Routing algorithms as tools for integrating social distancing with emergency evacuation.
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ABSTRACT:
SUBMITTER: Tsai YL
PROVIDER: S-EPMC8490376 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:As COVID-19 spreads across the globe, new technologies are being leveraged to enforce social distancing requirements. I explore social distancing through the theoretical lens of Michel Foucault’s biopolitics, with an emphasis on recognizing unauthorized movement and controlling circulation. Although reporting and widely shared data visualizations about COVID-19 have made many people newly aware that their movements are being tracked and surveilled, governments are already implementing new measures such as geofencing and artificial intelligence (AI)–based facial recognition to facilitate the enforcement of social distancing. The tracking of COVID-19 spread and social distancing behaviors of the public has made more visible the practices of biopolitics but also generated new opportunities for even greater surveillance and control. The current moment offers an opportunity to shift public perceptions about data surveillance, technological control, and the racial disparities of biopower, much in the same way that public perceptions around social media shifted during and after the Arab Spring. How we collectively respond to these biopolitical processes will, in part, determine how such power relations are articulated in the future.
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Project description:Social distancing interventions can be effective against epidemics but are potentially detrimental for the economy. Businesses that rely heavily on face-to-face communication or close physical proximity when producing a product or providing a service are particularly vulnerable. There is, however, no systematic evidence about the role of human interactions across different lines of business and about which will be the most limited by social distancing. Here we provide theory-based measures of the reliance of U.S. businesses on human interaction, detailed by industry and geographic location. We find that, before the pandemic hit, 43 million workers worked in occupations that rely heavily on face-to-face communication or require close physical proximity to other workers. Many of these workers lost their jobs since. Consistently with our model, employment losses have been largest in sectors that rely heavily on customer contact and where these contacts dropped the most: retail, hotels and restaurants, arts and entertainment and schools. Our results can help quantify the economic costs of social distancing.
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Project description:IntroductionGovernments and public health authorities across many jurisdictions implemented social (physical) distancing measures to contain the spread of the 2019 novel coronavirus disease (COVID-19). Adherence to these measures is variable and likely influenced by various factors. This study aimed to 1) identify the individual sociodemographic, COVID-19 and social distancing related, and psychological determinants of social distancing adherence, and 2) explore regional differences in social distancing adherence in the United States (U.S.) and English-speaking Canada based on each region's discrepant response to social distancing restrictions.MethodsA web-based repeated cross-sectional survey was conducted in 4,942 English-speaking participants from the four most populous U.S. states, specifically New York, California, Texas, and Florida, and Canada (www.covid19-database.com). The study was conducted at two timepoints, from May 1 to 5, 2020 (n = 1,019, Canadian participants only) and from July 6 to 10, 2020 (n = 3,923). Separate univariate models were computed for individual sociodemographic, COVID-19 and social distancing related, and psychological determinants of social distancing adherence. To determine the total variance explained, a univariate analysis including all of the determinants was performed. Regional differences in social distancing were compared between the four U.S. states and Canada, and between the U.S. as a whole and Canada.ResultsAdherence to social distancing was higher in May (mean = 4.4/5.0±0.7) compared to July (mean = 4.3/5.0±0.7) [t (4940) = 6.96, p < 0.001], likely a reflection of relaxing restrictions. There were no regional differences in adherence. Sociodemographic, COVID-19 and social distancing related, and psychological determinants explained 10, 36, and 23% of the variance of social distancing adherence, respectively. Higher perceived seriousness of COVID-19 [β (SE) = 0.39 (0.01), p < 0.001, partial η2 = 0.22], lower risk propensity [β (SE) = -0.15 (0.01), p < 0.001, partial η2 = 0.06], germ aversion [β (SE) = 0.12 (0.01), p < 0.001, partial η2 = 0.03], age [β (SE) = 0.01 (0.00), p < 0.001, partial η2 = 0.02], and greater social support [β (SE) = 0.03 (0.00), p < 0.001, partial η2 = 0.02] had the largest effects on social distancing adherence.ConclusionPublic service initiatives to emphasize the serious consequences of infection and targeted interventions toward certain sociodemographic groups, such as younger adults and vulnerable individuals in greater need of social support, may help enhance the public's adherence to social distancing measures during subsequent waves of COVID-19 and future pandemics.
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