Background: The coronavirus pandemic (COVID-19) is causing a havoc globally, exacerbated by the newly discovered SARS-CoV-2 virus. Due to its high population density, India is one of the most badly effected countries from the first wave of COVID-19. Therefore, it is extremely necessary to accurately predict the state-wise and overall dynamics of COVID-19 to get the effective and efficient organization of resources across India. Methods: In this study, the dynamics of COVID-19 in India and several of its selected states with different demographic structures were analyzed using the SEIRD epidemiological model. The basic reproductive ratio R0 was systemically estimated to predict the dynamics of the temporal progression of COVID-19 in India and eight of its states, Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh. Results: For India, the SEIRD model calculations show that the peak of infection is expected to appear around the middle of October, 2020. Furthermore, we compared the model scenario to a Gaussian fit of the daily infected cases and obtained similar results. The early imposition of a nation-wide lockdown has reduced the number of infected cases but delayed the appearance of the infection peak significantly. Conclusion: After comparing our calculations using India's data to the real life dynamics observed in Italy and Russia, we can conclude that the SEIRD model can predict the dynamics of COVID-19 with sufficient accuracy.
{"title":"A study of the COVID-19 epidemic in India using the SEIRD model","authors":"R. Banerjee, S. Bhattacharjee, P. Varadwaj","doi":"10.15302/j-qb-021-0260","DOIUrl":"https://doi.org/10.15302/j-qb-021-0260","url":null,"abstract":"Background: The coronavirus pandemic (COVID-19) is causing a havoc globally, exacerbated by the newly discovered SARS-CoV-2 virus. Due to its high population density, India is one of the most badly effected countries from the first wave of COVID-19. Therefore, it is extremely necessary to accurately predict the state-wise and overall dynamics of COVID-19 to get the effective and efficient organization of resources across India. Methods: In this study, the dynamics of COVID-19 in India and several of its selected states with different demographic structures were analyzed using the SEIRD epidemiological model. The basic reproductive ratio R0 was systemically estimated to predict the dynamics of the temporal progression of COVID-19 in India and eight of its states, Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh. Results: For India, the SEIRD model calculations show that the peak of infection is expected to appear around the middle of October, 2020. Furthermore, we compared the model scenario to a Gaussian fit of the daily infected cases and obtained similar results. The early imposition of a nation-wide lockdown has reduced the number of infected cases but delayed the appearance of the infection peak significantly. Conclusion: After comparing our calculations using India's data to the real life dynamics observed in Italy and Russia, we can conclude that the SEIRD model can predict the dynamics of COVID-19 with sufficient accuracy.","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"31 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67351195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-06DOI: 10.1007/s40484-020-0210-9
Xu Liao, Xiaoran Chai, Xingjie Shi, Lin S. Chen, Jin Liu
{"title":"The statistical practice of the GTEx Project: from single to multiple tissues","authors":"Xu Liao, Xiaoran Chai, Xingjie Shi, Lin S. Chen, Jin Liu","doi":"10.1007/s40484-020-0210-9","DOIUrl":"https://doi.org/10.1007/s40484-020-0210-9","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1 - 17"},"PeriodicalIF":3.1,"publicationDate":"2020-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0210-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42372291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-31DOI: 10.1007/s40484-020-0212-7
Xue Jiang, Mohammad Asad, Lin Li, Zhanpeng Sun, Jean-Sébastien Milanese, Bo Liao, Edwin Wang
{"title":"Germline genomes have a dominant-heritable contribution to cancer immune evasion and immunotherapy response","authors":"Xue Jiang, Mohammad Asad, Lin Li, Zhanpeng Sun, Jean-Sébastien Milanese, Bo Liao, Edwin Wang","doi":"10.1007/s40484-020-0212-7","DOIUrl":"https://doi.org/10.1007/s40484-020-0212-7","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1 - 12"},"PeriodicalIF":3.1,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0212-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48750306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-23DOI: 10.1007/s40484-020-0211-8
Naoki Matsuda, Ken-ichi Hironaka, Masashi Fujii, Takumi Wada, Katsuyuki Kunida, Haruki Inoue, M. Eto, Daisuke Hoshino, Y. Furuichi, Y. Manabe, N. Fujii, H. Noji, H. Imamura, Shinya Kuroda
{"title":"Monitoring and mathematical modeling of mitochondrial ATP in myotubes at single-cell level reveals two distinct population with different kinetics","authors":"Naoki Matsuda, Ken-ichi Hironaka, Masashi Fujii, Takumi Wada, Katsuyuki Kunida, Haruki Inoue, M. Eto, Daisuke Hoshino, Y. Furuichi, Y. Manabe, N. Fujii, H. Noji, H. Imamura, Shinya Kuroda","doi":"10.1007/s40484-020-0211-8","DOIUrl":"https://doi.org/10.1007/s40484-020-0211-8","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1 - 10"},"PeriodicalIF":3.1,"publicationDate":"2020-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0211-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49412760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-18DOI: 10.1007/s40484-020-0209-2
Kang Kang, Xue-Long Sun, Lizhong Wang, Xiaotian Yao, Senwei Tang, Junjie Deng, Xiaoli Wu, Can Yang, Gang Chen
{"title":"Direct-to-consumer genetic testing in China and its role in GWAS discovery and replication","authors":"Kang Kang, Xue-Long Sun, Lizhong Wang, Xiaotian Yao, Senwei Tang, Junjie Deng, Xiaoli Wu, Can Yang, Gang Chen","doi":"10.1007/s40484-020-0209-2","DOIUrl":"https://doi.org/10.1007/s40484-020-0209-2","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1 - 15"},"PeriodicalIF":3.1,"publicationDate":"2020-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0209-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49242355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-17DOI: 10.1007/s40484-020-0207-4
Huanhuan Zhu, Xiang Zhou
{"title":"Transcriptome-wide association studies: a view from Mendelian randomization","authors":"Huanhuan Zhu, Xiang Zhou","doi":"10.1007/s40484-020-0207-4","DOIUrl":"https://doi.org/10.1007/s40484-020-0207-4","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1-15"},"PeriodicalIF":3.1,"publicationDate":"2020-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0207-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45821382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1007/s40484-020-0208-3
Xing Chen, Y. Lai
{"title":"A censored-Poisson model based approach to the analysis of RNA-seq data","authors":"Xing Chen, Y. Lai","doi":"10.1007/s40484-020-0208-3","DOIUrl":"https://doi.org/10.1007/s40484-020-0208-3","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1-17"},"PeriodicalIF":3.1,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0208-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47639660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-09DOI: 10.1007/s40484-020-0205-6
Bo Yuan, Yao Lu, Q. Zhang, Lin Hou
{"title":"Prediction and differential analysis of RNA secondary structure","authors":"Bo Yuan, Yao Lu, Q. Zhang, Lin Hou","doi":"10.1007/s40484-020-0205-6","DOIUrl":"https://doi.org/10.1007/s40484-020-0205-6","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1-10"},"PeriodicalIF":3.1,"publicationDate":"2020-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-020-0205-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47773580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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