COVID-19疫苗接种期间传播力的数学模型

Pub Date : 2023-03-01 DOI:10.32523/2306-6172-2023-11-1-4-28

F. Aqel, A. Hamza, A. Nour Eddine

{"title":"COVID-19疫苗接种期间传播力的数学模型","authors":"F. Aqel, A. Hamza, A. Nour Eddine","doi":"10.32523/2306-6172-2023-11-1-4-28","DOIUrl":null,"url":null,"abstract":"The aim of this work is to develop a new Reservoir People (RP) transmission mathematical model, to simulate the potential transmission of COVID-19 virus and Delta variant in the Moroccan population during the vaccination period. The originality of this work resides in the fact that the different parameters that appear in the model problem, depend on the period of vaccination. The existence and uniqueness of non-negative normalized solutions are proved. A cost function to minimize with respect to the parameters is defined. To this aim, a novel hybrid algorithm, called Neural Network with Sine-Cosine algorithm (NNSCA) is proposed. The obtained numerical simulation confirms that our model is robust and can efficiently predict the evolution of the virus in Morocco during the vaccination period.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MATHEMATICAL MODEL OF COVID-19 TRANSMISSIBILITY DURING THE VACCINATION PERIOD\",\"authors\":\"F. Aqel, A. Hamza, A. Nour Eddine\",\"doi\":\"10.32523/2306-6172-2023-11-1-4-28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this work is to develop a new Reservoir People (RP) transmission mathematical model, to simulate the potential transmission of COVID-19 virus and Delta variant in the Moroccan population during the vaccination period. The originality of this work resides in the fact that the different parameters that appear in the model problem, depend on the period of vaccination. The existence and uniqueness of non-negative normalized solutions are proved. A cost function to minimize with respect to the parameters is defined. To this aim, a novel hybrid algorithm, called Neural Network with Sine-Cosine algorithm (NNSCA) is proposed. The obtained numerical simulation confirms that our model is robust and can efficiently predict the evolution of the virus in Morocco during the vaccination period.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32523/2306-6172-2023-11-1-4-28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32523/2306-6172-2023-11-1-4-28","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

这项工作的目的是建立一个新的水库人(RP)传播数学模型，以模拟疫苗接种期间摩洛哥人群中COVID-19病毒和德尔塔变体的潜在传播。这项工作的独创性在于，模型问题中出现的不同参数取决于接种疫苗的时间。证明了非负归一化解的存在唯一性。定义了一个相对于参数最小化的代价函数。为此，提出了一种新的混合算法——神经网络与正弦余弦算法(NNSCA)。得到的数值模拟证实，我们的模型是稳健的，可以有效地预测摩洛哥疫苗接种期间病毒的演变。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

MATHEMATICAL MODEL OF COVID-19 TRANSMISSIBILITY DURING THE VACCINATION PERIOD

The aim of this work is to develop a new Reservoir People (RP) transmission mathematical model, to simulate the potential transmission of COVID-19 virus and Delta variant in the Moroccan population during the vaccination period. The originality of this work resides in the fact that the different parameters that appear in the model problem, depend on the period of vaccination. The existence and uniqueness of non-negative normalized solutions are proved. A cost function to minimize with respect to the parameters is defined. To this aim, a novel hybrid algorithm, called Neural Network with Sine-Cosine algorithm (NNSCA) is proposed. The obtained numerical simulation confirms that our model is robust and can efficiently predict the evolution of the virus in Morocco during the vaccination period.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助