Mathematical Modelling of COVID-19 Pandemic in Nepal Using Logistic Growth Model
Laxman Bahadur Kunwar1, Vijai Shanker Verma2*
1Department of Mathematics, Tribhuvan University, TRM Campus, Birgunj, Nepal
2*Department of Mathematics & Statistics, DeenDayal Upadhyaya Gorakhpur University, Gorakhpur, India
Laxman Bahadur Kunwar1, Vijai Shanker Verma2*
1Department of Mathematics, Tribhuvan University, TRM Campus, Birgunj, Nepal
2*Department of Mathematics & Statistics, DeenDayal Upadhyaya Gorakhpur University, Gorakhpur, India
Int. J. Grad. Res. Rev. Vol 7(1): 17-24.
Copyright (c) 2021 International Journal of Graduate Research and Review
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
In this study, coronavirus disease (COVID-19) outbreak in Nepal is studied by using exponential and logistic mathematical models. The model is analysed by deriving some important expressions such as growth rate of epidemic, maximum possible number of infected people and corresponding time of epidemic peak, relationship between number of cases per day and the total number of cases. The main objective of the study is to examine the applicability of the logistic model for the study of the COVID-19 pandemic and other similar communicable diseases in the future. The estimation of the parameters of the model is based upon COVID-19 pandemic data from January 20, 2020 to October 14, 2020. The actual time-series data of the coronavirus disease 2019 for Nepal seem to good fit the proposed model. The findings suggest that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviour are the best measures to reduce the transmission rate of the COVID-19. The detailed derivations of the expressions are presented regarding the working situation of non-mathematics researchers in the field of Biological Sciences.
Keywords: logistic equation; exponential growth; growth rate; mathematical modelling; coronavirus COVID-19; pandemic.
In this study, coronavirus disease (COVID-19) outbreak in Nepal is studied by using exponential and logistic mathematical models. The model is analysed by deriving some important expressions such as growth rate of epidemic, maximum possible number of infected people and corresponding time of epidemic peak, relationship between number of cases per day and the total number of cases. The main objective of the study is to examine the applicability of the logistic model for the study of the COVID-19 pandemic and other similar communicable diseases in the future. The estimation of the parameters of the model is based upon COVID-19 pandemic data from January 20, 2020 to October 14, 2020. The actual time-series data of the coronavirus disease 2019 for Nepal seem to good fit the proposed model. The findings suggest that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviour are the best measures to reduce the transmission rate of the COVID-19. The detailed derivations of the expressions are presented regarding the working situation of non-mathematics researchers in the field of Biological Sciences.
Keywords: logistic equation; exponential growth; growth rate; mathematical modelling; coronavirus COVID-19; pandemic.
