Bacillary dysentery remains a public health concern in the world. Hunan Province is one of the provinces having the highest risk of bacillary dysentery in China, however, the spatial-temporal distribution, variation of bacillary dysentery and sensitivity to meteorological factors in there are unclear. In this paper, a Bayesian space-time hierarchical model (BSTHM) was used to detect space-time variation, and effects of meteorological factors between 2010 and 2015. The risk of bacillary dysentery showed apparent spatial-temporal heterogeneity. The highest risk occurred in the summer season. Economically undeveloped mountainous areas in the west and south of the province had the highest incidence rates. Twenty three (18.9%) and 20 (16.4%) counties were identified as hot and cold spots, respectively. Among the hotspots, 11 counties (47.8%) exhibited a rapidly decreasing trend, suggesting they may become low-risk areas in the future. Of the cold spot counties, six (30%) showed a slowly decreasing trend, and may have a higher risk in the future. Among meteorological factors, air temperature, relative humidity, and wind speed all played a significant role in the spatial-temporal distribution of bacillary dysentery risk. These findings can contribute to the implementation of an early warning system for controlling and preventing bacillary dysentery.