A mathematical model for control strategies of COVID-19

References

• NHS. SARS (severe acute respiratory syndrome), https://www.nhs.uk/conditions/sars/. 10 2019. Accessed on 27 March, 2020.
   Google Scholar
• WHO. Coronavirus disease (COVID-19) outbreak, 2020. http://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov. Access on 11 April 2020.
   Google Scholar
• WHO. Consensus document on the epidemiology of severe acute respiratory syndrome (SARS), 11 2003. http://www.who.int/csr/sars/en/WHOconsensus.pdf. Accessed on 27 March, 2020.
   Google Scholar
• Luca Ferretti, Chris Wymant, Michelle Kendall, Lele Zhao, Anel Nurtay, Lucie Abeler-Dörner, Michael Parker, David Bonsall, and Christophe Fraser. Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing. Science, 368(6491):1–7, 2020. DOI: https://doi.org/10.1126/science.abb6936.
   Web of Science ®Google Scholar
• Hiroshi Nishiura, Natalie M Linton, and Andrei R Akhmetzhanov. Serial interval of novel coronavirus (COVID-19) infections. International journal of infectious diseases, 93 (2020):284–286.
   PubMed Web of Science ®Google Scholar
• LA Real and R Biek. Infectious disease modeling and the dynamics of transmission. Wildlife and emerging zoonotic diseases: the biology, circumstances and consequences of cross-species transmission, pages 33–49, 2007.
   Google Scholar
• Joel Hellewell, Sam Abbott, Amy Gimma, Nikos I Bosse, Christopher I Jarvis, Timothy W Russell, James D Munday, Adam J Kucharski, WJohn Edmunds, Fiona Sun, et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. The Lancet Global Health, 8:e488–e496, 2020. DOI: https://doi.org/10.1016/S2214-109X(20)30074-7.
   PubMed Web of Science ®Google Scholar
• Prakashini Banka and Catherine M Comiskey. The incubation period of covid-19: A scoping review and meta-analysis to aid modelling and planning. medRxiv, 2020. DOI: https://doi.org/10.1101/2020.10.20.20216143.
   Google Scholar
• NA Hartemink, SE Randolph, SA Davis, and JAP Heesterbeek. The basic reproduction number for complex disease systems: Defining R0 for tick-borne infections. The American Naturalist, 171(6):743–754, 2008. DOI: https://doi.org/10.1086/587530.
   PubMed Web of Science ®Google Scholar
• Nicholas LePan. Visualizing the history of pandemics, March 2020. Accessed on 14 June 2020.
   Google Scholar
• Yanli Ma, Jia-Bao Liu, and Haixia Li. Global dynamics of an SIQR model with vaccination and elimination hybrid strategies. Mathematics, 6(328):2–12, 2018. DOI: https://doi.org/10.3390/math6120328.
   Google Scholar
• Muhammad Dure Ahmad, Muhammad Usman, Adnan Khan, and Mudassar Imran. Optimal control analysis of ebola disease with control strategies of quarantine and vaccination. Infectious diseases of poverty, 5:72:1–12, 2016. DOI: https://doi.org/10.1186/s40249-016-0161-6.
   PubMedGoogle Scholar
• Zhongwei Cao and Shengjuan Zhou. Dynamical behaviors of a stochastic SIQR epidemic model with quarantine-adjusted incidence. Discrete Dynamics in Nature and Society, 2018, 2018. DOI: https://doi.org/10.1155/2018/3693428.
   Google Scholar
• Gerardo Chowell, Paul W Fenimore, Melissa A Castillo-Garsow, and Carlos Castillo-Chavez. SARS outbreaks in ontario, hong kong and singapore: the role of diagnosis and isolation as a control mechanism. Journal of theoretical biology, 224:1–8, 2003. DOI: https://doi.org/10.1016/S0022-5193(03)00228-5.
   PubMed Web of Science ®Google Scholar
• Attila Dénes and Abba B Gumel. Modeling the impact of quarantine during an outbreak of ebola virus disease. Infectious Disease Modelling, 4:12–27, 2019. DOI: https://doi.org/10.1016/j.idm.2019.01.003.
   PubMedGoogle Scholar
• Abba B Gumel, Shigui Ruan, Troy Day, James Watmough, Fred Brauer, P Van den Driessche, Dave Gabrielson, Chris Bowman, Murray E Alexander, Sten Ardal, et al. Modelling strategies for controlling SARS outbreaks. Proceedings of the Royal Society of London. Series B: Biological Sciences, 271(1554):2223–2232, 2004. DOI: https://doi.org/10.1098/rspb.2004.2800.
   PubMed Web of Science ®Google Scholar
• Wendi Wang and Shigui Ruan. Simulating the SARS outbreak in beijing with limited data. Journal of theoretical biology, 227 (2004) (3):369–379, 2004. DOI: https://doi.org/10.1016/j.jtbi.2003.11.014.
   PubMed Web of Science ®Google Scholar
• Yicang Zhou, Zhien Ma, and Fred Brauer. A discrete epidemic model for sars transmission and control in china. Mathematical and Computer Modelling, 40(13):1491–1506, 2004. DOI: https://doi.org/10.1016/j.mcm.2005.01.007.
   PubMedGoogle Scholar
• Biao Tang, Nicola Luigi Bragazzi, Qian Li, Sanyi Tang, Yanni Xiao, and Jianhong Wu. An updated estimation of the risk of transmission of the novel coronavirus (2019-ncov). Infectious disease modelling, 5 (2020):248–255, 2020. DOI: https://doi.org/10.1016/j.idm.2020.02.001.
   PubMedGoogle Scholar
• Weston C Roda, Marie B Varughese, Donglin Han, and Michael Y Li. Why is it difficult to accurately predict the covid-19 epidemic? Infectious Disease Modelling, 5 (2020):271–281, 2020.
   PubMedGoogle Scholar
• Jun Lin, Weihao Huang, Muchen Wen, Dehong Li, Shuyi Ma, Jiawen Hua, Hang Hu, Shan Yin, Yanjun Qian, Peiling Chen, et al. Containing the spread of coronavirus disease 2019 (covid-19): Meteorological factors and control strategies. Science of The Total Environment, 744 (2020) 140935:1–7, 2020. DOI: https://doi.org/10.1016/j.scitotenv.2020.140935.
   Web of Science ®Google Scholar
• Cleo Anastassopoulou, Lucia Russo, Athanasios Tsakris, and Constantinos Siettos. Databased analysis, modelling and forecasting of the COVID-19 outbreak. PloS one, 15(3:e0230405):1–21, 2020. DOI: https://doi.org/10.1371/journal.pone.0230405.
   Web of Science ®Google Scholar
• Jinming Cao, Xia Jiang, Bin Zhao, et al. Mathematical modeling and epidemic prediction of covid-19 and its significance to epidemic prevention and control measures. Journal of Biomedical Research & Innovation, 1(1:103):1–19, 2020.
   Google Scholar
• Liangrong Peng, Wuyue Yang, Dongyan Zhang, Changjing Zhuge, and Liu Hong. Epidemic analysis of COVID-19 in china by dynamical modeling. pages 1–11.
   Google Scholar
• Bimal Kumar Mishra, Ajit Kumar Keshri, Yerra Shankar Rao, Binay Kumar Mishra, Buddhadeo Mahato, Syeda Ayesha, Bansidhar Prasad Rukhaiyyar, Dinesh Kumar Saini, and Aditya Kumar Singh. COVID-19 created chaos across the globe: Three novel quarantine epidemic models. Chaos, Solitons & Fractals, 138 (2020) 109928:1–34, 2020. DOI: https://doi.org/10.1016/j.chaos.2020.109928.
   Web of Science ®Google Scholar
• Vaibhav Bhatnagar, Ramesh Chandra Poonia, Pankaj Nagar, Sandeep Kumar, Vijander Singh, Linesh Raja, and Pranav Dass. Descriptive analysis of covid-19 patients in the context of india. Journal of Interdisciplinary Mathematics, pages 1–16, 2020. DOI: https://doi.org/10.1080/09720502.2020.1761635.
   Web of Science ®Google Scholar
• Vijander Singh, Ramesh Chandra Poonia, Sandeep Kumar, Pranav Dass, Pankaj Agarwal, Vaibhav Bhatnagar, and Linesh Raja. Prediction of covid-19 corona virus pandemic based on time series data using support vector machine. Journal of Discrete Mathematical Sciences and Cryptography, 23:8:1583–1597, 2020. DOI: https://doi.org/10.1080/09720529.2020.1784535.
   Web of Science ®Google Scholar
• Rajani Kumari, Sandeep Kumar, Ramesh Chandra Poonia, Vijander Singh, Linesh Raja, Vaibhav Bhatnagar, and Pankaj Agarwal. Analysis and predictions of spread, recovery, and death caused by covid-19 in india. Big Data Mining and Analytics, 4(2):65–75, 2021.
   Google Scholar
• Palak Agarwal and Kavita Jhajharia. Data analysis and modeling of covid-19. Journal of Statistics and Management Systems, 24(1):1–16, 2021. DOI: https://doi.org/10.1080/09720510.2020.1840076.
   Web of Science ®Google Scholar
• SD Warbhe, NK Lamba, and KC Deshmukh. Impact of covid-19: A mathematical model. Journal of Interdisciplinary Mathematics, pages 1–11, 2020. DOI: https://doi.org/10.1080/09720502.2020.1833444.
   Google Scholar
• Sanjay Kumar, Vineet Kumar, Uday Awasthi, Manu Vatsal, and Sanjay Kumar Singh. Modified seir model for prediction of covid-19 outbreak trend in india with effectiveness of preventive care. Journal of Statistics and Management Systems, pages 1–11, 2020. DOI: https://doi.org/10.1080/09720510.2020.1833463.
   Google Scholar
• Jayanta Mondal, Piu Samui, and Amar Nath Chatterjee. Optimal control strategies of nonpharmaceutical and pharmaceutical interventions for covid-19 control. Journal of Interdisciplinary Mathematics, pages 1–29, 2020. DOI: https://doi.org/10.1080/09720502.2020.1833459.
   Google Scholar
• Odo Diekmann, JAP Heesterbeek, and Michael G Roberts. The construction of nextgeneration matrices for compartmental epidemic models. Journal of the Royal Society Interface, 7(47):873–885, 2010. DOI: https://doi.org/10.1098/rsif.2009.0386.
   PubMed Web of Science ®Google Scholar
• Hyun Mo Yang. The basic reproduction number obtained from jacobian and next generation matrices–a case study of dengue transmission modelling. Biosystems, 126:52–75, 2014. DOI: https://doi.org/10.1016/j.biosystems.2014.10.002.
   PubMed Web of Science ®Google Scholar