{"title":"基于网络SEIR模型的印度新冠肺炎疫情防控措施实施与阶段性放松分析","authors":"Piklu Mallick, Sourav K. Bhowmick, S. Panja","doi":"10.1109/ICC54714.2021.9703146","DOIUrl":null,"url":null,"abstract":"In this paper, an investigation is carried out to analyse how periodic lockdown and unlocking have helped India to combat the first wave of COVID-19. To that end, a networked SEIR model is considered that captures the spreading dynamics of the disease in sixteen of the worst affected states of India. In this regard, a distance based contact matrix is constructed to reflect the connectivity between states. Various rate parameters of the model are estimated as well as the basic reproduction number $(\\mathscr{R}_{0})$ of each of the sixteen states for each phase of lockdown is found out. Finally, a comparison is drawn between the simulated results of cumulative infected caseload using the estimated parameters and that with the real COVID-19 data of India till December 31, 2020, which establishes the effectiveness of the method.","PeriodicalId":382373,"journal":{"name":"2021 Seventh Indian Control Conference (ICC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of Imposition and Periodic Relaxation of Lockdown on the Spread of COVID-19 in India through Networked SEIR Model\",\"authors\":\"Piklu Mallick, Sourav K. Bhowmick, S. Panja\",\"doi\":\"10.1109/ICC54714.2021.9703146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an investigation is carried out to analyse how periodic lockdown and unlocking have helped India to combat the first wave of COVID-19. To that end, a networked SEIR model is considered that captures the spreading dynamics of the disease in sixteen of the worst affected states of India. In this regard, a distance based contact matrix is constructed to reflect the connectivity between states. Various rate parameters of the model are estimated as well as the basic reproduction number $(\\\\mathscr{R}_{0})$ of each of the sixteen states for each phase of lockdown is found out. Finally, a comparison is drawn between the simulated results of cumulative infected caseload using the estimated parameters and that with the real COVID-19 data of India till December 31, 2020, which establishes the effectiveness of the method.\",\"PeriodicalId\":382373,\"journal\":{\"name\":\"2021 Seventh Indian Control Conference (ICC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Seventh Indian Control Conference (ICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICC54714.2021.9703146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Seventh Indian Control Conference (ICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICC54714.2021.9703146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of Imposition and Periodic Relaxation of Lockdown on the Spread of COVID-19 in India through Networked SEIR Model
In this paper, an investigation is carried out to analyse how periodic lockdown and unlocking have helped India to combat the first wave of COVID-19. To that end, a networked SEIR model is considered that captures the spreading dynamics of the disease in sixteen of the worst affected states of India. In this regard, a distance based contact matrix is constructed to reflect the connectivity between states. Various rate parameters of the model are estimated as well as the basic reproduction number $(\mathscr{R}_{0})$ of each of the sixteen states for each phase of lockdown is found out. Finally, a comparison is drawn between the simulated results of cumulative infected caseload using the estimated parameters and that with the real COVID-19 data of India till December 31, 2020, which establishes the effectiveness of the method.