Spatial-temporal analysis of tuberculosis in Chongqing, China 2011-2018

Abstract

Background: China is a country with a high burden of pulmonary tuberculosis (PTB). Chongqing is in the southwest of China, where the notification rate of PTB ranks tenth in China. This study analyzed the temporal and spatial distribution characteristics of PTB in Chongqing in order to improve TB control measures. Methods: A spatial-temporal analysis has been performed based on the data of PTB from 2011 to 2018, which was extracted from the National Surveillance System. The effect of TB control was measured by variation trend of pathogenic positive PTB notification rate and total TB notification rate. Time series, spatial autonomic correlation and spatial-temporal scanning methods were used to identify the temporal trends and spatial patterns at county level. Results: A total of 188,528 cases were included in this study. A downward trend was observed in PTB between 2011 and 2018 in Chongqing. The peak of PTB notification occurred in late winter and early spring annually. By calculating the value of Global Moran's I and Local Getis's G i * , we found that PTB was spatially clustered and some significant hot spots were detected in the southeast and northeast of Chongqing. One most likely cluster and three secondary clusters were identified by Kulldorff's scan spatial-temporal Statistic. Conclusions: This study identified seasonal patterns and spatial-temporal clusters of PTB cases in Chongqing. Priorities should be given to southeast and northeast of Chongqing for better TB control.

Spatial Analysis of a Tuberculosis Incidence in Magelang City in 2021

“…The denser population in certain areas, the spread of tuberculosis would be more likely to occur. And there was no difference in cases of tuberculosis in areas with high population density and low population density [23][24]. Population density could determine the speed of disease transmission, also determined the quality of health services and the number of patients in an emergency (the number of sufferers if there was a sudden change such as an extraordinary event).…”

Distribution of bacteriologically positive and bacteriologically negative pulmonary tuberculosis in Northwest China: spatiotemporal analysis

“…Therefore, bias was minimised as much as possible. In addition, PTB cases were notified according to their current address instead of the address of the hospital where they were diagnosed 12 . The geographical distribution of PTB cases was not affected by the location of doctors who attended them.…”

“…Most of the previous studies on the spatiotemporal patterns of PTB only considered all PTB cases as a whole and did not distinguish notified BP-PTB and notified bacteriologically negative PTB (BN-PTB) 11 , 12 . BP-PTB is the most infectious type of PTB and even contributes to outbreaks in crowds.…”

Tuberculosis space-temporal distribution from 2011 to 2016 in the municipality of Maputo, Mozambique

“…Munch et al (2003) used a GIS to analyze spatial patterns of TB transmission in a high-incidence area in South Africa. In China, the Spatial-temporal analysis of tuberculosis was evaluated for Chongqing, between 2011 and 2018 (Yu et al 2020). Kumar et al (2014) analyzed a time-series to discover the seasonality of tuberculosis in Delhi, India.…”

“…In the Mozambican municipalities and regions, García-Basteiro et al (2017) analyzed the TB notification time-series (1997 to 2012) to assess the evolution of incidence rates and other key indicators of the disease in the district of Manhiça. In this sense, the analysis of the Spatio-temporal of diseases by GIS can support the development of public intervention actions aiming to contain the disease proliferation, being a strategy adopted by many countries (Munch et al 2003;Kumar et al 2014;García-Basteiro et al 2017;Gashu et al 2018;Wardani and Wahono, 2020;Wang et al 2020;Yu et al 2020).…”