Spatiotemporal analysis of tuberculosis incidence and its associated factors in mainland China

Guo, Cui; Du, Yue; Shen, Si; Lao, Xiang Qian; Qian, Jun; Ou, Chun Quan

doi:10.1017/s0950268817001133

Cited by 61 publications

(61 citation statements)

References 51 publications

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“…Per capita GDP and education level were found to be statistically significant in the models 1, 2 and 3, indicating that economic development, and improved awareness of TB could help to alleviate the SS + PTB epidemic. Our results are consistent with other studies [15,39,40]. Evidence indicates that TB is a poverty-related disease, with an average treatment period of 6 months [41].…”

Section: Discussionsupporting

confidence: 93%

“…Spatial and spatiotemporal analysis of TB notification cases could provide crucial epidemiological information to guide interventions. In recent years, the geographical information system (GIS) and spatial statistics were used to detect the spatial characteristics of TB in China [14][15][16][17][18]. Several studies have demonstrated that TB is not randomly distributed.…”

Section: Introductionmentioning

confidence: 99%

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The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis

Liao

Gao

et al. 2020

Infect Dis Poverty

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Background: Internal migration places individuals at high risk of contracting tuberculosis (TB). However, there is a scarcity of national-level spatial analyses regarding the association between TB and internal migration in China. In our research, we aimed to explore the spatial variation in cases of sputum smear-positive pulmonary TB (SS + PTB) in China; and the associations between SS + PTB, internal migration, socioeconomic factors, and demographic factors in the country between 2005 and 2015. Methods: Reported cases of SS + PTB were obtained from the national PTB surveillance system database; cases were obtained at the provincial level. Internal migration data were extracted from the national population sampling survey and the census. Spatial autocorrelations were explored using the global Moran's statistic and local indicators of spatial association. The spatial temporal analysis was performed using Kulldorff's scan statistic. Fixed effects regression was used to explore the association between SS + PTB and internal migration. Results: A total of 4 708 563 SS + PTB cases were reported in China between 2005 and 2015, of which 3 376 011 (71.7%) were male and 1 332 552 (28.3%) were female. There was a trend towards decreasing rates of SS + PTB notifications between 2005 and 2015. The result of global spatial autocorrelation indicated that there were significant spatial correlations between SS + PTB rate and internal migration each year (2005-2015). Spatial clustering of SS + PTB cases was mainly located in central and southern China and overlapped with the clusters of emigration. The proportions of emigrants and immigrants were significantly associated with SS + PTB. Per capita GDP and education level were negatively associated with SS + PTB. The internal migration flow maps indicated that migrants preferred neighboring provinces, with most migrating for work or business. Conclusions: This study found a significant spatial autocorrelation between SS + PTB and internal migration. Both emigration and immigration were statistically associated with SS + PTB, and the association with emigration was stronger than that for immigration. Further, we found that SS + PTB clusters overlapped with emigration clusters, and the internal migration flow maps suggested that migrants from SS + PTB clusters may influence the TB epidemic characteristics of neighboring provinces. These findings can help stakeholders to implement effective PTB control strategies for areas at high risk of PTB and those with high rates of internal migrants.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis

Liao

Gao

et al. 2020

Infect Dis Poverty

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“…The radius at the bottom of cylinder represents geographic position and size of cluster area. The height of cylinder denotes time of outbreaks (28). As the constant changes of radius and time, spatial window is in dynamic changing, and counting the number of positive and/or negative events occurring (29).…”

Section: Spatio-temporal Cluster Analysismentioning

confidence: 99%

Retrospect and Risk Analysis of Foot-and-Mouth Disease in China Based on Integrated Surveillance and Spatial Analysis Tools

et al. 2020

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Foot-and-mouth disease (FMD) is a highly contagious disease of livestock and seriously affects the development of animal husbandry. It is necessary to defend the spread of FMD. To explore the distribution characteristics and transmission of FMD between 2010 and 2017 in China, Global Moran's I test and Getis-Ord Gi index were used to analyze the spatial cluster. A space-time permutation scan statistic was applied to analyze the spatio-temporal pattern. GIS-based method was employed to create a map representing the distribution pattern, directional trend, and hotspots for each outbreak. The number of cases was defined as the number of animals with FMD for the above analysis. We also constructed a phylogenetic tree to compare the homology and variation of FMD virus (FMDV) to provide a clue for the potential development of an effective vaccine. The results indicated that the FMD outbreaks in China had obvious time patterns and clusters in space and space-time, with the outbreaks concentrated in the first half of each year. The outbreaks of FMD decreased each year from 2010 with an obvious downward trend of hotspots. Spatial analysis revealed that the distribution of FMD outbreaks in 2010, 2015, and 2017 exhibited a clustered pattern. Space-time scanning revealed that the spatio-temporal clusters were centered in Guangdong, Tibet and the junction of Wuhan, Jiangxi, Anhui. Comparison of the spatial analysis and space-time analysis of FMD outbreaks revealed that Guangdong was the same cluster of the two in 2010. In addition, the directional trend analysis indicated that the FMD transmission was oriented northwest-southeast. The findings demonstrated that FMDV in China can be divided into three pedigrees and the homology of these strains is very high while comparing the first FMDV strain with the others. The data provide a basis for the effective monitoring and prevention of FMD, and for the development of an FMD vaccine in China.

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“…The epidemiological mechanism interacting with socioeconomic factors at different spatial locations determines the variability of the geographical distribution of a disease [17]. The disparities of TB incidence were in uenced by geospatial factors, population and socioeconomic heterogeneity, which will further affect the migrant population [18][19][20][21][22]. However, there is still no systematic analysis of how TB population size and socioeconomic heterogeneity affect tuberculosis transmission between the provinces in China.…”

Section: Introductionmentioning

confidence: 99%

Modeling tuberculosis transmission flow in China

Wang¹,

Xu²,

Hu³

et al. 2020

Preprint

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Background: China has the largest population and third largest number of tuberculosis cases in the world. Tuberculosis still remains a major public health concern in China. The increasing floating population has become an important part of China’s socioeconomic process and brought the potential risk for infectious disease transmission in the huge population. Both the flow of tuberculosis population in the country and the role of massive floating population in tuberculosis transmission are yet unclear.Methods: 14,027 tuberculosis flow data were derived from the new smear-positive pulmonary tuberculosis cases in China in 2012, provided by the nationwide Infectious Disease Reporting System. Spatial interaction model was used to model the tuberculosis flow and the regional socioeconomic factors.Results: The Pearl River Delta in southern China and the Yangtze River Delta along China’s east coast presented as the largest destination and concentration areas of tuberculosis inflows. Socioeconomic factors were determinants of tuberculosis flow. A 10% increase in per capita GDP was associated with 2.1% decrease in tuberculosis outflows from the provinces of origin, and 0.5% increase in tuberculosis inflows to the destinations and 18.9% increase in intraprovincial flow. Per capita net income of rural households and per capita disposable income of urban households were positively associated with tuberculosis flows. A 10% increase in per capita net income corresponded to 3.6% increase in outflows from the origin, 12.8% increase in inflows to the destinations and 47.9% increase in intraprovincial flows. Tuberculosis incidence had positive impacts on tuberculosis flows. A 10% increase in the number of tuberculosis cases corresponded to 1.1% increase in tuberculosis inflows to the destinations, 2.0% increase in outflows from the origins, and 2.2% increase in intraprovincial flows. A 10% increase in the tuberculosis incidence rate was associated with 9.9% increase in tuberculosis intraprovincial flows. In addition, the tuberculosis flow had a significant spatial dependence and positively affected tuberculosis flows in the neighboring regions.Conclusions: Tuberculosis flows had clear spatial stratified heterogeneity and spatial autocorrelation; regional socio-economic characteristics had different and statistically significant effects on tuberculosis flows in the origin and destination, and income factor played an important role among the determinants.

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Spatiotemporal analysis of tuberculosis incidence and its associated factors in mainland China

Cited by 61 publications

References 51 publications

The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis

The association between internal migration and pulmonary tuberculosis in China, 2005–2015: a spatial analysis

Retrospect and Risk Analysis of Foot-and-Mouth Disease in China Based on Integrated Surveillance and Spatial Analysis Tools

Modeling tuberculosis transmission flow in China

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