Evidence map›Paper›PMID 40559726›Full record

ArticleTropical medicine and infectious disease2025

Epidemiological Characteristics and Trends of Zoonotic Diseases in China from 2015 to 2022.

Yunfei Zhang, Mengjie Geng, Yue Shi, Baijun Jin, Qian Xiong, Sheng Zhou, Jiangmei Liu, Biao Kan, Maigeng Zhou, Tian Qin and 1 more

Abstract read
In one paragraph

Article in Tropical medicine and infectious disease, 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. Review
  2. Review
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

11 authors.

Yunfei ZhangNational Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0002-4698-5314
Mengjie GengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Yue ShiNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Baijun JinJilin Province for Disease Control and Prevention, Jilin 130062, China.
Qian XiongSchool of Health Policy and Management, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.
Sheng ZhouNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Jiangmei LiuNational Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Biao KanNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Maigeng ZhouNational Center for Chronic and Non-Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.ORCID 0000-0002-1046-6803
Tian QinNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Canjun ZhengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China.ORCID 0000-0001-6822-8755

Funding

National Natural Science Foundation of China 82073675Operation Project of Public Health Emergency Response Mechanism of Chinese Center for Disease Control and Prevention 102393220020010000017
6 · The paper itself

Abstract

This study aimed to analyze the epidemiological characteristics and incidence trends of zoonotic diseases in China from 2015 to 2022, providing evidence for zoonotic disease prevention and control strategies. Individual case data for nationally reported zoonotic diseases from the Chinese Disease Prevention and Control Information System were collected. Descriptive epidemiology and statistical methods were employed to analyze trends along with changes in their spatial, temporal, and demographic distributions. From 2015 to 2022, the annual incidence rates of leishmaniasis, Japanese encephalitis, rabies, echinococcosis, hemorrhagic fever with renal syndrome (HFRS), and schistosomiasis showed a fluctuating downward trend. The incidence rates of anthrax and leptospirosis remained relatively stable. The incidence of brucellosis declined from 2015 to 2018 but subsequently increased through 2022. Western provinces, such as Gansu, Ningxia, Qinghai, Xinjiang, and Yunnan, remain high-incidence areas for multiple zoonotic diseases, with farmers being the population at the highest risk. These findings indicate it is essential to strengthen cross-sectoral cooperation and develop region- and population-specific prevention and control strategies based on the 'One Health' concept, particularly in areas with high incidence rates and among high-risk populations.

Indexed as

Chinaepidemiological characteristicszoonoses

Identifiers

PMID40559726
PMCPMC12197502

What OpenQuestion holds

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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.