Mathematical modeling of COVID-19 transmission: The roles of intervention strategies and lockdown

被引:0
|
作者
Bugalia S. [1 ]
Bajiya V.P. [1 ]
Tripathi J.P. [1 ]
Li M.-T. [2 ]
Sun G.-Q. [3 ,4 ]
机构
[1] Department of Mathematics, Central University of Rajasthan, Bandar Sindri, Kishangarh, Ajmer, Rajasthan
[2] School of Mathematics, Taiyuan University of Technology, Taiyuan
[3] Department of Mathematics, North University of China, Taiyuan
[4] Complex Systems Research Center, Shanxi University, Taiyuan
来源
基金
中国国家自然科学基金;
关键词
COVID-19; Lockdown; Quarantine; Stability; Transcritical bifurcation; Transmission rate;
D O I
10.3934/MBE.2020318
中图分类号
学科分类号
摘要
An outbreak of rapidly spreading coronavirus established human to human transmission and now became a pandemic across the world. The new confirmed cases of infected individuals of COVID-19 are increasing day by day. Therefore, the prediction of infected individuals has become of utmost important for health care arrangements and to control the spread of COVID-19. In this study, we propose a compartmental epidemic model with intervention strategies such as lockdown, quarantine, and hospitalization. We compute the basic reproduction number (R0), which plays a vital role in mathematical epidemiology. Based on R0, it is revealed that the system has two equilibrium, namely disease-free and endemic. We also demonstrate the non-negativity and boundedness of the solutions, local and global stability of equilibria, transcritical bifurcation to analyze its epidemiological relevance. Furthermore, to validate our system, we fit the cumulative and new daily cases in India. We estimate the model parameters and predict the near future scenario of the disease. The global sensitivity analysis has also been performed to observe the impact of different parameters on R0. We also investigate the dynamics of disease in respect of different situations of lockdown, e.g., complete lockdown, partial lockdown, and no lockdown. Our analysis concludes that if there is partial or no lockdown case, then endemic level would be high. Along with this, the high transmission rate ensures higher level of endemicity. From the short time prediction, we predict that India may face a crucial phase (approx 6000000 infected individuals within 140 days) in near future due to COVID-19. Finally, numerical results show that COVID-19 may be controllable by reducing the contacts and increasing the efficacy of lockdown. © 2020 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
引用
收藏
页码:5961 / 5986
页数:25
相关论文
共 50 条
  • [41] Mathematical modelling of COVID-19 transmission and mitigation strategies in the population of Ontario, Canada
    Tuite, Ashleigh R.
    Fisman, David N.
    Greer, Amy L.
    CANADIAN MEDICAL ASSOCIATION JOURNAL, 2020, 192 (19) : E497 - E505
  • [42] ABOUT MATHEMATICAL MODELING OF COVID-19
    Krivorotko, Olga Igorevna
    Kabanikhin, Sergey Igorevich
    SIBERIAN ELECTRONIC MATHEMATICAL REPORTS-SIBIRSKIE ELEKTRONNYE MATEMATICHESKIE IZVESTIYA, 2023, 20 (02): : 1211 - 1268
  • [43] Mathematical modeling of the outbreak of COVID-19
    Arvind Kumar Sinha
    Nishant Namdev
    Pradeep Shende
    Network Modeling Analysis in Health Informatics and Bioinformatics, 2022, 11
  • [44] Mathematical modeling and control of Covid-19
    Ghasemabadi, Atena
    MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2024, 47 (12) : 10478 - 10489
  • [45] Mathematical modeling of the outbreak of COVID-19
    Sinha, Arvind Kumar
    Namdev, Nishant
    Shende, Pradeep
    NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, 2022, 11 (01):
  • [46] Aggravation of Cancer, Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling
    Efil, Fatma Nese
    Qureshi, Sania
    Gokbulut, Nezihal
    Hosseini, Kamyar
    Hincal, Evren
    Soomro, Amanullah
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2024, 140 (01): : 485 - 512
  • [47] Mathematical modelling for decision making of lockdown during COVID-19
    Ghosh, Ahona
    Roy, Sandip
    Mondal, Haraprasad
    Biswas, Suparna
    Bose, Rajesh
    APPLIED INTELLIGENCE, 2022, 52 (01) : 699 - 715
  • [48] A SIQ mathematical model on COVID-19 investigating the lockdown effect
    Bhadauria, Archana Singh
    Pathak, Rachana
    Chaudhary, Manisha
    INFECTIOUS DISEASE MODELLING, 2021, 6 : 244 - 257
  • [49] Mathematical modelling for decision making of lockdown during COVID-19
    Ahona Ghosh
    Sandip Roy
    Haraprasad Mondal
    Suparna Biswas
    Rajesh Bose
    Applied Intelligence, 2022, 52 : 699 - 715
  • [50] Conformable mathematical modeling of the COVID-19 transmission dynamics: A more general study
    Thabet, Hayman
    Kendre, Subhash
    MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2023, 46 (17) : 18126 - 18149