[agents] Tailoring time series models for forecasting coronavirus spread: Case studies of 187 countries

[Leila Fayez Ismail]

Dear Colleagues,

I will be very happy to hear from you about our publication paper, which introduces a methodology to select the time-series model with the best accuracy for a particular country, among 13 time-series models.

Tailoring time series models for forecasting coronavirus spread:
Case studies of 187 countries
https://www.sciencedirect.com/science/article/pii/S2001037020303998<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS2001037020303998&data=04%7C01%7CLeila%40uaeu.ac.ae%7Ce07150867de8445dcdbe08d9356d616a%7C97a92b044c8743419b08d8051ef8dce2%7C0%7C0%7C637599566171041650%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=X1pVu6XjDZpoO%2BEYW%2FWD61iUsaqsrF6j5p8UYPmX72g%3D&reserved=0>

Please do not hesitate to contact me with your comments.

Abstract
When will the coronavirus end? Are the current precautionary measures effective? To answer these questions it is important to forecast regularly and accurately the spread of COVID-19 infections. Different time series forecasting models have been applied in the literature to tackle the pandemic situation. The current research efforts developed a few of these models and validate their accuracy for selected countries. It becomes difficult to draw an objective comparison between the performance of these models at a global scale. This is because the time series trend for the infection differs between the countries depending on the strategies adopted by the healthcare organizations to decrease the spread. Consequently, it is important to develop a tailored model for a country that allows healthcare organizations to better judge the effect of the undertaken precautionary measures, and provision more efficiently the needed resources to face this disease. This paper addresses this void. We develop and compare the performance of the time series models in the literature in terms of root mean squared error and mean absolute percentage error.

Best regards,
Leila


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Leila Ismail, Ph.D.
Associate Professor, Dept. of Computer Science & Software Engineering
Founder and Director to Intelligent Distributed Computing & Systems (INDUCE) Research Laboratory
(Industry 4.0 projects and beyond)
[Beyond the sky's the limit]
College of IT, UAE University
P.O.Box 15551, Al-Ain, UAE
Telephone: +971-3-7135530



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