Evidence map›Paper›PMID 40109434›Full record

ArticleFrontiers in public health2025

Public concerns analysis and early warning of Mpox based on network data platforms-taking Baidu and WeChat as example.

Kai Yang, Shuangfeng Fan, Jiali Deng, Jinjie Xia, Xiaoyuan Hu, Linlin Yu, Bin Wang, Wei Yu

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Kai Yang *Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu Center for Disease Control and Prevention, Chengdu, China.
Shuangfeng Fan *Chengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu Center for Disease Control and Prevention, Chengdu, China.
Jiali DengDepartment of Orthopaedics, The First Affiliated Hospital of Chengdu Medical College, Sichuan, China.
Jinjie XiaChengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu Center for Disease Control and Prevention, Chengdu, China.
Xiaoyuan HuEmergency Response Office, Xinjiang Uighur Autonomous Region Center for Disease Control and Prevention, Urumqi, China.
Linlin YuChengdu Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Chengdu Center for Disease Control and Prevention, Chengdu, China.
Bin WangComprehensive Emergency Office, Center for Disease Control and Prevention of Qingbaijiang District, Chengdu, China.
Wei YuComprehensive Emergency Office, Center for Disease Control and Prevention of Qingbaijiang District, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the outbreak of Mpox in non-endemic countries in May 2022, which has captured international attention. In response, this study leveraged the real-time, predictive, and wide coverage advantages of big data to reflect the public's needs and interests regarding the Mpox epidemic, and explore its potential early warning role. We carried out a systematic data search weekly on two major network data platforms-Baidu Search Index (BDI) and WeChat Search Index (WCI) in China, and the index data overview, main concern information, hotspot regional distribution were analyzed. Besides, the correlation between the search index and the number of new cases of Mpox globally and within China were also investigated. Our results showed that both BDI and WCI mirrored the trends of the Mpox epidemic, with peaks in interest aligning with the release of relevant policies and events. The public's interest evolved from basic knowledge of the disease to a focus on treatment and prevention, with attentiveness centrally placed in economically developed areas such as Guangdong, Beijing, and Shanghai. A positive correlation was observed between the Chinese epidemic and the BDI (

Indexed as

Big DataDisease OutbreaksChinaHumansMpox, MonkeypoxBaidubig dataearly warningMpoxpublic concernWeChat

Identifiers

PMID40109434
PMCPMC11919868

What OpenQuestion holds

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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.