Surveillance And Early Warning System Of Sheep Coccidiosis In Mainland China

Coccidiosis(coccidiasis of sheep)is a protodisease,mainly caused by the coccidioides.Sheep and goats of different breeds and ages have susceptibility to coccidia.Direct contact between sick and healthy sheep may lead to the spread of the pathogen,which pollutes the environment when the eggs are excreted from the feces,and may be infected because contaminated drinking water or food is fed to healthy sheep.Sheep of different ages can be infected with coccidiosis,but 1～3 months of lamb is more likely to influence and catch the disease,when the lamb in the herd spread rapidly,incidence can reach 100%,the lamb a development of various tissues and organs are not complete,immunity and low disease resistance,when general treatment,case fatality rate can reach 60%.Such parasitic diseases have caused great economic losses to the sheep farming industry and pose a great threat to public health.Therefore,it is of great practical significance to understand the epidemic characteristics of FCC in China in recent years and to explore its occurrence and transmission risks in China.In this study,we collected the epidemic data and climate and environmental data.We used geographic information technology and spatiotemporal analysis technology combined with temporal and spatial dimensions to explore the distribution characteristics and transmission trend of cocciococcus in China,and visualized the results.At the same time,the maximum entropy(MaxEnt)model and the risk of occurrence and transmission,to reveal the main factors affecting the occurrence and spread of the disease,and finally,the network geographic information technology(Web GIS)technology and Arc GIS Sever extension development software according to the Web GIS.Main research contents include:(1)The spatial autocorrelation method was applied to explain the spatial distribution of inococcus disease.Based on global spatial and local spatial autocorrelation analysis revealed the spatial distribution pattern of the outbreaks in China.The results of global spatial autocorrelation show that when each administrative region in China as a whole,coccidiosis presents a clustered distribution pattern.During the local autocorrelation analysis of each administrative region,it was found that Sichuan Province,Ningxia Hui Autonomous Region and Shanxi Province showed high and high clustering,while the southeast coastal areas showed high and low clustering,and the other regions showed no significant clustering.(2)Use direction analysis and spatiotemporal aggregation analysis to analyze the transmission direction and the spatial and temporal distribution of sheep coccal disease.Based on direction analysis and spatiotemporal aggregation analysis,we explore the trend of transmission direction and development in time and space of the outbreak in China.The results of spatiotemporal clustering analysis show that there are eight statistically significant spatiotemporal clustering areas of coccidian outbreaks in China.Level area in Qinghai Hainan Tibetan autonomous prefecture,secondary clusters in Taizhou,tertiary clusters in Kunming,Yunnan province,level 4 clusters in Inner Mongolia autonomous region bayinnaoer city,five clusters in Nanyang,Fujian province,six clusters in Dingxi city,Gansu province,seven clusters area in Xinjiang Changji hui autonomous region,eight clusters in Zhangjiajie in Hunan province.(3)Construct a MaxEnt model to analyze the risk factors of coccidiosis.Based on the MaxEnt model,the risk factors affecting the prevalence of coccicoccal transmission in China and exploring the high risk areas of epidemic distribution were analyzed.The combined contribution rate of various variables in the MaxEnt model and the test results of Jackknife method show that the coldest monthly precipitation(bio＿19),normalized differential vegetation index(ndvi)and the highest temperature of the warmest month(bio＿5)are important environmental factors affecting the distribution of cocciosis.MaxEnt The niche model combines the distribution of susceptible animals for coccidiosis in China.The high risk areas of coccidiosis are mainly located in Gansu province,Ningxia Hui Autonomous Region,Shaanxi Province,Yunnan Province,central Xinjiang Uygur Autonomous Region and southeastern Tibet.(4)Based on Web GIS technology,complete the design and development of ococcal disease monitoring and early warning systemUsing Arc GIS secondary development and network geographic information(Web GIS)technology,and the results of the risk analysis model in the paper,the monitoring and early warning system was designed.Finally,the system correlated disease attribute data and geospatial data,and information management and mathematical model prediction functions,so as to realize the emergency reporting of coccidia data information,and the performance of spatiotemporal monitoring,risk identification and predictive analysis.This study provides scientific reference for the surveillance and control of sheep coccidiasis in China.