Evidence map›Paper›PMID 38827562›Full record

ArticleInfectious medicine2024

Expert consensus on One Health for establishing an enhanced and integrated surveillance system for key infectious diseases.

Yanpeng Cheng, Zhen Zhang, Yuelong Shu, Lili Ren, Min Kang, Dongfeng Kong, Xiaolu Shi, Qiuying Lv, Zhigao Chen, Yinghui Li and 21 more

Abstract read
In one paragraph

Article in Infectious medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

31 authors.

Yanpeng ChengShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Zhen ZhangShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Yuelong ShuInstitute of Medical Biology, Chinese Academy of Medical Sciences, Beijing 100000, China.
Lili RenInstitute of Medical Biology, Chinese Academy of Medical Sciences, Beijing 100000, China.
Min KangGuangdong Provincial Center for Disease Control and Prevention, Guangzhou 510000, China.
Dongfeng KongShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Xiaolu ShiShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Qiuying LvShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Zhigao ChenShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Yinghui LiShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Renli ZhangShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Puxuan LuElectronic Journal of Emerging Infectious Diseases, Shenzhen 518000, China.
Yan LuShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Tingting LiuShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Nixuan ChenShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Huawei XiongShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Chen DuShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Jun YuanGuangzhou Center for Disease Control and Prevention, Guangzhou 510000, China.
Liang WangChengdu Center for Disease Control and Prevention, Chengdu 610000, China.
Rongqi LiuShenzhen Animal Disease Prevention and Control Center, Shenzhen 518000, China.
Weihong ChenLuohu District Center for Disease Control and Prevention, Shenzhen 518000, China.
Xueyun LiFutian District Center for Disease Control and Prevention, Shenzhen 518000, China.
Qihui LinLonghua District Center for Disease Control and Prevention, Shenzhen 518000, China.
Gang LiLonggang District Center for Disease Control and Prevention, Shenzhen 518000, China.
Xindong ZhangBaoan District Center for Disease Control and Prevention, Shenzhen 518000, China.
Jianhui YuanNanshan District Center for Disease Control and Prevention, Shenzhen 518000, China.
Tieqiang WangGuangming District Center for Disease Control and Prevention, Shenzhen 518000, China.
Yongchao GuoShenzhen Uni-medical Technology Co., Ltd, Shenzhen 518000, China.
Jianhua LuShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Xuan ZouShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.
Tiejian FengShenzhen Center for Disease Control and Prevention, Shenzhen 518000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China has been continuously improving its monitoring methods and strategies to address key infectious diseases (KIDs). After the severe acute respiratory syndrome epidemic in 2003, China established a comprehensive reporting system for infectious diseases (IDs) and public health emergencies. The relatively lagging warning thresholds, limited warning information, and outdated warning technology are insufficient to meet the needs of comprehensive monitoring for modern KIDs. Strengthening early monitoring and warning capabilities to enhance the public health system has become a top priority, with increasing demand for early warning thresholds, information, and techniques, thanks to constant innovation and development in molecular biology, bioinformatics, artificial intelligence, and other identification and analysis technologies. A panel of 31 experts has recommended a fourth-generation comprehensive surveillance system targeting KIDs (41 notifiable diseases and emerging IDs). The aim of this surveillance system is to systematically monitor the epidemiology and causal pathogens of KIDs in hosts such as humans, animals, and vectors, along with associated environmental pathogens. By integrating factors influencing epidemic spread and risk assessment, the surveillance system can serve to detect, predict, and provide early warnings for the occurrence, development, variation, and spread of known or novel KIDs. Moreover, we recommend comprehensive ID monitoring based on the fourth-generation surveillance system, along with a data-integrated monitoring and early warning platform and a consortium pathogen detection technology system. This series of considerations is based on systematic and comprehensive monitoring across multiple sectors, dimensions, factors, and pathogens that is supported by data integration and connectivity. This expert consensus will provides an opportunity for collaboration in various fields and relies on interdisciplinary application to enhance comprehensive monitoring, prediction, and early warning capabilities for the next generation of ID surveillance. This expert consensus will serve as a reference for ID prevention and control as well as other related activities.

Indexed as

Emerging infectious diseaseExpert consensusInfectious diseaseKey infectious diseasesOne HealthSurveillance system

Identifiers

PMID38827562
PMCPMC11141439

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.