Classification of community-acquired outbreaks for the global transmission of COVID-19: Machine learning and statistical model analysis

• Main Authors: Wang, Wei-Chun, Lin, Ting-Yu, Chiu, Sherry Yueh-Hsia, Chen, Chiung-Nien, Pongdech Sarakarn, Mohd Yusof Hj Ibrahim, Chen, Sam Li-Sheng, Chen, Hsiu-Hsi, Yeh, Yen-Po
• Format: Article
• Language: English; English
• Published: Elsevier 2021
• Subjects: HB135-147 Mathematical economics. Quantitative methods Including econometrics, input-output analysis, game theory; RA1-1270 Public aspects of medicine
• Online Access: https://eprints.ums.edu.my/id/eprint/32677/1/Classification%20of%20community-acquired%20outbreaks%20for%20the%20global%20transmission%20of%20COVID-19_%20Machine%20learning%20and%20statistical%20model%20analysis.pdf; https://eprints.ums.edu.my/id/eprint/32677/3/Classification%20of%20community-acquired%20outbreaks%20for%20the%20global%20transmission%20of%20COVID-19_%20Machine%20learning%20and%20statistical%20model%20analysis%20_ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/32677/; https://www.sciencedirect.com/science/article/pii/S0929664621002230; https://doi.org/10.1016/j.jfma.2021.05.010
• Institution: Universiti Malaysia Sabah

Background: As Coronavirus disease 2019 (COVID-19) pandemic led to the unprecedent largescale repeated surges of epidemics worldwide since the end of 2019, data-driven analysis to look into the duration and case load of each episode of outbreak worldwide has been motivated. Methods: Using open data...