Abstract
AbstractExtension 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 to fit 4-set of COVID-19 clinical data consist of cumulative populations of infected, deceased, recovered, and susceptible. Trends of COVID-19 in Trends in Gulf Cooperation Council (GCC) countries are successfully predicted using available data from outbreak until 23rd June 2020. Promising results of SEIR-PAD model provide insight into better management of COVID-19 pandemic in GCC countries.
Publisher
Cold Spring Harbor Laboratory
Reference13 articles.
1. Treatment strategies for Middle East respiratory syndrome coronavirus;J Virus Erad,2016
2. Centers for Disease Control and Prevention. A Novel Coronavirus Called MERS-CoV [Updated August 22,2016]. Available from: https://www.cdc.gov/coronavirus/
3. Modeling of a super-spreading event of the MERS-corona virus during the Hajj season using simulation of the existing data;Int J Stat Med Biol Res,2017
4. The Characteristics of Middle Eastern Respiratory Syndrome Coronavirus Transmission Dynamics in South Korea