Evidence map›Paper›PMID 39213025›Full record

ArticleJournal of medical Internet research2024

Characteristics, Influence, Prevention, and Control Measures of the Mpox Infodemic: Scoping Review of Infodemiology Studies.

XiangYu Yan, Zhuo Li, Chunxia Cao, Longxin Huang, Yongjie Li, Xiangbin Meng, Bo Zhang, Maohe Yu, Tian Huang, Jiancheng Chen and 13 more

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2024. 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. Article
  2. Article
  3. Misinformation, disinformation, and fake news amid the new global Mpox emergency.Revista panamericana de salud publica = Pan American journal of public health · 2024
    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

23 authors.

XiangYu Yan *School of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.ORCID 0000-0002-1496-0358
Zhuo Li *Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, China.ORCID 0009-0000-3888-9376
Chunxia Cao *School of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.ORCID 0000-0003-4857-425X
Longxin HuangDepartment of Clinical Medicine, North Sichuan Medical College, Nanchong, China.ORCID 0009-0003-1700-2707
Yongjie LiSchool of Basic Medical Sciences, Peking University, Beijing, China.ORCID 0000-0003-4811-3947
Xiangbin MengDepartment of Cardiology, The First Hospital of Hebei Medical University, Shijiazhuang, China.ORCID 0000-0002-4252-7869
Bo ZhangSchool of Environmental Science and Engineering, Hainan University, Haikou, China.ORCID 0000-0003-2244-5388
Maohe YuTianjin Center for Disease Control and Prevention, Tianjin, China.ORCID 0000-0002-7466-1624
Tian HuangYunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0002-0512-6791
Jiancheng ChenXiamen Peiyang BCI & Smart Health Innovation Research Institution, Xiamen, China.ORCID 0009-0004-7297-7037
Wei LiYunnan Provincial Hospital of Traditional Chinese Medicine, Kunming, China.ORCID 0009-0004-5107-7988
Linhui HaoYunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0002-7914-938X
Dongsheng HuangBaoshan Prefecture Center for Disease Control and Prevention, Baoshan, China.ORCID 0000-0002-3984-4054
Bin YiLincang Prefecture Center for Disease Control and Prevention, Lincang, China.ORCID 0009-0002-4125-2450
Ming ZhangDepartment of Radiation Oncology, The Third Affiliated Hospital of Kunming Medical University & Tumor Hospital of Yunnan Province, Kunming, China.ORCID 0009-0009-6418-5239
Shun ZhaYunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0002-0912-9447
Haijun YangYan'An Hospital of Kunming City, Kunming, China.ORCID 0009-0007-0327-4532
Jian YaoSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China.ORCID 0009-0007-8044-5518
Pengjiang QianSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China.ORCID 0000-0002-5596-3694
Chun Kai LeungDepartment of Public and International Affairs, City University of Hong Kong, Hong Kong, China.ORCID 0000-0002-9255-796X
Haojun Fan *School of Disaster and Emergency Medicine, Tianjin University, Tianjin, China.ORCID 0000-0003-1111-0232
Pei Jiang *Department of Public Health, North Sichuan Medical College, Nanchong, China.ORCID 0009-0009-6518-7412
Tiejun Shui *Yunnan Center for Disease Control and Prevention, Kunming, China.ORCID 0000-0002-2224-0545

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe mpox pandemic has caused widespread public concern around the world. The spread of misinformation through the internet and social media could lead to an infodemic that poses challenges to mpox control.

objectiveThis review aims to summarize mpox-related infodemiology studies to determine the characteristics, influence, prevention, and control measures of the mpox infodemic and propose prospects for future research.

methodsThe scoping review was conducted based on a structured 5-step methodological framework. A comprehensive search for mpox-related infodemiology studies was performed using PubMed, Web of Science, Embase, and Scopus, with searches completed by April 30, 2024. After study selection and data extraction, the main topics of the mpox infodemic were categorized and summarized in 4 aspects, including a trend analysis of online information search volume, content topics of mpox-related online posts and comments, emotional and sentiment characteristics of online content, and prevention and control measures for the mpox infodemic.

resultsA total of 1607 articles were retrieved from the databases according to the keywords, and 61 studies were included in the final analysis. After the World Health Organization's declaration of an mpox public health emergency of international concern in July 2022, the number of related studies began growing rapidly. Google was the most widely used search engine platform (9/61, 15%), and Twitter was the most used social media app (32/61, 52%) for researchers. Researchers from 33 countries were concerned about mpox infodemic-related topics. Among them, the top 3 countries for article publication were the United States (27 studies), India (9 studies), and the United Kingdom (7 studies). Studies of online information search trends showed that mpox-related online search volume skyrocketed at the beginning of the mpox outbreak, especially when the World Health Organization provided important declarations. There was a large amount of misinformation with negative sentiment and discriminatory and hostile content against gay, bisexual, and other men who have sex with men. Given the characteristics of the mpox infodemic, the studies provided several positive prevention and control measures, including the timely and active publishing of professional, high-quality, and easy-to-understand information online; strengthening surveillance and early warning for the infodemic based on internet data; and taking measures to protect key populations from the harm of the mpox infodemic.

conclusionsThis comprehensive summary of evidence from previous mpox infodemiology studies is valuable for understanding the characteristics of the mpox infodemic and for formulating prevention and control measures. It is essential for researchers and policy makers to establish prediction and early warning approaches and targeted intervention methods for dealing with the mpox infodemic in the future.

Indexed as

InfodemicMpox, MonkeypoxSocial MediaHumansInternetPandemicscontent topicdigital healthinfodemicinfodemiologyinformation search volumempox

Identifiers

PMID39213025
PMCPMC11399743

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.