Modelling the transmission dynamics of COVID-19 in six high-burden countries

Rahman, Azizur, and Kuddus, Md Abdul (2021) Modelling the transmission dynamics of COVID-19 in six high-burden countries. BioMed Research International, 2021. 5089184.

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The new Coronavirus Disease 19, officially known as COVID-19, originated in China in 2019 and has since spread worldwide. We presented an age-structured Susceptible-Latent-Mild-Critical-Removed (SLMCR) compartmental model of COVID-19 disease transmission with nonlinear incidence during the pandemic period. We provided the model calibration to estimate parameters with day-wise COVID-19 data, i.e., reported cases by worldometer from 15th February to 30th March 2020 in six high-burden countries, including Australia, Italy, Spain, the USA, the UK, and Canada. We estimate transmission rates for each country and found that the country with the highest transmission rate is Spain, which may increase the new cases and deaths than the other countries. We found that saturation infection negatively impacted the dynamics of COVID-19 cases in all the six high-burden countries. The study used a sensitivity analysis to identify the most critical parameters through the partial rank correlation coefficient method. We found that the transmission rate of COVID-19 had the most significant influence on prevalence. The prediction of new cases in COVID-19 until 30th April 2020 using the developed model was also provided with recommendations to control strategies of COVID-19. We also found that adults are more susceptible to infection than both children and older people in all six countries. However, in Italy, Spain, the UK, and Canada, older people show more susceptibility to infection than children, opposite to the case in Australia and the USA. The information generated from this study would be helpful to the decision-makers of various organisations across the world, including the Ministry of Health in Australia, Italy, Spain, the USA, the UK, and Canada, to control COVID-19.

Item ID: 72740
Item Type: Article (Research - C1)
ISSN: 2314-6133
Copyright Information: Copyright © 2021 Azizur Rahman and Md Abdul Kuddus. 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.
Date Deposited: 10 Mar 2022 03:57
FoR Codes: 42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 100%
SEO Codes: 20 HEALTH > 2002 Evaluation of health and support services > 200205 Health policy evaluation @ 100%
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