EXPLORATION OF DISTRICT-WISE COVID-19 SPREAD IN SARAWAK USING GEOGRAPHICALLY WEIGHTED REGRESSION (GWR)

• Main Author: Fiona, Teu Pui Jun
• Format: Final Year Project Report
• Language: English
• Published: Universiti Malaysia Sarawak, (UNIMAS) 2023
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://ir.unimas.my/id/eprint/44148/1/Fiona%20Teu%20Pui%20Jun%20%20ft.pdf; http://ir.unimas.my/id/eprint/44148/

In the year 2020, the COVID-19 outbreak was well-controlled in the Malaysian state of Sarawak. However, there was a surge in positive cases that began in January 2021 and affected all districts, including rural areas with limited health care. Because COVID-19 is extremely dangerous to human health, it is critical to investigate the spreading pattern at the district level. The COVID�19 socio-demographic factor is captured and extracted using Principal Component Analysis (PCA). The dependent variable in this study is COVID-19 cumulative cases and incidence rate while the independent variable is the socio-demographic factors. Because dispersion occurs at different gradient levels across geographies, the Geographically Weighted Regression (GWR) model is used in this study to investigate the relationship between socio-demographic and district-level COVID�19 cases. The finding in this study reveals that there is significant spatial and temporal variation in the spread of COVID-19 across the districts of Sarawak by using GWR. Two independent variables (pop_density and pop_0_14) influence most positively to COVID-19 cases.