Predictive Research on COVID-19 using the Compartmental Model

Haotian Guo

2021

Abstract

Compartmental models appeared in our field of vision in the early 20th century, with the contributions mainly of Ronald Ross, Hilda Hudson, David Kendall and other scientists. These models turned out to be one of the most important techniques to model real world issues and to provide most of the answers that people seek. In epidemiology, in particular, these are the essential modeling techniques to the modeling of infectious diseases. Compartmental models have helped epidemiologists solve problems like the initial spread of the disease, the number of people infected, and the level of risk the disease would bring to people. In the early 2019, a highly infectious kind of pneumonia, later named COVID-19 by the World Health Organization, was firstly discovered in China, and later the doctors and epidemiologists would find out that this disease was actually due to a new kind of virus that had never been studied or seen before. In study this “new” virus, epidemiologists revealed to us how important and effective compartmental models can be even when dealing with a virus that scientists did not have full knowledge on its properties. For this project, several models were also developed with the toll of compartmental model based on the data extracted from the website of the World Health Organization of the spread of COVID-19 in countries like Vietnam, Spain, and the United States of America. The goal was trying to do was to simulate the spread of the data and predict the trend of the spread in such countries. Based on the analysis, it’s concluded that COVID may be still prevalent in countries like these for a very long period of time, and because of that, there is a possibility that COVID may never end worldwide.

Paper Citation

in Harvard Style

Guo H. (2021). Predictive Research on COVID-19 using the Compartmental Model. In Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA, ISBN 978-989-758-589-0, pages 187-190. DOI: 10.5220/0011154000003437

in Bibtex Style

@conference{pmbda21,
author={Haotian Guo},
title={Predictive Research on COVID-19 using the Compartmental Model},
booktitle={Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA,},
year={2021},
pages={187-190},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011154000003437},
isbn={978-989-758-589-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA,
TI - Predictive Research on COVID-19 using the Compartmental Model
SN - 978-989-758-589-0
AU - Guo H.
PY - 2021
SP - 187
EP - 190
DO - 10.5220/0011154000003437