Evidence map›Paper›PMID 39752190›Full record

Observational studyJournal of medical Internet research2025

US State Public Health Agencies' Use of Twitter From 2012 to 2022: Observational Study.

Samuel R Mendez, Sebastian Munoz-Najar, Karen M Emmons, Kasisomayajula Viswanath

Abstract readObservational Study
In one paragraph

Observational study in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Barriers to Public Health Trust-Building Using Social Media: A Qualitative Analysis.Disaster medicine and public health preparedness · 2025
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Samuel R MendezDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0003-4402-1885
Sebastian Munoz-NajarHarvard Graduate School of Education, Cambridge, MA, United States.ORCID 0000-0002-4402-9564
Karen M EmmonsDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0002-0685-6446
Kasisomayajula ViswanathDepartment of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States.ORCID 0000-0002-4795-5803

Funding

U Mass Boston / DFHCC U54 Partnership (1 of 2)U54CA156732 · NCI · DANA-FARBER CANCER INST · PI Nikhil Wagle · 2010 to 2026
$25.6M
NCI NIH HHS U54 CA156732
6 · The paper itself

Abstract

backgroundTwitter (subsequently rebranded as X) is acknowledged by US health agencies, including the US Centers for Disease Control and Prevention (CDC), as an important public health communication tool. However, there is a lack of data describing its use by state health agencies over time. This knowledge is important amid a changing social media landscape in the wake of the COVID-19 pandemic.

objectiveThe study aimed to describe US state health agencies' use of Twitter from 2012 through 2022. Furthermore, we organized our data collection and analysis around the theoretical framework of the networked public to contribute to the broader literature on health communication beyond a single platform.

methodsWe used Twitter application programming interface data as indicators of state health agencies' engagement with the 4 key qualities of communication in a networked public: scalability, persistence, replicability, and searchability. To assess scalability, we calculated tweet volume and audience engagement metrics per tweet. To assess persistence, we calculated the portion of tweets that were manual retweets or included an account mention. To assess replicability, we calculated the portion of tweets that were retweets or quote tweets. To assess searchability, we calculated the portion of tweets using at least 1 hashtag.

resultsWe observed a COVID-19 pandemic-era shift in state health agency engagement with scalability. The overall volume of tweets increased suddenly from less than 50,000 tweets in 2019 to over 94,000 in 2020, resulting in an average of 5.3 per day. Though mean tweets per day fell in 2021 and 2022, this COVID-19 pandemic-era low was still higher than the pre-COVID-19 pandemic peak. We also observed a more fragmented approach to searchability aligning with the start of the COVID-19 pandemic. More state-specific hashtags were among the top 10 during the COVID-19 pandemic, compared with more general hashtags related to disease outbreaks and natural disasters in years before. We did not observe such a clear COVID-19 pandemic-era shift in engagement with replicability. The portion of tweets mentioning a CDC account gradually rose and fell around a peak of 7.0% in 2018. Similarly, the rate of retweets of a CDC account rose and fell gradually around a peak of 5.4% in 2018. We did not observe a clear COVID-19 pandemic-era shift in persistence. The portion of tweets mentioning any account reached a maximum of 21% in 2013. It oscillated for much of the study period before dropping off in 2021 and reaching a minimum of 10% in 2022. Before 2018, the top 10 mentioned accounts included at least 2 non-CDC or corporate accounts. From 2018 onward, state agencies were much more prominent.

conclusionsOverall, we observed a more fragmented approach to state health agency communication on Twitter during the pandemic, prioritizing volume over searchability, formally replicating existing messages, and leaving traces of interactions with other accounts.

Indexed as

COVID-19Public HealthSocial MediaCenters for Disease Control and Prevention, U.S.Health CommunicationHumansPandemicsSARS-CoV-2United Statescommunication toolCOVID-19 pandemicdata collectiondata sciencegovernment agencieshealth communicationinformation technologyinteractionmessagepublic healthsocial mediastate governmenttheoretical frameworktweetTwitter

Identifiers

PMID39752190
PMCPMC11742096

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.