Evidence map›Paper›PMID 39656721›Full record

ArticlePLoS neglected tropical diseases2024

Retrospective analysis of spatiotemporal variation of scrub typhus in Yunnan Province, 2006-2022.

Zhuo Li, Shuzhen Deng, Tian Ma, Jiaxin Hao, Hao Wang, Xin Han, Menghan Lu, Shanjun Huang, Dongsheng Huang, Shuyuan Yang and 2 more

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Analysis of the Epidemiological Characteristics and Risk Factors for Severe Progression of Scrub Typhus in the Dali Region of China.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Article
  3. Article
  4. Article
  5. 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

12 authors.

Zhuo LiState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Shuzhen DengYunnan Center for Disease Control and Prevention, Kunming, Yunnan, China.
Tian MaState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Jiaxin HaoState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Hao WangState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Xin HanState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Menghan LuState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Shanjun HuangState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.
Dongsheng HuangBaoshan Prefecture Center for Disease Control and Prevention, Baoshan, Yunnan, China.
Shuyuan YangKunming center for Disease Control and Prevention, Kunming, Yunnan, China.
Qing ZhenState Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonoses Research of the Ministry of Education, Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, PR China.ORCID 0000-0002-2816-4539
Tiejun ShuiYunnan Center for Disease Control and Prevention, Kunming, Yunnan, China.ORCID 0000-0003-3302-2428

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScrub typhus is a life-threatening zoonotic infection. In recent years, the endemic areas of scrub typhus have been continuously expanding, and the incidence rate has been increasing. However, it remains a globally neglected disease. Yunnan Province is a major infected area, and the study of spatiotemporal and seasonal variation scrub typhus in this region is crucial for the prevention and control of the disease. METHODS/

resultsWe collected surveillance data on scrub typhus cases in Yunnan Province from 2006 to 2022. Using methods such as spatial trend analysis, Moran's I, and retrospective temporal scan statistics, the spatial and seasonal changes of scrub typhus were analyzed. The study period recorded 71,068 reported cases of scrub typhus in Yunnan Province, with the annual incidence rate sharply increasing (P<0.001). Approximately 93.38% of cases are concentrated in June to November (P = 0.001). Nearly 98.0% of counties were affected. The center of gravity of incidence migrates in a south and west direction. The incidence of scrub typhus was positively correlated spatially, and the spatial clustering distribution was significant. The most likely spatial cluster of cases (relative risk = 14.09, P<0.001) was distributed in Lincang, Dehong, Baoshan, Banna, and Puer. Significant positive correlations between the number of scrub typhus cases and average temperature, precipitation and relative humidity.

conclusionsIn Yunnan Province, scrub typhus is widely transmitted, with an increasing incidence, and it exhibits distinct seasonal characteristics (from June to November). The center of gravity of incidence has shifted to the south and west, with higher incidence rates observed in border regions. The risk clustering regions encompass all border prefectures. This pattern is significantly correlated with climatic factors such as average temperature, precipitation, and relative humidity. The relevant departments should strengthen the monitoring of scrub typhus, formulate prevention and control strategies, and provide health education to local residents.

Indexed as

Scrub TyphusSeasonsSpatio-Temporal AnalysisChinaFemaleHumansIncidenceMaleRetrospective Studies

Identifiers

PMID39656721
PMCPMC11630589

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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.