The prevalence and distribution of infectious diseases and occupational diseases in specific time and space is the result of the interaction between natural environment, social economy and other factors, its distribution pattern has spatial properties. Based on the assumption of independence, the traditional statistical methods ignore the spatial attributes of diseases and cannot analyze the spatial characteristics of diseases. On the basis of geographic information system, the spatial autocorrelation analysis can simultaneously analyze the spatial relationship and attribute value of diseases, explore the spatial dependence of disease data in different spatial units, and provide decision-making basis for the prediction and early warning of diseases such as occupational and infectious diseases, and the formulation and evaluation of prevention and control measures.
传染病及职业病在特定时空内的流行与分布是自然环境与社会经济等多重因素相互作用的结果，其分布格局具有空间属性。传统统计学方法以独立性假设为前提，忽略了疾病的空间属性，无法分析疾病的空间特征。空间自相关方法以地理信息系统为依托，能够同时对疾病的空间关系及属性值进行分析，探讨不同空间单元疾病数据间的空间依赖性，为传染病、职业病等疾病预测预警、防控措施的制定与评价等方面提供决策依据。.
Keywords: Chronic disease; Communicable diseases; Occupational diseases; Public health; Spatial autocorrelation analysis; Spatial weight matrices.