Evidence map›Paper›PMID 36777468›Full record

ArticleChina CDC weekly2023

Epidemic Characteristics, High-Risk Areas and Space-Time Clusters of Human Brucellosis - China, 2020-2021.

Huimin Yang, Quilan Chen, Yu Li, Di Mu, Yanping Zhang, Wenwu Yin

Abstract read
In one paragraph

Article in China CDC weekly, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 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

6 authors.

Huimin YangKey Laboratory of Surveillance and Early-warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Quilan ChenKey Laboratory of Surveillance and Early-warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Yu LiKey Laboratory of Surveillance and Early-warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Di MuKey Laboratory of Surveillance and Early-warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Yanping ZhangKey Laboratory of Surveillance and Early-warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Wenwu YinKey Laboratory of Surveillance and Early-warning on Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Analyze the recent epidemiological and temporal-spatial characteristics of human brucellosis in China and provide information for adjusting strategies for brucellosis control. Methods: Human brucellosis data were obtained from the National Notifiable Disease Reporting System (NNDRS). A geographical information system (GIS) was used to visualize high-risk areas with annual incidence based on county (district) polygons. The space-time scan statistic (STSS) was applied to detect the space-time clusters of human brucellosis. Results: A total of 69,767 cases were reported from 2,083 counties in the mainland of China in 2021, a 47.7% increase from 2020 (47,425). About 95.5% of the total cases were centralized in northern China and 31.8% in Inner Mongolia (IM). The number of counties with an incidence exceeding 100 per 100,000 was 34 in 2020 and 65 in 2021. From 2020 to 2021, 24 space-time clusters were detected. The two primary clusters were located northeast of IM, including 109 counties. The secondary clusters affected 208 counties in 2020 and spread to 297 counties in 2021, the majority of which were located in the middle of IM, exhibiting a trend spreading west from IM to neighboring provincial-level administrative divisions (PLADs). Conclusions: From 2020 to 2021, the incidence of human brucellosis nationwide was exponential, demonstrating distinct spatiotemporal characteristics. Space-time clusters were located in IM and neighboring areas. Therefore, considerable efforts are required to curb this momentum.

Indexed as

Epidemiology characteristicsHuman brucellosisSpace-time clustering

Identifiers

PMID36777468
PMCPMC9902746

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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.