Version 1
: Received: 31 May 2020 / Approved: 31 May 2020 / Online: 31 May 2020 (20:46:37 CEST)
How to cite:
Biswas, S.K.; Ghosh, J.K.; Sarkar, S.; Ghosh, U. COVID-19 Pandemic in India: A Mathematical Model Study. Preprints2020, 2020050508. https://doi.org/10.20944/preprints202005.0508.v1.
Biswas, S.K.; Ghosh, J.K.; Sarkar, S.; Ghosh, U. COVID-19 Pandemic in India: A Mathematical Model Study. Preprints 2020, 2020050508. https://doi.org/10.20944/preprints202005.0508.v1.
Cite as:
Biswas, S.K.; Ghosh, J.K.; Sarkar, S.; Ghosh, U. COVID-19 Pandemic in India: A Mathematical Model Study. Preprints2020, 2020050508. https://doi.org/10.20944/preprints202005.0508.v1.
Biswas, S.K.; Ghosh, J.K.; Sarkar, S.; Ghosh, U. COVID-19 Pandemic in India: A Mathematical Model Study. Preprints 2020, 2020050508. https://doi.org/10.20944/preprints202005.0508.v1.
Abstract
The present novel corona virus (2019-nCoV) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. The infection induced death rate is also very high. There is no vaccine or anti-viral medicine for such infection. So at this moment a major worldwide problem is that how we can control this pandemic. On the other hand, India is a high population density country, where the corona virus disease (COVID-19) has started to spread from $1^{st}$ week of March, 2020 in a significant number of COVID-19 positive cases. Due to this high population density human to human social contact rate is very high in India. So control of the pandemic COVID-19 in early stage is very urgent and challenging problem. Mathematical models are employed in this paper to study the COVID-19 dynamics, to identify the influential parameters and to find the proper prevention strategies to reduce the outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the key model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impacts on the disease dynamics have also been studied.Future trends of the disease transmission has been Predicted from our model with some control measures. Finally, the positive measures to control the disease have been summarized.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
