Abstract
Mathematical models are a must to better understand data and its possible consequences. For COVID-19 outbreak, it helps to predict, and therefore, policies and guidelines can be designed accordingly. In this study, we define an improved mathematical model to evaluate the severity of any pandemic like COVID-19 given the average recovery time. Progressive mortality and progressive recovery rates are defined by considering the median of the number of cases during the recovery period. Since the median is resistant to outlier data points, there is a scope to define new formulae by considering a more suitable data representative. This article has defined two new terms called the Advanced Recovery Rate (ARR) and Advanced Mortality Rate (AMR). This study presents mathematical formulae for ARR and AMR. The Mathematical justification and proof of concept of the advanced formulae show that it will replace the existing terms and be beneficial to all the stakeholders.
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Appendices
Appendix
Case Study
Consider that there are 200 infected cases by the particular pandemic or epidemic from days 1 to 20. After 20 days, there is no positive case. Considering an optimum recovery time interval of 10 days, in separate Excel sheet, detailed information about advanced, classical, and progressive rates for recovery and mortality rates are provided.
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Bhapkar, H.R., Mahalle, P.N., Shinde, G.R. (2023). Advanced Mathematical Model to Measure the Severity of Any Pandemics. In: Dey, N. (eds) Data-Driven Approach for Bio-medical and Healthcare. Data-Intensive Research. Springer, Singapore. https://doi.org/10.1007/978-981-19-5184-8_11
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DOI: https://doi.org/10.1007/978-981-19-5184-8_11
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