TB Research

Research on the spatial clustering of tuberculosis cases in Wenshan Prefecture, Yunnan Province from 2009 to 2018

Zizhao Zhao, Zhong Sun, Songwang Yang, Hongyu Chen, Dihan Li, Rong Li, Yuzhuo Zhang, Shiyuan Dai, et al. (14 authors)

Abstract

Objective: This research is to describe the current situation of tuberculosis epidemic in Wenshan Prefecture and explore the spatial clustering distribution characteristics of cases..Methods: The number of reported cases of tuberculosis in Wenshan Prefecture from 2009 to 2018 was epidemiological description and spatial autocorrelation analysis.Results: From 2009 to 2018, the number of reported cases of tuberculosis in Wenshan Prefecture was 10,210. The cumulative reported cases were 17,972 males (66.31%), and 9131 females (33.69%). The age distribution of the affected population was 44.58±16.60 years old, mainly concentrated in over 60 years old age group (6653 persons, accounting for 24.55%) and the 19–29 year-old group (5066 persons, accounting for 18.69%); the occupational composition of the cases was mainly farmers (24084 cases, accounting for 88.86%), followed by students (748 cases, (2.76%); Moran’s I index of the reported cases were all greater than 0, indicating that the distribution of tuberculosis cases in the spatial unit was positively correlated, with (Z>1.96)and (P<0.05), and the difference was statistically significant.Conclusion: From 2009 to 2018, the number of reported cases in Wenshan Prefecture of Yunnan Province showed an overall upward trend, and the distribution of cases in spatial units was positively correlated with spatial clustering as a whole; hot spots were mainly concentrated in the middle of Wenshan Prefecture, and cold spots were mainly concentrated in the south . In addition to the implementation of basic public health services, personalized health education methods should also be adopted for border ethnic minority areas, so as to further control the prevalence and spread of tuberculosis in border areas.

MeSH terms

  • Cluster analysis
  • Tuberculosis
  • Geography
  • Computer science