Evidence map›Paper›PMID 41170169›Full record

ArticleChina CDC weekly2025

Epidemiological Characteristics and Spatiotemporal Clustering Analysis of Human Rabies - China, 2005-2024.

Xi Chen, Jinhui Zhang, Shouming Lyu, Canjun Zheng, Wenwu Yin, Di Mu, Yanping Zhang

Abstract read
In one paragraph

Article in China CDC weekly, 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

7 authors.

Xi ChenNational 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 (Chinese Academy of Preventive Medicine), Beijing, China.
Jinhui ZhangNational 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 (Chinese Academy of Preventive Medicine), Beijing, China.
Shouming LyuChina Field Epidemiology Training Program, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing, China.
Canjun ZhengNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing, China.
Wenwu YinNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing, China.
Di MuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing, China.
Yanping ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention (Chinese Academy of Preventive Medicine), Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Rabies remains a significant zoonotic disease in China. Following comprehensive control measures implemented since 2006, annual human cases declined steadily from 2008 through 2023. However, 2024 witnessed a 36.9% increase in cases compared with 2023, indicating possible changes in transmission dynamics or control effectiveness. This study analyzes the epidemiological characteristics and spatiotemporal patterns of rabies from 2005 to 2024 to inform targeted prevention strategies. Methods: We employed descriptive epidemiological methods to analyze the spatiotemporal distribution and demographic characteristics of rabies cases in China. Spatial clustering was assessed using global and local Moran's I statistics ( Results: Following a peak of 3,300 cases in 2007, rabies incidence declined continuously for 16 years before resurging in 2024 (167 cases, representing a 36.9% increase compared with 2023). Cases remained geographically concentrated, with 76.0% occurring in six central and southern provincial-level administrative divisions. The majority of affected counties (74%) reported only a single case. Males (70.0%), farmers (68.6%), and individuals aged 41-70 years (53.8%) comprised the highest-risk populations. Spatial analysis revealed that High-High clusters decreased in number over time. These clusters also shifted geographically: from widespread distribution across southwestern provincial-level administrative divisions (PLADs) during 2005-2014 to concentration in central agricultural zones during 2020-2024, particularly along the border regions of Henan, Hunan, Hubei, and Anhui PLADs. We identified 352 high-frequency counties. Spatiotemporal scan statistics detected seven significant clusters during 2005-2024, all located in central and southwestern regions. Outbreaks within these clusters peaked during summer and autumn months (July-November) from 2006 to 2013, with no new clusters emerging after 2014. Conclusions: Our findings demonstrate that China's rabies control efforts have successfully transitioned the epidemic from widespread endemic transmission to sporadic occurrence with localized clustering. The 2024 resurgence occurred predominantly in historically endemic hotspots identified through spatial analysis. Sustaining these control achievements will require implementing precision prevention strategies specifically targeted at these persistent high-risk counties.

Indexed as

preventionrabiesspatiotemporal clusteringsurveillance

Identifiers

PMID41170169
PMCPMC12569532

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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.