Evidence map›Paper›PMID 25412324›Full record

ArticlePLoS neglected tropical diseases2014

Spatiotemporal transmission dynamics of hemorrhagic fever with renal syndrome in China, 2005-2012.

Wen-Yi Zhang, Li-Ya Wang, Yun-Xi Liu, Wen-Wu Yin, Wen-Biao Hu, Ricardo J Soares Magalhaes, Fan Ding, Hai-Long Sun, Hang Zhou, Shen-Long Li and 7 more

Erratum issuedAbstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 pooled it
–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

49 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  9. Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation.Proceedings of the National Academy of Sciences of the United States of America · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Wen-Yi ZhangInstitute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.
Li-Ya WangInstitute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.
Yun-Xi LiuDepartment of Infection Management and Disease Control, Chinese PLA General Hospital, Beijing, People's Republic of China.
Wen-Wu YinChinese Center for Disease Control and Prevention, Beijing, People's Republic of China.
Wen-Biao HuSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Ricardo J Soares MagalhaesSchool of Veterinary Science, The University of Queensland, Brisbane, Australia; WHO Collaborating Centre for Children Environmental Health, Queensland Children's Medical Research Institute, University of Queensland, Brisbane, Australia.
Fan DingChinese Center for Disease Control and Prevention, Beijing, People's Republic of China.
Hai-Long SunInstitute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.
Hang ZhouChinese Center for Disease Control and Prevention, Beijing, People's Republic of China.
Shen-Long LiInstitute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.
Ubydul HaqueEmerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America; Department of Geography, University of Florida, Gainesville, Florida, United States of America.
Shi-Lu TongSchool of Public Health and Social Work, Queensland University of Technology, Brisbane, Australia.
Gregory E GlassEmerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America; Department of Geography, University of Florida, Gainesville, Florida, United States of America.
Peng BiDiscipline of Public Health, University of Adelaide, Adelaide, Australia.
Archie C A ClementsResearch School of Population Health, The Australian National University, Canberra, Australian Capital Territory, Australia.
Qi-Yong LiuState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China.
Cheng-Yi LiInstitute of Disease Control and Prevention, Academy of Military Medical Science, Beijing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem with 90% of the total reported cases in the world. This study describes the spatiotemporal dynamics of HFRS cases in China and identifies the regions, time, and populations at highest risk, which could help the planning and implementation of key preventative measures.

methodsData on all reported HFRS cases at the county level from January 2005 to December 2012 were collected from Chinese Center for Disease Control and Prevention. Geographic Information System-based spatiotemporal analyses including Local Indicators of Spatial Association and Kulldorff's space-time scan statistic were performed to detect local high-risk space-time clusters of HFRS in China. In addition, cases from high-risk and low-risk counties were compared to identify significant demographic differences.

resultsA total of 100,868 cases were reported during 2005-2012 in mainland China. There were significant variations in the spatiotemporal dynamics of HFRS. HFRS cases occurred most frequently in June, November, and December. There was a significant positive spatial autocorrelation of HFRS incidence during the study periods, with Moran's I values ranging from 0.46 to 0.56 (P<0.05). Several distinct HFRS cluster areas were identified, mainly concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties.

conclusionsThis study identified significant space-time clusters of HFRS in China during 2005-2012 indicating that preventative strategies for HFRS should be particularly focused on the northeastern, central, and eastern of China to achieve the most cost-effective outcomes.

Indexed as

AdultChinaCluster AnalysisFemaleHemorrhagic Fever with Renal SyndromeHumansIncidenceMaleMiddle AgedSpatio-Temporal Analysis

Identifiers

PMID25412324
PMCPMC4239011

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Registered trials

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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.