Evidence map›Paper›PMID 28056840›Full record

ArticleBMC infectious diseases2017

Rapid increase of scrub typhus incidence in Guangzhou, southern China, 2006-2014.

Ye Sun, Yue-Hong Wei, Yang Yang, Yu Ma, Sake J de Vlas, Hong-Wu Yao, Yong Huang, Mai-Juan Ma, Kun Liu, Xiao-Ning Li and 5 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

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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

15 authors.

Ye SunThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Yue-Hong WeiGuangzhou Center for Disease Control and Prevention, Guangdong Province, Guangzhou, 510440, People's Republic of China.
Yang YangDepartment of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, 32311, Florida, USA.
Yu MaGuangzhou Center for Disease Control and Prevention, Guangdong Province, Guangzhou, 510440, People's Republic of China.
Sake J de VlasDepartment of Public Health, Erasmus Medical Center, University Medical Center Rotterdam, 999025, Rotterdam, The Netherlands.
Hong-Wu YaoThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Yong HuangGuangzhou Center for Disease Control and Prevention, Guangdong Province, Guangzhou, 510440, People's Republic of China.
Mai-Juan MaThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Kun LiuThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Xiao-Ning LiGuangzhou Center for Disease Control and Prevention, Guangdong Province, Guangzhou, 510440, People's Republic of China.
Xin-Lou LiThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Wen-Hui ZhangThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China.
Li-Qun FangThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China. fanglq@bmi.ac.cn.
Zhi-Cong YangGuangzhou Center for Disease Control and Prevention, Guangdong Province, Guangzhou, 510440, People's Republic of China. yangzc@gzcdc.org.cn.
Wu-Chun CaoThe State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, 20 Dong-Da Street, Fengtai District, Beijing, 100071, People's Republic of China. caowc@bmi.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the last decade, scrub typhus (ST) has been emerging or re-emerging in some areas of Asia, including Guangzhou, one of the most affected endemic areas of ST in China.

methodsBased on the data on all cases reported in Guangzhou from 2006 to 2014, we characterized the epidemiological features, and identified environmental determinants for the spatial distribution of ST using a panel negative binomial model.

resultsA total of 4821 scrub typhus cases were reported in Guangzhou during 2006-2014. The annual incidence increased noticeably and the increase was relatively high and rapid in rural townships and among elderly females. The majority of cases (86.8%) occurred during May-October, and farmers constituted the majority of the cases, accounting for 33.9% in urban and 61.6% in rural areas. The number of housekeeper patients had a rapid increment in both rural and urban areas during the study period. Atmospheric pressure and relative humidity with lags of 1 or 2 months, distributions of broadleaved forest and rural township were identified as determinants for the spatiotemporal distribution of scrub typhus.

conclusionOur results indicate that surveillance and public education need to be focused on the elderly farmers in rural areas covered with broadleaf forest in southern China.

Indexed as

AgedAged, 80 and overChinaFemaleHumansIncidenceMaleMiddle AgedModels, StatisticalRisk FactorsRural PopulationScrub TyphusSeasons

Identifiers

PMID28056840
PMCPMC5216553

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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.