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Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Jun 12, 2023
Date Accepted: Sep 19, 2023

The final, peer-reviewed published version of this preprint can be found here:

Trend of the Tuberculous Pleurisy Notification Rate in Eastern China During 2017-2021: Spatiotemporal Analysis

Zhou Y, Luo D, Liu K, Chen B, Chen S, Liu Z, Pan J, Jiang J

Trend of the Tuberculous Pleurisy Notification Rate in Eastern China During 2017-2021: Spatiotemporal Analysis

JMIR Public Health Surveill 2023;9:e49859

DOI: 10.2196/49859

PMID: 37902822

PMCID: 10644181

Spatiotemporal Trend in Tuberculous Pleurisy notification rate in Eastern China during 2017–2021: Spatiotemporal Analysis

  • Ying Zhou; 
  • Dan Luo; 
  • Kui Liu; 
  • Bin Chen; 
  • Songhua Chen; 
  • Zhengwei Liu; 
  • Junhang Pan; 
  • Jiangmin Jiang

ABSTRACT

Background:

Tuberculosis pleurisy (TP) presents a serious allergic reaction in pleura caused by Mycobacterium tuberculosis; however, few studies have described its spatial epidemiological characteristics in eastern China.

Objective:

This study aimed to determine the epidemiological distribution of TP and predict its further development in the Zhejiang Province.

Methods:

Data on all notified cases of TP in Zhejiang Province, China, from 2017 to 2021 were collected using the existing tuberculosis management information system. Analysis including spatial autocorrelation and spatial-temporal scan analysis, were performed to identify incidence hot spots and clusters, respectively. Prediction of TP was performed by Autoregressive Integrated Moving Average (SARIMA) model, Holt-Winters exponential smoothing model (H-W ETS) and Prophet model using R (4.2.0) and SPSS 27 software.

Results:

The average incidence of TP in Zhejiang Province was 7.06/100,000, peaking in the summer. The male-to-female ratio was 2.18:1. In terms of geographical distribution, clusters of cases were observed in the western part of Zhejiang Province, including part of Hangzhou, Quzhou, Jinhua, Lishui, Wenzhou and Taizhou city. Spatial-temporal analysis identified one most likely cluster and four secondary clusters. The Holt-Winters model outperformed SARIMA and Prophet in predicting the trend in TP prevalence.

Conclusions:

The western region of Zhejiang Province poses the highest risk of TP. Comprehensive interventions, such as chest X-ray screening and symptom screening, should be reinforced to improve the early identification. Additionally, a more systematic assessment of the prevalence trend of TP should include more predictors.


 Citation

Please cite as:

Zhou Y, Luo D, Liu K, Chen B, Chen S, Liu Z, Pan J, Jiang J

Trend of the Tuberculous Pleurisy Notification Rate in Eastern China During 2017-2021: Spatiotemporal Analysis

JMIR Public Health Surveill 2023;9:e49859

DOI: 10.2196/49859

PMID: 37902822

PMCID: 10644181

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