About: Abstract Objectives Non-pharmaceutical interventions (NPIs) are effective in curbing the spread of SARS-CoV-2. All US states have adopted NPI policies, but the compliance to these measures and influence of socio-political factors on NPI adherence is unknown. NPI adherence may be approximated by personal mobility in a population which is tracked by anonymous mobile phone data. Study Design A cross-sectional study of state-level mobility changes across the US. Methods State-level mobility was based on anonymous mobile phone data from multiple participating carriers collected by the University of Washington Institute for Health Metrics and Evaluation (http://www.healthdata.org). Pearson’s correlation coefficient was used to examine the strength and direction of the relationship between political affiliations and mobility restriction across states. Multivariable linear regression analyses were used to assess other factors that may impact personal travel. Results All states experienced a decline in personal mobility but had varying nadirs ranging from a 34% to 69% reduction in mobility which was not temporally related to the timing of state-level NPI measures. There was a statistically significant linear and negative correlation of r= -0.79 between the proportion of Republicans/leaning Republicans and NPI adherence across US states. The negative association between Republicans and NPI adherence was significant even when adjusting for urbanization, proportion of essential workers, population, Gini index, and poverty rates. Conclusions Political orientation affects risk perception, which may contribute to the unwillingness of some individuals to perceive the COVID-19 pandemic as a risk and to comply with NPIs. Our results highlight the importance of socio-political factors in disease control and emphasizes the importance of bipartisan efforts in fighting the pandemic. These results may have implications for the development, dissemination, and communication of public health policies.   Goto Sponge  NotDistinct  Permalink

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  • Abstract Objectives Non-pharmaceutical interventions (NPIs) are effective in curbing the spread of SARS-CoV-2. All US states have adopted NPI policies, but the compliance to these measures and influence of socio-political factors on NPI adherence is unknown. NPI adherence may be approximated by personal mobility in a population which is tracked by anonymous mobile phone data. Study Design A cross-sectional study of state-level mobility changes across the US. Methods State-level mobility was based on anonymous mobile phone data from multiple participating carriers collected by the University of Washington Institute for Health Metrics and Evaluation (http://www.healthdata.org). Pearson’s correlation coefficient was used to examine the strength and direction of the relationship between political affiliations and mobility restriction across states. Multivariable linear regression analyses were used to assess other factors that may impact personal travel. Results All states experienced a decline in personal mobility but had varying nadirs ranging from a 34% to 69% reduction in mobility which was not temporally related to the timing of state-level NPI measures. There was a statistically significant linear and negative correlation of r= -0.79 between the proportion of Republicans/leaning Republicans and NPI adherence across US states. The negative association between Republicans and NPI adherence was significant even when adjusting for urbanization, proportion of essential workers, population, Gini index, and poverty rates. Conclusions Political orientation affects risk perception, which may contribute to the unwillingness of some individuals to perceive the COVID-19 pandemic as a risk and to comply with NPIs. Our results highlight the importance of socio-political factors in disease control and emphasizes the importance of bipartisan efforts in fighting the pandemic. These results may have implications for the development, dissemination, and communication of public health policies.
Subject
  • Zoonoses
  • Epidemiology
  • Centers for Disease Control and Prevention
  • COVID-19
  • Mobile phones
  • Embedded systems
  • New media
  • 2000s fads and trends
  • Telephony
  • Mobile telecommunications
  • Mobile telecommunication services
  • Radio technology
  • Telecommunications-related introductions in 1973
  • Videotelephony
  • Sarbecovirus
  • Chiroptera-borne diseases
  • Infraspecific virus taxa
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