A Mathematical Model for Ebola Control
Abstract: This paper aims to analyze the cases of Ebola in West Africa, forecast the future trend of the spread of the virus, and provide some consulting opinions for related departments to make decisions. Firstly, we construct the SIR-L model for Ebola epidemics based on the classical infectious diseases SIR model and the Logistic model to simulate and predict the spread trends of the virus. We get that the Ebola has crossed the peak period in the three main countries, but the cases of the Ebola are still at a high level. Then we forecast the new cases in the next week: 88, 28 and 238 cases for Guinea, Liberia, and Sierra Leone, respectively. Secondly, by analyzing the data that we forecast, combing with the population size and geographical location of each country, a dynamical model is established based on gravity center method and gray theory, which are utilized to select the optimal distribution center. It reveals that River Cess, Bo, Mamou are the optimal distribution centers of Liberia, Sierra Leone, and Guinea, respectively. Sierra Leone, the hardest-hit area, is se-lected as the production country, and Bo is selected as the production center. Finally, based on the optimal distribution center and production center, we develop the distribution model of emergency supplies in three layers, which refers to some of advanced sophisticated logistics systems and operational experiences of modern enterprise logistics systems. That is to say, the production center is considered as the first layer of the network; the distribution center of the three countries is the second layer; and the town center of each country’s county is the third layer. We design a distribution network system based on the principle that the delivery time of the Ebola is the shortest in the beginning, and the cost of the rescue system is the lowest in the later period.
文章引用: 杨号鑫 , 王嘉辉 , 唐鑫桂 (2015) 埃博拉疫情控制模型。 统计学与应用， 4， 70-85. doi: 10.12677/SA.2015.42009
 WHO (2015) 2014 Ebola outbreak in West Africa—Case counts. http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/case-counts.html
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