People in the pro-Trump parts of the US stayed at home less and got COVID more

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Peer-reviewed: This work was reviewed and scrutinised by relevant independent experts.

Observational study: A study in which the subject is observed to see if there is a relationship between two or more things (eg: the consumption of diet drinks and obesity). Observational studies cannot prove that one thing causes another, only that they are linked.

People: This is a study based on research using people.

People in counties in the United States that voted for Donald Trump in the 2016 presidential election tended to physically distance 14 per cent less than those in counties that voted for Hillary Clinton, according to US research. The counties who watched the most Fox News were also less likely to physically distance. The study, which analysed location data from 15 million people's smartphones from March to May 2020, showed that these partisanship partisan differences in distancing were associated with higher COVID-19 infection growth rates in pro-Trump regions.

Journal/conference: Nature Human Behaviour

Link to research (DOI): 10.1038/s41562-020-00977-7

Organisation/s: Yale University, USA

Funder: P.P. was supported by the Swedish Research Council (no. 2016-06793).

Media release

From: Springer Nature

2.  Human Behaviour: Pro-Trump areas physically distanced less during the COVID-19 pandemic, predicting health outcomes

People in counties in the United States that voted for Donald Trump (Republican) in the 2016 presidential election tended to physically distance 14% less than those in counties that voted for Hillary Clinton (Democrat) from March to May 2020. This study, published in Nature Human Behaviour, analysed daily geotracking data from 15 million people and found that

Numerous polls have found a partisan gap in perceptions and support for preventative health behaviours during the COVID-19 pandemic in the United States. However, it is unclear whether these polls reflect real-world behaviour.

Anton Gollwitzer and colleagues analysed the daily geotracking data from 15 million smartphones in 3,000 US counties to study whether physical distancing in the first few months of the pandemic differed according to partisan leaning. They measured physical distancing in terms of reduction in general movement and reduction in visiting nonessential services (such as restaurants, salons and clothing stores) compared to the previous year using GPS coordinates.

The authors found that people in counties that voted for Trump in 2016 showed a 24% drop in regular activity, while those in counties that voted for Clinton showed a larger 38% reduction. They also observed that partisanship was more strongly associated with physical distancing than other factors, including a county’s median income, the number of COVID-19 cases, commuting to work, population density and racial and age demographics. Furthermore, the partisan gap strengthened over time, even when stay-at-home orders were in place. Finally, using a combination of mathematical models, the authors found that partisan differences in physical distancing related to subsequent infection and fatality growth rates. According to these models, reduced physical distancing in pro-Trump counties was associated with a higher subsequent daily infection growth rate than average.

The authors caution that their data are correlational and do not demonstrate that partisanship in the U.S. caused different physical distancing patterns. However, they conclude that partisanship might be an important risk factor for the current COVID-19 pandemic and potentially other public health crises.

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