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COVID-19: Review of Data Analysis

Authors:
Anthony Dias
Cristiana Barata
Filipe Fidalgo
Ângela Oliveira

Keywords: PRISMA; literature review; Covid-19; prediction; SIR

Abstract:
The first infection caused by Covid-19 appeared in December 2019 and has infected about 250 million people since. In pandemics, it is essential to model propagation so that it is possible to know how to act to avoid a significant public health problem. Since the appearance of Covid-19, mathematicians, scientists, physicians, and engineers have cooperated in data analysis. This study aims to understand which mathematical models are more relevant and used in this context. Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, we will analyse Covid-19 related articles, meeting the results in predicting this pandemic in Portugal and worldwide. All the articles chosen use models or algorithms to perform prediction, and we conclude that the Susceptible-Infected-Recovered (SIR) model was the most appropriate and the most used. All the articles have been published up to April 2021.

Pages: 5 to 10

Copyright: Copyright (c) IARIA, 2022

Publication date: October 16, 2022

Published in: conference

ISSN: 2519-8491

ISBN: 978-1-68558-004-9

Location: Lisbon, Portugal

Dates: from October 16, 2022 to October 20, 2022