Spatiotemporal analysis and seasonality of tuberculosis in Pudong New Area of Shanghai, China, 2014–2023

• Published in: BMC infectious diseases Vol. 24; no. 1; pp. 761 - 11
• Main Authors: Pan, Shuishui, Chen, Lili, Xin, Xin, Li, Shihong, Zhang, Yixing, Chen, Yichen, Xiao, Shaotan
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 31.07.2024; BioMed Central; BMC
• Subjects: Analysis; Autocorrelation; China; China - epidemiology; Cluster Analysis; Clustering; Disease control; Disease hot spots; Disease prevention; Epidemiology; Geographic Information Systems; Geographical distribution; Geography; Health aspects; Humans; Incidence; Infectious diseases; Mortality; Population; Public health; Pudong New Area; Remote sensing; Risk analysis; Seasonal distribution; Seasonal variations; Seasonality; Seasons; Space-time scan analysis; Spatial analysis; Spatial autocorrelation analysis; Spatial distribution; Spatio-Temporal Analysis; Temporal distribution; Towns; Trends; Tuberculosis; Tuberculosis - epidemiology; China; Shanghai China; Space-time scan analysis; Pudong New Area; Tuberculosis; Spatial autocorrelation analysis; Seasonality
• ISSN: 1471-2334; 1471-2334
• DOI: 10.1186/s12879-024-09645-x

Spatiotemporal analysis is a vital method that plays an indispensable role in monitoring epidemiological changes in diseases and identifying high-risk clusters. However, there is still a blank space in the spatial and temporal distribution of tuberculosis (TB) incidence rate in Pudong New Area, Shanghai. Consequently, it is crucial to comprehend the spatiotemporal distribution of TB in this district, this will guide the prevention and control of TB in the district. Our research used Geographic Information System (GIS) visualization, spatial autocorrelation analysis, and space-time scan analysis to analyze the TB incidence reported in the Pudong New Area of Shanghai from 2014 to 2023, and described the spatiotemporal clustering and seasonal hot spot distribution of TB incidence. From 2014 to 2023, the incidence of TB in the Pudong New Area decreased, and the mortality was at a low level. The incidence of TB in different towns/streets has declined. The spatial autocorrelation analysis revealed that the incidence of TB was spatially clustered in 2014, 2016-2018, and 2022, with the highest clusters in 2014 and 2022. The high clustering area was mainly concentrated in the northeast. The space-time scan analysis indicated that the most likely cluster was located in 12 towns/streets, with a period of 2014-2018 and a radiation radius of 15.74 km. The heat map showed that there was a correlation between TB incidence and seasonal variations. From 2014 to 2023, the incidence of TB in the Pudong New Area of Shanghai declined, but there were spatiotemporal clusters and seasonal correlations in the incidence area. Local departments should formulate corresponding intervention measures, especially in high-clustering areas, to achieve accurate prevention and control of TB within the most effective time and scope.