Dataset Information

Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015.

ABSTRACT:

Background

Tuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it.

Methods

The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff's retrospective space-time scan statistics was used to identify the temporal, spatial and spatio-temporal clusters of reported TB in the mainland of China by using the discrete Poisson probability model. Spatio-temporal clusters of sputum smear-positive (SS+) reported TB and sputum smear-negative (SS-) reported TB were also detected at the prefecture level.

Results

A total of 10?200?528 reported TB cases were collected from 2005 to 2015 in 340 prefectures, including 5?283?983 SS- TB cases and 4?631?734 SS?+?TB cases with specific sputum smear results, 284?811 cases without sputum smear test. Significantly TB clustering patterns in spatial, temporal and spatio-temporal were observed in this research. Results of the Kulldorff's scan found twelve significant space-time clusters of reported TB. The most likely spatio-temporal cluster (RR?=?3.27, P?ConclusionsThis study identified the time and region of TB, SS+ TB and SS- TB clustered easily in 340 prefectures in the mainland of China, which is helpful in prioritizing resource assignment in high-risk periods and high-risk areas, and to formulate powerful strategy to prevention and control TB.

SUBMITTER: Liu MY

PROVIDER: S-EPMC6195697 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015.

Liu Meng-Yang MY Li Qi-Huan QH Zhang Ying-Jie YJ Ma Yuan Y Liu Yue Y Feng Wei W Hou Cheng-Bei CB Amsalu Endawoke E Li Xia X Wang Wei W Li Wei-Min WM Guo Xiu-Hua XH

Infectious diseases of poverty 20181020 1

<h4>Background</h4>Tuberculosis (TB) is still one of the most serious infectious diseases in the mainland of China. So it was urgent for the formulation of more effective measures to prevent and control it.<h4>Methods</h4>The data of reported TB cases in 340 prefectures from the mainland of China were extracted from the China Information System for Disease Control and Prevention (CISDCP) during January 2005 to December 2015. The Kulldorff's retrospective space-time scan statistics was used to id ...[more]

PMID: 30340513

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Project description:Coronavirus disease 2019 (COVID-19) has become a worldwide public health threat. Many associated factors including population movement, meteorological parameters, air quality and socioeconomic conditions can affect COVID-19 transmission. However, no study has combined these various factors in a comprehensive analysis. We collected data on COVID-19 cases and the factors of interest in 340 prefectures of mainland China from 1 December 2019 to 30 April 2020. Moran's I statistic, Getis-Ord Gi⁎ statistic and Kulldorff's space-time scan statistics were used to identify spatial clusters of COVID-19, and the geographically weighted regression (GWR) model was applied to investigate the effects of the associated factors on COVID-19 incidence. A total of 67,449 laboratory-confirmed cases were reported during the study period. Wuhan city as well as its surrounding areas were the cluster areas, and January 25 to February 21, 2020, was the clustering time of COVID-19. The population outflow from Wuhan played a significant role in COVID-19 transmission, with the local coefficients varying from 14.87 to 15.02 in the 340 prefectures. Among the meteorological parameters, relative humidity and precipitation were positively associated with COVID-19 incidence, while the average wind speed showed a negative correlation, but the relationship of average temperature with COVID-19 incidence inconsistent between northern and southern China. NO2 was positively associated, and O3 was negatively associated, with COVID-19 incidence. Environment with high levels of inbound migration or travel, poor ventilation, high humidity or heavy rainfall, low temperature, and high air pollution may be favorable for the growth, reproduction and spread of SARS-CoV-2. Therefore, applying appropriate lockdown measures and travel restrictions, strengthening the ventilation of living and working environments, controlling air pollution and making sufficient preparations for a possible second wave in the relatively cold autumn and winter months may be helpful for the control and prevention of COVID-19. Graphical abstract Unlabelled Image

Project description:BackgroundTuberculosis (TB) makes a big challenge to public health, especially in high TB burden counties of China and Greater Mekong Subregion (GMS). The aim of this study was to identify the spatial-temporal dynamic process and high-risk region of notified pulmonary tuberculosis (PTB), sputum smear-positive tuberculosis (SSP-TB) and sputum smear-negative tuberculosis (SSN-TB) cases in Yunnan, the south-western of China between years of 2005 to 2018. Meanwhile, to evaluate the similarity of prevalence pattern for TB among GMS.MethodsData for notified PTB were extracted from the China Information System for Disease Control and Prevention (CISDCP) correspond to population information in 129 counties of Yunnan between 2005 to 2018. Seasonally adjusted time series defined the trend cycle and seasonality of PTB prevalence. Kulldorff's space-time scan statistics was applied to identify temporal, spatial and spatial-temporal PTB prevalence clusters at county-level of Yunnan. Pearson correlation coefficient and hierarchical clustering were applied to define the similarity of TB prevalence among borders with GMS.ResultThere were a total of 381,855 notified PTB cases in Yunnan, and the average prevalence was 59.1 per 100,000 population between 2005 to 2018. A declined long-term trend with seasonality of a peak in spring and a trough in winter for PTB was observed. Spatial-temporal scan statistics detected the significant clusters of PTB prevalence, the most likely cluster concentrated in the northeastern angle of Yunnan between 2011 to 2015 (RR?=?2.6, P?<?0.01), though the most recent cluster for PTB and spatial cluster for SSP-TB was in borders with GMS. There were six potential TB prevalence patterns among GMS.ConclusionThis study detected aggregated time interval and regions for PTB, SSP-TB, and SSN-TB at county-level of Yunnan province. Similarity prevalence pattern was found in borders and GMS. The localized prevention strategy should focus on cross-boundary transmission and SSN-TB control.

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Project description:BackgroundWe used data released by the government to analyze the epidemiological distribution of pulmonary tuberculosis in mainland China from 2004 to 2015, in order to provide a deeper understanding of trends in the epidemiology of pulmonary tuberculosis in China and a theoretical basis to assess the effectiveness of government interventions and develop more targeted prevention and control strategies.MethodsA discrete dynamic model was designed based on the epidemiological characteristics of pulmonary tuberculosis and fitted to data published by the government to estimate changes in indicators such as adequate contact rate, prevalence of non-treated pulmonary tuberculosis (abbreviated as prevalence), and infection rate. Finally, we performed sensitivity analyses of the effects of parameters on the population infection rate.ResultsThe epidemiological features of pulmonary tuberculosis in China include a pattern of seasonal fluctuations, with the highest rates of infection in autumn and winter. The adequate contact rate has increased slightly from an average of 0.12/month in 2010 to an average of 0.21/month in 2015. The prevalence in the population has continued to decrease from 3.4% in early 2004 to 1.7% in late 2015. The Mycobacterium tuberculosis (M. tuberculosis) infection rate in the population decreased gradually from 42.3% at the beginning of 2004 to 36.7% at the end of 2015. The actual number of new infections gradually decreased from 1,300,000/year in 2010 to 1,100,000/year in 2015. The actual number of new patients each year has been relatively stable since 2010 and remains at approximately 2,600,000/year.ConclusionsThe population prevalence and the M. tuberculosis infection rate have decreased year by year since 2004, indicating that the tuberculosis epidemic in China has been effectively controlled. However, pulmonary tuberculosis has become increasingly contagious since 2010. China should focus on the prevention and control of pulmonary tuberculosis during autumn and winter.

Dataset Information

Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015.

Background

Methods

Results

Publications

Spatial and temporal clustering analysis of tuberculosis in the mainland of China at the prefecture level, 2005-2015.

Similar Datasets

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