Browsing by Author "Sadhu, A."

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    Comparative analysis of the impact of epidemiological modeling on COVID-19
    (De Gruyter, 2023) Bhattacharjee, S.; Das, K.; Zaman, S.; Sadhu, A.; Roy, S.K.; Naha, A.; Khan, F.S.; Sarkar, B.
    This chapter provides a comprehensive review on different existing epidemiological models proposed for analyzing the impact of COVID-19. Since December 2019, COVID-19 emerged as an alarming threat to mankind. To mitigate the impact of pandemic, several preventive measures have been practiced by nations. But due to mutation of the virus, the pandemic prevails. This review provides a vivid description of the contributions of different existing epidemiological models on COVID-19. A comparative analysis of SIR, ESIR, SEPIR, SEIR, SEIJR, SEIAR, SEIR-P, SIRD, SEIRD, R-SEIRD, SEIRDH, SEIQARDT, SIDARTHE, θ-SEIHRD, and SIRDV models have been highlighted. Effects of important parameters like infection rate and recovery rate on different epidemiological models have been addressed. Model parameters, assumptions about the model, techniques used, and contributions and drawbacks of the respective models have also been discussed. Apart from epidemical models, this chapter aims to focus on precise illustration on multiple strains of SARS-CoV-2. Comprehensive analysis on the impact of vaccination on multiple strains has also been reported. © 2023 Walter de Gruyter GmbH, Berlin/Boston.