Evidence map›Paper›PMID 41356278›Full record

ArticleThe Lancet regional health. Western Pacific2025

Epidemiological analysis of infectious diseases in older people in China from 2014 to 2022: a population-based study.

Sheng-Hong Lin, Chen-Long Lv, Meng-Jie Geng, Rui-Cheng Gao, Yan-Qun Sun, Yan-He Wang, Ya-Ming Zheng, Tian Tang, Chun-Xi Shan, Yao Tian and 12 more

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

22 authors.

Sheng-Hong LinState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Chen-Long LvState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Meng-Jie GengDivision of Infectious Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Rui-Cheng GaoDepartment of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Yan-Qun SunClinical Research Center, Children's Hospital of Nanjing Medical University, Nanjing, China.
Yan-He WangThe 968th Hospital of Joint Logistics Support Force of PLA, Jinzhou, Liaoning, China.
Ya-Ming ZhengDivision of Infectious Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Tian TangState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Chun-Xi ShanState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Yao TianState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Yun-Bo QiuState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Jun MaState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Yan ZhangState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Yu-Feng YangState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Qiang XuState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Guo-Lin WangState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Yan-Ping ZhangDivision of Infectious Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Qun LiChinese Center for Disease Control and Prevention, Beijing, China.
Li-Ping WangDivision of Infectious Disease Control and Prevention, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Peng-Tao BaoSenior Department of Pulmonary and Critical Care Medicine, The Eighth Medical Center of Chinese PLA General Hospital, Beijing, China.
Li-Qun FangState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.
Wei LiuState Key Laboratory of Pathogen and Biosecurity, Academy of Military Medical Science, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The whole world is undergoing an unprecedented rapid population aging, and the accompanying threat of infectious diseases epidemic among the older people will pose a serious challenge to the national public health. Methods: We extracted individual data on 21 notifiable infectious diseases (NIDs) among individuals aged ≥60 years from the Chinese Infectious Disease Surveillance and Control Project (CISDCP) from 2014 to 2022 in the mainland of China. We comprehensively analyzed the epidemiological characteristics of NIDs in older people and estimated the impact of age, year, and the COVID-19 pandemic. Findings: A total of 8,604,064 cases of 21 major NIDs were reported, with an overall annual incidence of 362·10/100,000. Sexually transmitted or bloodborne diseases (STBDs, 45·23%) were the most common diseases. Notably, ranking of syphilis rose from fourth to third, while HIV/AIDS moved from eighth to seventh; respiratory diseases (34·88%) showed sustained declines. Tuberculosis remained the most common respiratory diseases despite a 6·4% annual decline (APC, P < 0·001); gastrointestinal or enteroviral diseases (GEDs, 18·35%) showed sustained declines, except for infectious diarrhea and hepatitis E; vector-borne or zoonotic diseases (VBZDs, 1·54%) remained low, though brucellosis increased during COVID-19 pandemic. Inflection point analysis revealed that 13 diseases, such as tuberculosis, infectious diarrhea, hepatitis B, and others, exhibited a quadratic distribution (inverted "V" shape) in age-specific incidence as age increased. Difference was noticeable between regions, with the older people in Inner Mongolia-Xinjiang region and South China region continuing to carry a disproportionate burden from NIDs. Interpretation: Although China's success in infectious disease control in older people. Effective prevention and control strategies are needed for highest incidence diseases, such as tuberculosis, hepatitis B, and infectious diarrhea, especially in high-incidence regions and among critical age points. Funding: National Major Research & Development Program of China (2022YFC2604000).

Indexed as

Infectious diseasesNational surveillanceOlder peoplePublic health

Identifiers

PMID41356278
PMCPMC12677096

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.