关键词: 自然疫源性疾病, 信息熵, 空间分布, 影响因素, 自然因素, 空间自相关, 中国

Abstract:

To date, there have been 43 types of natural focus diseases reported in China, 14 of which are officially-recognized infectious diseases including plague, human-avian influenza, malaria, and dengue fever. Most natural focus diseases are characterized by strong pathogenicity, serious clinical behavior, high mortality rate, and high incidence rate. In 2008, the fever with thrombocytopenia syndrome emerged in China, and dengue fever broke out in Guangdong province in 2014. Natural focus diseases are great threats to Chinese, epsically in the context that there is currently no comprehensive method for acquiring the distribution characteristics of multiple diseases. The equilibrium degree in a region reflects the structure of the diseases in that region, and the distribution of the degree can help understand the distribution of multiple diseases. The paper used the quantity information of 14 natural focus diseases in China from 2004 to 2015, and applied Shannon information entropy theory to explore the spatial distribution pattern of the equilibrium degree of multiple natural focus diseases. Spatial autocorrelation analysis was adopted to detect the high incidence areas and low incidence areas. Finally, based on Pearson correlation coefficient analysis, the correlations among elevation, temperature, precipitation, NDVI, population, density of population, GDP, and information entropy were quantified. Results show that: (1) Anhui Province and Inner Mongolia Autonomous Region had the highest number of natural focus diseases. The information entropy of natural focus diseases in mainland China showed obvious northwest-southeast differentiation characteristics. The high-value aggregation areas and low-value aggregation areas were mainly distributed on the two sides of the boundary line of the mountains from Hebei Province to Yunnan Province. (2) Compared with social factors, natural factors were the main factors affecting the equilibrium degree of natural focus diseases. It was more prone to a variety of diseases in warm and humid areas with appropriate temperatures and adequate moisture. Single disease was more likely to occur in specific livestock or specific mosquitoes areas. (3) Areas with a high total number of cases usually resulted from a large number of cases of one disease, and these areas were less equilibrated, while areas with high information entropy usually resulted from many concentrated outbreaks of diseases. Our findings help understand the distribution characteristics of natural focus diseases in China, and demonstrate the potential of applying information entropy to analyze the prevention and control measures of natural focus diseases.

Key words: Natural focus disease, information entropy, spatial distribution, impact factors, natural factor, spatial autocorrelation analysis, China