Abstract
The first outbreak of the COVID-19 epidemic in Saudi Arabia was reported on March 2nd, 2020. Every year more than 2 million people come from more than 188 countries to Saudi Arabia to perform pilgrimage (Hajj in Arabic). Therefore, extrapolating the epidemic strength during the Hajj season (end of July) in the holy places has become essential. In this paper, we employ the power of mathematical modeling to infer the epidemic intensity over a 300 days’ time span in Saudi Arabia generally and the Holy places specifically. In particular, we obtain the following epidemiological insights such as the number of infections, the daily infection increase, the expected number of death cases, and the epidemic peak. Results indicate that, the epidemic peak has already been reached in both Makka and Madina. In addition, the number of infections will reach its saturation point by the first week of October 2020 as the daily increase in the number of infections will diminish. This means that, Hajj can be conducted safely only by reducing the number of pilgrims and providing suitable sets of preventive and precautionary measures.
Highlights
The outbreak of novel coronavirus (COVID-19)disease was first reported in Wuhan City, China in December 2019
We study the epidemiological situation in Saudi Arabia
Saudi Arabia was reported on March 2nd, 2020
Summary
The outbreak of novel coronavirus (COVID-19)disease was first reported in Wuhan City, China in December 2019. Pathologists around the globe are working tirelessly to find a vaccine or treatment for the invading virus. Researchers are working hard to model the virus spreading dynamics and developing mathematical models to predict the spreading behaviour of the coronavirus. In [2], Toshikazu Kuniya employed the SEIR model to predict the epidemic peak of Coronavirus in Japan. The author found out that, an epidemic peak may reach the early-middle summer. Hiroshi Nishiura [3], studied the infection scenario of the novel coronavirus in on the Diamond Princess. He employed a back-calculation method to estimate the peak time of infection and the estimated number of infections on the ship. Zaho et al, [4] presented
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.