medRxiv preprint doi: https://doi.org/10.1101/2020.11.29.20240515; this version posted December 11, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license . Trends of COVID-19 (Coronavirus Disease) in GCC Countries using SEIR-PAD Dynamic Model Ahmad Sedaghat 1*, Seyed Amir Abbas Oloomi 2, Mahdi Ashtian Malayer 3, Amir Mosavi 4,5,6* 1School of Engineering, Australian College of Kuwait, Safat 13015, Kuwait;
[email protected];
[email protected] 2 Department of Mechanical Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran;
[email protected] 3Young Researchers and Elite Club, Yazd Branch, Islamic Azad University, Yazd, Iran;
[email protected] 4School of Economics and Business, Norwegian University of Life Sciences, 1430 Ås, Norway 5School of the Built Environment, Oxford Brookes University, Oxford OX3 0BP, UK 6John von Neumann Faculty of Informatics, Obuda University, 1034 Budapest, Hungary;
[email protected] Abstract Extension of SIR type models has been reported in a number of publications in mathematics community. But little is done on validation of these models to fit adequately with multiple clinical data of an infectious disease. In this paper, we introduce SEIR-PAD model to assess susceptible, exposed, infected, recovered, super-spreader, asymptomatic infected, and deceased populations. SEIR-PAD model consists of 7-set of ordinary differential equations with 8 unknown coefficients which are solved numerically in MATLAB using an optimization algorithm.