Evidence map›Paper›PMID 41955459›Full record

ArticleJournal of medical Internet research2026

Misinformation in Social Media Narratives on Highly Pathogenic Avian Influenza: Systematic Content Analysis of Facebook and Instagram Posts.

Ahmed Al-Rawi, Betty Ackah, Abdelrahman Fakida, Kelley Lee

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ahmed Al-Rawi *School of Communication, Simon Fraser University, Schrum Science Centre-K 9653, Burnaby, BC, V5A1S6, Canada, 1 (778) 782-3117.ORCID http://orcid.org/0000-0001-7336-1550
Betty Ackah *School of Communication, Simon Fraser University, Schrum Science Centre-K 9653, Burnaby, BC, V5A1S6, Canada, 1 (778) 782-3117.ORCID http://orcid.org/0000-0003-3689-1880
Abdelrahman Fakida *School of Communication, Simon Fraser University, Schrum Science Centre-K 9653, Burnaby, BC, V5A1S6, Canada, 1 (778) 782-3117.ORCID http://orcid.org/0000-0002-6307-0351
Kelley Lee *Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada.ORCID http://orcid.org/0000-0002-3625-1915

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Recurrent outbreaks of the highly pathogenic avian influenza (HPAI) A (H5N1) virus in farmed poultry, and reports of infections in dairy cattle herds in the United States since March 2024, have triggered concerns about the spillover threat to human populations and a subsequent influenza pandemic. The increasing threat that H5N1 poses to human health has led to more vigilant public health monitoring of these developments. In addition to intensifying surveillance, preventative strategies-like vaccinating those at higher risk-are being evaluated to help minimize infection and spread. Objective: Efforts to mitigate and respond to such an event will entail broad public health interventions including vaccination. However, analysis of the COVID-19 pandemic suggests that information quality can significantly impact the effectiveness of such measures by influencing public understanding and trust. Misinformation about H5N1 and other viruses circulating online often includes inaccurate information about transmission, prevention, and the severity of the viruses. By systematically analyzing these false narratives, public health authorities can better tailor their pandemic prevention, preparedness, and response strategies. Methods: In light of the emerging threat of H5N1, we analyzed the content of social media posts from Facebook (approximately 350,000) and Instagram (n=69,551) related to HPAI. Using 40 keywords associated with misinformation, we identified over 500 posts explicitly mentioning H5N1 and related terms for further systematic analysis. Posts were coded to identify targets and topics in the social media narratives. The "target" refers to the organization or person mentioned in the post, while the "topic" refers to the primary issue or subject being addressed. Results: Our content analysis identifies 7 main targets of misinformation, including government (149/544, 27%), health authorities (108/544, 20%), and international organizations (74/544, 14%). Also, from the 6 topics that have been identified, we found that the most widespread one was that authority figures purposefully engineer pandemics to achieve multiple political, economic, and other objectives (362/544, 67%) followed by societal destruction (121/544, 22%), and anti-vaccination (84/544, 15%). Other themes include societal destruction and religious allusions and prophecies. Conclusions: Our analysis of online content showed that H5N1 misinformation was primarily aimed at individuals or groups with differing degrees of political or institutional authority, such as government leaders and public health officials. These figures were often the focus due to their involvement in making health policy decisions and implementing public health measures. Decision-making entities and individuals were the target of various misinformation narratives. Results demonstrate the ongoing need for monitoring health misinformation to inform evolving public health responses to HPAI.

Indexed as

CommunicationInfluenza A Virus, H5N1 SubtypeInfluenza, HumanInfluenza in BirdsSocial MediaAnimalsHumansPandemicsH5N1health communicationhighly pathogenic avian influenzamisinformationsocial media

Identifiers

PMID41955459
PMCPMC13064957

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.