| African swine fever(ASF)is an acute and severe infectious disease caused by the African swine fever virus(ASFV),which can infect domestic pigs and wild boars.African swine fever has a very high fatality rate,and it spreads quickly and widely,which makes it difficult to prevent and control.In addition,the African swine fever virus encodes many proteins related to immune escape and interferes with a variety of cell signaling pathways related to immune regulation,which makes the development of effective vaccines extremely challenging.There is no effective treatment for African swine fever,the development of vaccines has made phased progress,but there is currently no commercial vaccine used to control African swine fever.From the perspective of epidemic history,the regions affected by African swine fever include more than 55 countries in Africa,Europe,and Asia,resulting in more than 77% of pigs in the world being threatened.In the affected areas,African swine fever has caused huge economic loss to the pig industry and has a profound impact on international trade.In 2018,the first African swine fever epidemic occurred in China.A large number of live pigs were culled to prevent the spread of the epidemic,but the spread could not be stopped.With the continuous outbreak of African swine fever worldwide,the molecular biology research of the African swine fever virus and the understanding of the epidemiological characteristics of African swine fever has been deepening.This will be beneficial to the development of African swine fever vaccine and treatment methods and the formulation of African swine fever prevention and control strategies,with a view to reducing the impact of African swine fever on breeding industry and pork prices.The spread speed of African swine fever depends on the host,virus,and external conditions,many of which are not fully understood.According to the survey and statistics of 68 cases of African swine fever in China,46% were caused by contaminated vehicles and workers,34% were caused by swill feeding,and 19% were caused by the transportation of pigs and products.Generally speaking,socio-economic factors,trade and transport factors,climate and environmental factors,and host density will affect the spread of African swine fever.Understanding the temporal and spatial epidemiological characteristics and risk factors of African swine fever is the focus of prevention and control measures.The main content of this research is to collect data on the African swine fever in mainland China between August 1,2018 and December 31,2020 reported by the Ministry of Agriculture and Rural Affairs of the People's Republic of China,including information on the location,time,and the number of cases of African swine fever.Collect the trade,climate,environmental,pig density,population density,highway and railway data of mainland China and other potential risk factors affecting the occurrence of African swine fever.Use global spatial autocorrelation analysis,local spatial autocorrelation analysis,and directional distribution analysis to explore the spatial distribution characteristics of African swine fever in mainland China.Use Spatio-temporal cluster analysis and direction test to explore the characteristics of the Spatio-temporal pattern of African swine fever in mainland China.Based on the epidemic data of African swine fever in mainland China and various risk factors data,a structural equation model and a MaxEnt model were constructed to analyze the risk factors and risk areas of African swine fever.Establish an African swine fever biological vector monitoring and early warning system,strengthen the collection and use of African swine fever biological vector data.The combined use of biological vector data and disease data will help improve animal disease-related information.Specific research contents include:(1)Based on the incidence of African swine fever in various provinces in mainland China from2018 to 2020,use global spatial autocorrelation and local spatial autocorrelation to explore the distribution patterns of African swine fever during the study period.The global spatial autocorrelation results showed that the African swine fever in mainland China presents a centralized distribution pattern in 2018 and a random pattern in 2019 and 2020.The results of local spatial autocorrelation analysis showed that the hot spots of African swine fever in mainland China in 2018 are Heilongjiang,Jilin,and Liaoning,and the cold spots are Hunan,Guizhou,Guangxi,and Chongqing;in 2019,the hot spots of African swine fever in mainland China are Xinjiang,Tibet,and Qinghai;in 2020,the hot spots of African swine fever in mainland China are Qinghai and Gansu.(2)Based on the geographic location of all epidemics of African swine fever in mainland China from 2018 to 2020 and the geographic location of the first case in each province,use directional distribution analysis and direction test to explore the distribution and transmission direction of African swine fever in mainland China during the study period.The results showed that the distribution of African swine fever in mainland China between 2018 and 2020 has obvious direction,showing a northeast-southwest direction;during the study period,African swine fever spread directionally from northeast to southwest.(3)Based on the onset time,the number of cases,latitude and longitude information of African swine fever in mainland China from 2018 to 2020,the Spatio-temporal cluster analysis is used to detect the temporal and spatial clusters of African swine fever in mainland China.The results showed that there are nine Spatio-temporal clusters of African swine fever in mainland China.The top three clusters are located in the northwest and southwest of mainland China.The center of the first-level Spatio-temporal clusters is in Gansu,the second and third-level Spatio-temporal clusters are located in Yunnan.(4)Based on the incidence of African swine fever in various provinces in mainland China from established to analyze the impact of trade and transport factors on the occurrence of African swine fever.The results showed that the occurrence of African swine fever in mainland China was positively correlated with pork transportation demand.The important transport risk factors affecting the occurrence of African swine fever are railway density and highway density.(5)Based on the geographical location of African swine fever epidemic and climate and environmental risk factor data in mainland China from 2018 to 2020,a MaxEnt model is constructed to explore the relationship between the climate and environmental factors and the occurrence of African swine fever and predict the high-risk areas of occurrence.The model results showed that the first three risk factors that have an important impact on the occurrence of African swine fever are population density,NDVI,and temperature annual range,and the high-risk areas of African swine fever occurrence in mainland China are mainly in North China,East China,the Central of China and Southern China.(6)The African swine fever biological vector monitoring and early warning system is based on WebGIS,B/S architecture,use Java Script and a variety of management software to build the system.According to the system requirements and objectives,the structure is designed,and a database is established to associate various data,to realize many functions including map operation,data management of pig breeding related units,data management,monitoring and early warning of African swine fever transmission vectors and epidemic situation,and assist in formulating prevention and control measures.In summary,this study analyzed the temporal and spatial distribution characteristics of African swine fever in mainland China from 2018 to 2020 and learned about the distribution pattern,distribution and transmission direction,temporal and spatial accumulation areas of African swine fever.The study on the temporal and spatial distribution characteristics of African swine fever is helpful to grasp the epidemic trend of African swine fever and provide reference materials for the formulation of prevention and control measures.The structural equation model and MaxEnt model were established to analyze the relationship between the occurrence of African swine fever and trade,transport,climate,and environmental risk factors,and predict the risk area of African swine fever in mainland China.This study results help to explore the etiology of African swine fever and assist managers in making effective decisions to stop the spread of African swine fever and control the outbreak.The African swine fever biological vectors monitoring and early warning system was established,to realize real-time monitoring,analysis,and early warning of African swine fever biological vectors and diseases,assist managers in monitoring and management,rationally allocate resources,and accurately prevent and control the epidemic. |
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