽  
Author(s):  
Eric Gluck ◽  
H. Bryant Nguyen ◽  
Kishore Yalamanchili ◽  
Margaret McCusker ◽  
Jaya Madala ◽  
...  

2020 ◽  
Vol 117 (28) ◽  
pp. 16264-16266 ◽  
Author(s):  
Joris Lammers ◽  
Jan Crusius ◽  
Anne Gast

The most effective way to stem the spread of a pandemic such as coronavirus disease 2019 (COVID-19) is social distancing, but the introduction of such measures is hampered by the fact that a sizeable part of the population fails to see their need. Three studies conducted during the mass spreading of the virus in the United States toward the end of March 2020 show that this results partially from people’s misperception of the virus’s exponential growth in linear terms and that overcoming this bias increases support for social distancing. Study 1 shows that American participants mistakenly perceive the virus’s exponential growth in linear terms (conservatives more so than liberals). Studies 2 and 3 show that instructing people to avoid the exponential growth bias significantly increases perceptions of the virus’s growth and thereby increases support for social distancing. Together, these results show the importance of statistical literacy to recruit support for fighting pandemics such as the coronavirus.


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