Mohammed Aba Oud1, Muqrin Almuqrin2. 1. Department of Mathematics and Statistics, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia. maabaoud@imamu.edu.sa. 2. Department of Mathematics, Faculty of Science in Zulfi, Majmaah University, Kingdom of Saudi Arabia.
Abstract
INTRODUCTION: This paper aims to measure the performance of early detection methods, which are usually used for infectious diseases. METHODOLOGY: By using real data of confirmed Coronavirus cases from the Kingdom of Saudi Arabia and Italy, the moving epidemic method (MEM) and the moving average cumulative sums (Mov. Avg Cusum) methods are used in our simulation study. RESULTS: Our results suggested that the CUSUM method outperforms the MEM in detecting the start of the Coronavirus outbreak. Copyright (c) 2021 Mohammed Aba Oud, Muqrin Almuqrin.
INTRODUCTION: This paper aims to measure the performance of early detection methods, which are usually used for infectious diseases. METHODOLOGY: By using real data of confirmed Coronavirus cases from the Kingdom of Saudi Arabia and Italy, the moving epidemic method (MEM) and the moving average cumulative sums (Mov. Avg Cusum) methods are used in our simulation study. RESULTS: Our results suggested that the CUSUM method outperforms the MEM in detecting the start of the Coronavirus outbreak. Copyright (c) 2021 Mohammed Aba Oud, Muqrin Almuqrin.
Entities:
Keywords:
COVID-19; CUSUM; MEM; Public health; detection method; monitoring
Authors: Giorgio Bagarella; Mauro Maistrello; Maddalena Minoja; Olivia Leoni; Francesco Bortolan; Danilo Cereda; Giovanni Corrao Journal: Int J Environ Res Public Health Date: 2022-09-28 Impact factor: 4.614