Public policy and health in the Trump era

Woolhandler, Steffie; Himmelstein, David U.; Ahmed, Sameer; Bailey, Zinzi; Bassett, Mary T.; Bird, Michael E.; Bor, Jacob; Bor, David H.; Carrasquillo, Olveen; Chowkwanyun, Merlin; Dickman, Samuel; Fisher, Samantha; Gaffney, Adam; Galea, Sandro; Gottfried, Richard N.; Grumbach, Kevin; Guyatt, Gordon; Hansen, Helena; Landrigan, Philip J.; Lighty, Michael; McKee, Martin; McCormick, Danny; McGregor, Alecia; Mirza, Reza; Morris, Juliana E; Mukherjee, Joia S.; Nestle, Marion; Prine, Linda; Saadi, Altaf; Schiff, Davida M.; Shapiro, Martin; Tesema, Lello; Venkataramani, Atheendar S.

doi:10.1016/s0140-6736(20)32545-9

Cited by 109 publications

(73 citation statements)

References 151 publications

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“…We, along with many others [ 9 – 14 ], suggest adding increased analytic and scientific attention to social media as a platform, and process, for the structuring of public health outcomes. We recognize that the data set provided here is only correlational, but given the numerous research findings regarding the use of social media by Donald Trump, and his administration’s well documented negative impact on public health [ 17 ], we argue that our data and analyses offer support to the assertion of a substantive influence of @realdonaldtrump in negatively shaping public health perceptions and thus outcomes.…”

Section: Discussionmentioning

confidence: 64%

“…Our assessment of Twitter patterns related to the COVID19 pandemic offers a cautionary tale for public health. The Lancet Commission on Public Policy and Health in the Trump Era clearly document the specific damage done to USA public health policy, and public health itself, by the Trump administration [ 17 ]. The report lays out a number of specific executive and legislative actions to remediate such harms, but does not address social media.…”

Section: Discussionmentioning

confidence: 99%

“…A recent study demonstrated that Donald Trump specifically exploited Twitter as a tool to divert/direct the attention of mainstream media in relation to his personal goals rather than public good [ 15 ]. There is also substantial evidence documenting Donald Trump’s antagonism towards scientific data and public health assessments/recommendations and the officials/researchers who generated them [ 16 ] and that such antagonism has had deleterious impacts on public health and health systems in the USA [ 17 ]. There is also evidence of the negative and harmful impact Donald Trump had as a Twitter user, resulting in his being suspended permanently from the social media platform on January 8 th , 2021 (see Twitter’s statement on the permanent suspension [ 18 ]).…”

Section: Introductionmentioning

confidence: 99%

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Social media and public perception as core aspect of public health: The cautionary case of @realdonaldtrump and COVID-19

Fuentes

Peterson

2021

PLoS ONE

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The social media milieu in which we are enmeshed has substantive impacts on our beliefs and perceptions. Recent work has established that this can play a role in influencing understanding of, and reactions to, public health information. Twitter, in particular, appears to play a substantive role in the public health information ecosystem. From July 25th, 2020 to November 15th, 2020, we collected weekly tweets related to COVID19 keywords and assessed their networks, patterns and properties. Our analyses revealed the dominance of a handful of individual accounts as central structuring agents in the networks of tens of thousands of tweets and retweets, and thus millions of views, related to specific COVID19 keywords. These few individual accounts and the content of their tweets, mentions, and retweets are substantially overrepresented in terms of public exposure to, and thus interaction with, critical elements of public health information in the pandemic. Here we report on one particularly striking aspect of our dataset: the prominent position of @realdonaldtrump in Twitter networks related to four key terms of the COVID19 pandemic in 2020.

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Section: Discussionmentioning

confidence: 64%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Social media and public perception as core aspect of public health: The cautionary case of @realdonaldtrump and COVID-19

Fuentes

Peterson

2021

PLoS ONE

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“…A pervasive sense of quarantine fatigue and panic attacks of getting infected are challenging human resilience [2][3]. COVID-19 is one of the extreme diseases as incurable and universally fatal, killing 25%-50% of patients [4]. In particular, the COVID-19 pandemic in the U. S. was exposed to mass dislocation, directly accelerating the decline and failure of public health.…”

Section: Introductionmentioning

confidence: 99%

“…With around 30 million diagnosed cases and over 540,000 deaths as of mid-January 2020, a disproportionate impact on COVID-19 was produced. There are 40% of cases should have been averted with international cooperation of medical care [4]. In addition, agespecific mortality rates in the US had remained corresponding to the weighted average of G7 nations [4].…”

Section: Introductionmentioning

confidence: 99%

Space-Time Cluster’s Detection and Geographical Weighted Regression Analysis of COVID-19 Mortality Impacts on Texas Counties

Zhang

Wu²,

Chow

2021

Preprint

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As COVID-19 run rampant in high-density housing sites, it is important to use real-time data tracking the virus mobility. Emerging cluster detection analysis is a precise way of blunting the spread of COVID-19 as quickly as possible and save lives. To track compliable mobility of COVID-19 on a spatial-temporal scale, this research is appropriately analyzed the disparities between spatial-temporal clusters, expectation Maximization clustering (EM) and hierarchical clustering (HC) analysis on Texas county-level. Then, based on the outcome of clustering analysis, the sensitive counties are Cottle, Stonewall, Bexar, Tarrant, Dallas, Harris, Jim hogg, and Real, corresponding to South-east Texas analysis in GWR modeling. The sensitive period took place in the last two quarters in 2020. We explored Postgre application to portray tracking Covid-19 trajectory. We captured 14 social, economic, and environmental 14 impact’s indices to perform Principal Component Analysis (PCA) to reduce dimensionality and minimize multicollinearity. By using the PCA, we extracted five factors related to mortality of COVID-19, involved population and hospitalization, age structure, natural supply, economic condition, air quality and medical care. We established the GWR model to seek the sensitive factors. The result shows that population, hospitalization, and economic condition are the sensitive factors. Those factors also triggered high increase of COVID-19 mortality. This research provides geographical understanding and solution of controlling COVID-19, reference of implementing geographically targeted ways to track virus mobility and satisfy for the need of Emergency Operations Plan (EOP).

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We Can Heal From Hate Crimes by Practicing Solidarity

Cai

2021

JAMA Intern Med

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Public policy and health in the Trump era

Cited by 109 publications

References 151 publications

Social media and public perception as core aspect of public health: The cautionary case of @realdonaldtrump and COVID-19

Social media and public perception as core aspect of public health: The cautionary case of @realdonaldtrump and COVID-19

Space-Time Cluster’s Detection and Geographical Weighted Regression Analysis of COVID-19 Mortality Impacts on Texas Counties

We Can Heal From Hate Crimes by Practicing Solidarity

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