A descriptive analysis of the Spatio-temporal distribution of intestinal infectious diseases in China

Mao, Ying; Zhang, Ning; Zhu, Bin; Liu, Jinlin; He, Rongxin

where n denotes the number of observed values, x i represents the incidence rate in province I, x j represents the incidence rate in province j, x indicates the mean value, and w ij represents a spatial weight matrix of systematic binomial distribution, which represents neighbouring relations between geographical units with n representing the total number of those units . In the present study, the data were based on regions. The value for w ij is 1 if province i and province j are adjacent. Otherwise, the value is 0. Local Moran's I avoids the weaknesses of global spatial autocorrelation by analysing the spatial autocorrelation of certain characters in local regions. The range and explanation for the local Moran's I was same as the global index. The cluster results obtained from local Moran's I were classified into four types: high-high cluster (HH, which indicated that the high cluster areas were surrounded by other high cluster areas), high-low cluster (HL, which indicated that the high cluster areas were surrounded by low cluster areas), low-high cluster (LH), and low-low (LL) cluster. The clusters were visualized using LISA cluster maps. The following equation was used to calculate local Moran's I: