Identifying Demographic Factors Attributed to the Infection Rate of Covid-19 in Malaysia

DOI

10.2991/978-94-6463-094-7_8How to use a DOI?

Keywords

Demographic factors; COVID-19; Boruta attribute selection; Regression models

Abstract

Since 2020, the Covid-19 pandemic has spread like wildfire across many countries, including Malaysia. The disease has caused disastrous impacts on the country’s economy, public health system, and the livelihoods of its citizens. Hence, there is an urgent need to investigate and determine the underlying factors attributed to the high infection rate of Covid-19. This research aims to study and identify demographic factors attributed to the high infection rate of Covid-19 in Malaysia using regression models. The preliminary results show that the labour force participation rate, unemployment rate, and average household income contribute to Malaysia’s high COVID-19 infection rates.

Copyright

© 2022 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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TY  - CONF
AU  - Jun-Ting Chan
AU  - Keng-Hoong Ng
AU  - Gee-Kok Tong
AU  - Choo-Yee Ting
AU  - Kok-Chin Khor
PY  - 2022
DA  - 2022/12/27
TI  - Identifying Demographic Factors Attributed to the Infection Rate of Covid-19 in Malaysia
BT  - Proceedings of the International Conference on Computer, Information Technology and Intelligent Computing (CITIC 2022)
PB  - Atlantis Press
SP  - 92
EP  - 103
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-094-7_8
DO  - 10.2991/978-94-6463-094-7_8
ID  - Chan2022
ER  -