{"title":"新型冠状病毒肺炎无症状感染者及再感染影响的数学模型","authors":"Arpita Devi, Asish Adak, Praveen Kumar Gupta","doi":"10.1615/CritRevBiomedEng.2024056294","DOIUrl":null,"url":null,"abstract":"<p><p>In this study, an epidemic model with a constant recruitment rate of susceptible individuals with a bilinear transmission rate of infection is considered. Vaccination-type treatment is inspected to minimize the impact of the disease. The asymptomatic infected and the vaccinated compartments are taken with regard to the circumstances of the coronavirus disease (COVID-19) pandemic 2020-2025. The impact of these two compartments is examined specifically to shed light on the behavioral dynamics. Local as well as the global stability of the disease-free equilibrium point and the endemic equilibrium point are examined by constructing Lyapunov functions. Hence, we prove that if the basic reproduction number is < 1, then there will be no disease in the system, and if the basic reproduction number is > 1, then the disease will persist. Sensitivity analysis is performed to identify the influential model parameters that have the greatest impact on the original reproduction number of the proposed model. The model is validated by fitting it to real data. Furthermore, we carried out numerical simulations of the model parameters and their accompanying theoretical results. To control or eliminate the effect of emerging diseases, we made several suggestions to control the most sensitive model parameters while using necessary preventive measures.</p>","PeriodicalId":94308,"journal":{"name":"Critical reviews in biomedical engineering","volume":"53 4","pages":"77-91"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Mathematical Model Evaluating the Impact of Asymptomatic COVID-19 Cases and Reinfection.\",\"authors\":\"Arpita Devi, Asish Adak, Praveen Kumar Gupta\",\"doi\":\"10.1615/CritRevBiomedEng.2024056294\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this study, an epidemic model with a constant recruitment rate of susceptible individuals with a bilinear transmission rate of infection is considered. Vaccination-type treatment is inspected to minimize the impact of the disease. The asymptomatic infected and the vaccinated compartments are taken with regard to the circumstances of the coronavirus disease (COVID-19) pandemic 2020-2025. The impact of these two compartments is examined specifically to shed light on the behavioral dynamics. Local as well as the global stability of the disease-free equilibrium point and the endemic equilibrium point are examined by constructing Lyapunov functions. Hence, we prove that if the basic reproduction number is < 1, then there will be no disease in the system, and if the basic reproduction number is > 1, then the disease will persist. Sensitivity analysis is performed to identify the influential model parameters that have the greatest impact on the original reproduction number of the proposed model. The model is validated by fitting it to real data. Furthermore, we carried out numerical simulations of the model parameters and their accompanying theoretical results. To control or eliminate the effect of emerging diseases, we made several suggestions to control the most sensitive model parameters while using necessary preventive measures.</p>\",\"PeriodicalId\":94308,\"journal\":{\"name\":\"Critical reviews in biomedical engineering\",\"volume\":\"53 4\",\"pages\":\"77-91\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Critical reviews in biomedical engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1615/CritRevBiomedEng.2024056294\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Critical reviews in biomedical engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1615/CritRevBiomedEng.2024056294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Mathematical Model Evaluating the Impact of Asymptomatic COVID-19 Cases and Reinfection.
In this study, an epidemic model with a constant recruitment rate of susceptible individuals with a bilinear transmission rate of infection is considered. Vaccination-type treatment is inspected to minimize the impact of the disease. The asymptomatic infected and the vaccinated compartments are taken with regard to the circumstances of the coronavirus disease (COVID-19) pandemic 2020-2025. The impact of these two compartments is examined specifically to shed light on the behavioral dynamics. Local as well as the global stability of the disease-free equilibrium point and the endemic equilibrium point are examined by constructing Lyapunov functions. Hence, we prove that if the basic reproduction number is < 1, then there will be no disease in the system, and if the basic reproduction number is > 1, then the disease will persist. Sensitivity analysis is performed to identify the influential model parameters that have the greatest impact on the original reproduction number of the proposed model. The model is validated by fitting it to real data. Furthermore, we carried out numerical simulations of the model parameters and their accompanying theoretical results. To control or eliminate the effect of emerging diseases, we made several suggestions to control the most sensitive model parameters while using necessary preventive measures.