Preprint Case Report Version 1 Preserved in Portico This version is not peer-reviewed

Statistical Error Calculation of Pandemic Predictive Models

Version 1 : Received: 9 June 2022 / Approved: 10 June 2022 / Online: 10 June 2022 (09:49:18 CEST)

How to cite: Nazir, M.H.; Gohar, F.A.; Rashid, U.; Yousuf, M.H. Statistical Error Calculation of Pandemic Predictive Models. Preprints 2022, 2022060158. https://doi.org/10.20944/preprints202206.0158.v1 Nazir, M.H.; Gohar, F.A.; Rashid, U.; Yousuf, M.H. Statistical Error Calculation of Pandemic Predictive Models. Preprints 2022, 2022060158. https://doi.org/10.20944/preprints202206.0158.v1

Abstract

COVID-19 outbreak started in the Chinese city of Wuhan and spread around the globe in months due to its high contagious level. Hence, this disease posed a great challenge to researchers and mathematicians. Numerous mathematical models have been suggested to visualize the spreading speed and trends of this pandemic. In this paper, a comparison of a widely established and accepted method, the Susceptible-Exposed-Infected-Quarantined-Recovered-Death-Insusceptible (SEIQRDP) model with a newly-proposed fractional-order SEIQRDP is studied. Densely populated Countries of Asia (Pakistan, India, and Bangladesh) have been chosen as data sets and both algorithms have been applied to their data. The same comparison technique has also been used on the data of two polar countries, New Zealand and Russia, that validated our findings. Error comparison of both algorithms has been recorded in a tabulated form which shows multi-fold erroneous trends over WHO data of selected countries.

Keywords

Epidemic Model; SEIQRDP; fractional-order SEIQRDP; COVID-19

Subject

Computer Science and Mathematics, Mathematics

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