Mathematical modeling on the transmission of COVID-19 and its reproduction numbers in SAARC countries
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Abstract
In the middle of December 2019, a virus known as coronavirus (COVID-19) generated by severe acute respiratory syndrome corona virus 2 (SARC-CoV-2) was first detected in Wuhan, Hubei Province, China. As of the 9th of March, 2022, spread to over 212 countries, causing 429 million confirmed cases and 6 million people to lose their lives worldwide. In developing countries like the South Asian area, alarming dynamic variations in the pattern of confirmed cases and death tolls were displayed. During epidemics, accurate assessment of the characteristics that characterize infectious disease transmission is critical for optimizing control actions, planning, and adapting public health interventions. The reproductive number, or the typical number of secondary cases caused by an infected individual, can be employed to determine transmissibility. Several statistical and mathematical techniques have been presented to calculate across the duration of an epidemic. A technique is provided for calculating epidemic reproduction numbers. It is a MATLAB version of the EpiEstim package's R function estimate R, version 2.2-3. in the South Asian Association for Regional Cooperation (SAARC) countries. The three methodologies supported are 'parametric SI,' 'non-parametric SI,' and 'uncertain SI.' The present study indicated that the highest reproduction number was 12.123 and 11.861 on 5th and 14th March 2020 in India and Sri_Lanka, whereas the lowest reproduction number was the lowest was 0.300 and 0.315 in Sri_Lanka and India. The Maximum and minimum reproductive number of Bangladesh was 3.752 and 0.725. In this study, we have tried to point out the worst, best and current situation of SAARC countries.
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COVID-19, Estimate, Reproduction number, Transmission
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