Abstract

BackgroundOver 150,000 confirmed cases, around 140 countries, and about 6,000 death occurred owing to coronavirus disease 2019 (COVID-19) pandemic in China, Italy, Iran, and South Korea. Iran reported its first confirmed cases of COVID-19 in Qom City on 19 February 2020 and has the third-highest number of COVID-19 deaths after China and Italy and the highest in Western Asia.MethodsWe applied a two-part model of time series to predict the spread of COVID-19 in Iran through addressing the daily relative increments. All of the calculations, simulations, and results in our paper were carried out by using MatLab R2015b software. The average, upper bound, and lower bound were calculated through 100 simulations of the fitted models.ResultsAccording to the prediction, it is expected that by 15 April 2020, the relative increment (RI) falls to the interval 1.5% to 3.6% (average equal to 2.5%). During the last three days, the RI belonged to the interval of 12% to 15%. It is expected that the reported cumulative number of confirmed cases reaches 71,000 by 15 April, 2020. Moreover, 80% confidence interval was calculated as 35K and 133K.ConclusionsThe screening of suspected people, using their electronic health files, helps isolate the patients in their earlier stage, which in turn helps decrease the period of transmissibility of the patients. Considering all issues, the best way is to apply the model with no modification to model the probable increasing or decreasing acceleration of spreading.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

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.