Objective To detect the spatial clustering and high risk areas of pulmonary tuberculosis (PTB) in Sichuan province in 2018 and,to compare the effects of application on both SaTScan 9.4.1 software and FleXScan 3.1.2 software to detect the PTB spatial clusters.Methods Geographic information database was established by using the incidence data of PTB and demographic data reported in the'China disease prevention of infectious disease reporting information management system'in Sichuan province in 2018.Spatial clustering analysis was conducted using the Poisson model in software SaTScan 9.4.1 and FleXScan 3.1.2 to detect the high risk areas of PTB by software ArcGIS 10.5.Differences of clusters locations and scopes in the two scanning methods were compared.Results The reported incidence rate of PTB was 57.34/100 000 (47 601 cases) in Sichuan province in 2018,presenting an obvious clustering distribution.SaTScan and FleXScan scanned 8 and 10 clusters showed statistically significant differences (P＜0.05),with log-likelihood ratio (LLR) as 24.62-2 416.05 and 1.48-2 618.96,respectively.Results from scanning of the two methods showed that the most likely clusters appeared in the Daliangshan and Xiaoliangshan of Liangshan Yi ethnic aggregation areas.The other clustering areas would include some minority areas in the western Sichuan plateau,detected by both two methods differences in the shape and scope of the clustering were detected by both methods.The clustering scopes detected by SaTScan covered some counties,in which the actual incidence was not high.FleXScan could distinguish the clusters and detect more irregular shaped clusters.Conclusions Obvious spatial clusters of PTB distribution were found in Sichuan in 2018.Areas of Daliangshan,Xiaoliangshan and the minority areas in Western Sichuan plateau appeared at high risk,suggesting these were the key areas for prevention and control.FleXScan seemed more conducive in accurately distinguishing the "cold spot" areas in the highly aggregated areas,and more suitable for the application of spatial clustering detection for TB,in Sichuan province.