Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)

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Analyses of Factors Affecting Deaths Associated with COVID-19 in Ontario

Authors
Jie Huang1, *
1University of Toronto, 27 King’s College Cir, M5S 1A1, Toronto, Ontario
*Corresponding author. Email: jieh.huang@mail.utoronto.ca
Corresponding Author
Jie Huang
Available Online 29 December 2022.
DOI
10.2991/978-94-6463-042-8_186How to use a DOI?
Keywords
COVID-19; Mortality; Time Series; Logistic Regression; Vaccination
Abstract

Since the outbreak of the COVID-19 in 2019, it has been a great challenge for the whole world. When the epidemic is serious and the vaccine will play a role, the statistic is an effective tool. It can help the government collect various data and conduct modelling analysis, so that it can face the actual situation and issue appropriate policies. This paper aims to analyse the factors that could affect the death rates among all COVID-19 confirmed cases in Ontario. Specifically, Seasonal ARIMA is used to fit past one-year data to predict short-term trend of confirmed case. An overall upward slope is predicted by selected time series model. Logistic regression is then used to determine how age group and vaccination could affect the mortality risk quantitatively. According to the information as of November 6, 2021, the forecast trend in the short term is expected to show an upward trend. In addition, age group and vaccination status significantly affect the probability of death of confirmed cases. The mortality increased with age. It has also been proved that the mortality of fully vaccinated patients is lower than that of partially vaccinated patients, followed by unvaccinated patients.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
Series
Advances in Computer Science Research
Publication Date
29 December 2022
ISBN
978-94-6463-042-8
ISSN
2352-538X
DOI
10.2991/978-94-6463-042-8_186How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jie Huang
PY  - 2022
DA  - 2022/12/29
TI  - Analyses of Factors Affecting Deaths Associated with COVID-19 in Ontario
BT  - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
PB  - Atlantis Press
SP  - 1294
EP  - 1300
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-042-8_186
DO  - 10.2991/978-94-6463-042-8_186
ID  - Huang2022
ER  -