Abstract:Objective To establish an appropriate quantitative model to evaluate the relationship between bacillary dysentery and floods in Liuzhou, China. Methods On the basis of time series analysis to control longterm trends, seasonal trends, lagged effect and meteorological factors, the seasonal autoregressive moving average (SARIMA) model was conducted to examine the relationship between bacillary dysentery and monthly flood days. Results This study showed that the morbidity of bacillary dysentery in the flood period was different to those in the control period. Multivariable SARIMA models showed that monthly flood days were negatively correlated to the monthly attack rate of bacillary dysentery. Conclusions The findings suggest that floods could have affected the transmission of bacillary dysentery. In addition, severe floods with a shorter duration may cause a higher risk of bacillary dysentery than the prolonged moderate floods.