| Summary: | Abstract 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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