Evidence map›Paper›PMID 35225193›Full record

ArticleEpidemiology and infection2022

Spatial epidemiological characteristics and exponential smoothing model application of tuberculosis in Qinghai Plateau, China.

Y Shang, T T Zhang, Z F Wang, B Z Ma, N Yang, Y T Qiu, B Li, Q Zhang, Q L Huang, K Y Liu

Abstract read
In one paragraph

Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 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

10 authors.

Y ShangDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.ORCID 0000-0002-1959-6030
T T ZhangDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
Z F WangDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
B Z MaQinghai Center for Disease Prevention and Control, Xining, Qinghai810007, China.
N YangDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
Y T QiuDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
B LiDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
Q ZhangDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
Q L HuangDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.
K Y LiuDepartment of Public Health, Qinghai University, Xining, Qinghai810001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The epidemic of tuberculosis has posed a serious burden in Qinghai province, it is necessary to clarify the epidemiological characteristics and spatial-temporal distribution of TB for future prevention and control measures. We used descriptive epidemiological methods and spatial statistical analysis including spatial correlation and spatial-temporal analysis in this study. Furthermore, we applied an exponential smoothing model for TB epidemiological trend forecasting. Of 43 859 TB cases, the sex ratio was 1.27:1 (M:F), and the average annual TB registered incidence was 70.00/100 000 of 2009-2019. More cases were reported in March and April, and the worst TB stricken regions were the prefectures of Golog and Yushu. High TB registered incidences were seen in males, farmers and herdsmen, Tibetans, or elderly people. 7132 cases were intractable, which were recurrent, drug resistant, or co-infected with other infections. Three likely cases clusters with significant high risk were found by spatial-temporal scan on data of 2009-2019. The exponential smoothing winters' additive model was selected as the best-fitting model to forecast monthly TB cases in the future. This research indicated that TB in Qinghai is still a serious threaten to the local residents' health. Multi-departmental collaboration and funds special for TB treatments and control are still needed, and the exponential smoothing model is promising which could be applied for forecasting of TB epidemic trend in this high-altitude province.

Indexed as

Models, StatisticalAdolescentAdultAgedChildChild, PreschoolChinaCluster AnalysisFemaleForecastingHumansIncidenceInfantInfant, NewbornMaleMiddle AgedCases clustersexponential smoothing modelQinghai Plateauspatial − temporal distributiontuberculosis

Identifiers

PMID35225193
PMCPMC8888277

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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.