{"title":"埃博拉疾病控制模型及药品物流路径优化算法","authors":"S. Yan","doi":"10.1109/BMEI.2015.7401617","DOIUrl":null,"url":null,"abstract":"Ebola is threatening us heavily nowadays, especially in Africa, which means that eradicating Ebola is a tremendous challenge to be faced. It is vital to ensure adequate quantities of Ebola treatment drugs supply to meet the timely and effective elimination of the Ebola epidemic. Ebola treating drug manufacturing and logistics transportation are particularly important and indispensable processes for preventing Ebola's spread. The paper established the control model of Ebola disease and completed the combination of the treatment drug delivery path optimal algorithm. The improved Mathematical Model structure of virus prevalence based on SEIQR is successfully built to eradicate Ebola spread. By Case simulation of Mathematical Model of probability statistics is used to predict the spread of the disease and support the selection of the most efficient transportation path. The improved optimization algorithm of pharmaceutical logistics path based on classical Dijkstra's algorithm is put forward and developed, which finds the fastest and most efficient path recursively by comparing medicine transportation time among transit points. Through the path analysis, we can also know the best locations of medicine delivery. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for the Health Control Organization to prevent the spread of the Ebola virus.","PeriodicalId":119361,"journal":{"name":"2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"The model of Ebola disease control and optimization algorithm of pharmaceutical logistics path\",\"authors\":\"S. Yan\",\"doi\":\"10.1109/BMEI.2015.7401617\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ebola is threatening us heavily nowadays, especially in Africa, which means that eradicating Ebola is a tremendous challenge to be faced. It is vital to ensure adequate quantities of Ebola treatment drugs supply to meet the timely and effective elimination of the Ebola epidemic. Ebola treating drug manufacturing and logistics transportation are particularly important and indispensable processes for preventing Ebola's spread. The paper established the control model of Ebola disease and completed the combination of the treatment drug delivery path optimal algorithm. The improved Mathematical Model structure of virus prevalence based on SEIQR is successfully built to eradicate Ebola spread. By Case simulation of Mathematical Model of probability statistics is used to predict the spread of the disease and support the selection of the most efficient transportation path. The improved optimization algorithm of pharmaceutical logistics path based on classical Dijkstra's algorithm is put forward and developed, which finds the fastest and most efficient path recursively by comparing medicine transportation time among transit points. Through the path analysis, we can also know the best locations of medicine delivery. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for the Health Control Organization to prevent the spread of the Ebola virus.\",\"PeriodicalId\":119361,\"journal\":{\"name\":\"2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2015.7401617\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 8th International Conference on Biomedical Engineering and Informatics (BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2015.7401617","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The model of Ebola disease control and optimization algorithm of pharmaceutical logistics path
Ebola is threatening us heavily nowadays, especially in Africa, which means that eradicating Ebola is a tremendous challenge to be faced. It is vital to ensure adequate quantities of Ebola treatment drugs supply to meet the timely and effective elimination of the Ebola epidemic. Ebola treating drug manufacturing and logistics transportation are particularly important and indispensable processes for preventing Ebola's spread. The paper established the control model of Ebola disease and completed the combination of the treatment drug delivery path optimal algorithm. The improved Mathematical Model structure of virus prevalence based on SEIQR is successfully built to eradicate Ebola spread. By Case simulation of Mathematical Model of probability statistics is used to predict the spread of the disease and support the selection of the most efficient transportation path. The improved optimization algorithm of pharmaceutical logistics path based on classical Dijkstra's algorithm is put forward and developed, which finds the fastest and most efficient path recursively by comparing medicine transportation time among transit points. Through the path analysis, we can also know the best locations of medicine delivery. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for the Health Control Organization to prevent the spread of the Ebola virus.