Evidence map›Paper›PMID 38896444›Full record

ArticleJMIR public health and surveillance2024

Spatiotemporal Epidemiological Trends of Mpox in Mainland China: Spatiotemporal Ecological Comparison Study.

Shuli Ma, Jie Ge, Lei Qin, Xiaoting Chen, Linlin Du, Yanbo Qi, Li Bai, Yunfeng Han, Zhiping Xie, Jiaxin Chen and 1 more

Abstract readComparative Study
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. 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

11 authors.

Shuli MaSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0009-0003-1935-2604
Jie GeSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0000-0003-3120-6362
Lei QinScientific Research Office, Qiqihar Medical University, Qiqihar, China.ORCID 0009-0005-3055-2142
Xiaoting ChenScientific Research Office, Qiqihar Medical University, Qiqihar, China.ORCID 0009-0001-4006-0636
Linlin DuSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0000-0001-8868-6374
Yanbo QiSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0009-0007-2263-3457
Li BaiSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0009-0001-2060-4667
Yunfeng HanSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0000-0001-7697-7721
Zhiping XieSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0009-0009-3218-1620
Jiaxin ChenSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0000-0003-0846-9260
Yuehui JiaSchool of Public Health, Qiqihar Medical University, Qiqihar, China.ORCID 0000-0002-0098-5941

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe World Health Organization declared mpox an international public health emergency. Since January 1, 2022, China has been ranked among the top 10 countries most affected by the mpox outbreak globally. However, there is a lack of spatial epidemiological studies on mpox, which are crucial for accurately mapping the spatial distribution and clustering of the disease.

objectiveThis study aims to provide geographically accurate visual evidence to determine priority areas for mpox prevention and control.

methodsLocally confirmed mpox cases were collected between June and November 2023 from 31 provinces of mainland China excluding Taiwan, Macao, and Hong Kong. Spatiotemporal epidemiological analyses, including spatial autocorrelation and regression analyses, were conducted to identify the spatiotemporal characteristics and clustering patterns of mpox attack rate and its spatial relationship with sociodemographic and socioeconomic factors.

resultsFrom June to November 2023, a total of 1610 locally confirmed mpox cases were reported in 30 provinces in mainland China, resulting in an attack rate of 11.40 per 10 million people. Global spatial autocorrelation analysis showed that in July (Moran I=0.0938; P=.08), August (Moran I=0.1276; P=.08), and September (Moran I=0.0934; P=.07), the attack rates of mpox exhibited a clustered pattern and positive spatial autocorrelation. The Getis-Ord Gi

conclusionsHot spots and HH clustering of mpox attack rates identified by local spatial autocorrelation analysis should be considered key areas for precision prevention and control of mpox. Specifically, Guangdong, Beijing, and Tianjin provinces should be prioritized for mpox prevention and control. These findings provide geographically precise and visualized evidence to assist in identifying key areas for targeted prevention and control.

Indexed as

Disease OutbreaksAdolescentAdultAgedChildChild, PreschoolChinaFemaleHumansInfantMaleMiddle AgedMpox, MonkeypoxSpatio-Temporal AnalysisYoung Adultemergenciesmpoxprevention and controlpublic healthspatiotemporal analysis

Identifiers

PMID38896444
PMCPMC11229661

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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.