{"title":"A reliable numerical simulation technique for solving COVID-19 model","authors":"Mahdi A. Sabea, M. A. Mohammed","doi":"10.28919/cmbn/7959","DOIUrl":null,"url":null,"abstract":". The nature of epidemiological models is characterized by randomness in their coefficients, while the classical or analytical and numerical methods deal with systems with fixed coefficients, which makes these methods inappropriate for solutions of epidemiological systems that have coefficients that change with time. For that, the numerical simulation methods that deal with time change are more appropriate than other ways. The aim of the research is to apply some of these methods to the COVID-19 system. Two efficient methods used for previous studies are used to solve this system, which are Monte Carlo Finite Difference Method and Mean Latin Hypercube Finite Difference Method. For the sake of comparison, a numerical method, the finite difference method, is used to solve this system. We have reached good results that give an analysis and impression of the behavior of the Covid 19 epidemic since its inception and predict its behavior for the next years. All results have been written in graphs and tabulated.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Mathematical Biology and Neuroscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28919/cmbn/7959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
. The nature of epidemiological models is characterized by randomness in their coefficients, while the classical or analytical and numerical methods deal with systems with fixed coefficients, which makes these methods inappropriate for solutions of epidemiological systems that have coefficients that change with time. For that, the numerical simulation methods that deal with time change are more appropriate than other ways. The aim of the research is to apply some of these methods to the COVID-19 system. Two efficient methods used for previous studies are used to solve this system, which are Monte Carlo Finite Difference Method and Mean Latin Hypercube Finite Difference Method. For the sake of comparison, a numerical method, the finite difference method, is used to solve this system. We have reached good results that give an analysis and impression of the behavior of the Covid 19 epidemic since its inception and predict its behavior for the next years. All results have been written in graphs and tabulated.
期刊介绍:
Communications in Mathematical Biology and Neuroscience (CMBN) is a peer-reviewed open access international journal, which is aimed to provide a publication forum for important research in all aspects of mathematical biology and neuroscience. This journal will accept high quality articles containing original research results and survey articles of exceptional merit.