Your browser doesn't support javascript.
loading
Predictions of PM2.5 using air pollutants and meteorological factors with COVID-19 cases in Malaysia and Indonesia: a comparative study using feature selection and robust regression.
Salsabila, Norin Binta; Jalaludin, Juliana; Suhaimi, Nur Faseeha; Wan Mansor, Wan Nurdiyana; Sumantri, Arif.
Afiliação
  • Salsabila NB; Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia.
  • Jalaludin J; Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia.
  • Suhaimi NF; Department of Environmental and Occupational Health, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Serdang, Malaysia.
  • Wan Mansor WN; Faculty of Ocean Engineering Technology, Universiti Malaysia Terengganu, Kuala Nerus, Malaysia.
  • Sumantri A; Study Program of Public Health, Health Science Faculty, State Islamic University (UIN), Syarif Hidayatullah Jakarta, Indonesia.
Int J Environ Health Res ; : 1-22, 2024 Aug 13.
Article em En | MEDLINE | ID: mdl-39135511
ABSTRACT
The study examines the relationship between air quality, meteorological factors, and COVID-19 cases in Cheras, Kuala Lumpur, and Kelapa Gading, North Jakarta. Analyzing data from 2020 and 2021, the research found notable correlations COVID-19 cases in Cheras were positively associated with relative humidity (RH) and carbon monoxide (CO) but negatively with ozone (O3) and RH in different years. In Kelapa Gading, COVID-19 cases were positively correlated with pollutants like sulfur dioxide (SO2) and CO, while ambient temperature (AT) showed a negative correlation. The enforcement of social restrictions notably reduced air pollution, affecting COVID-19 spread. Predictive models for PM2.5 levels using robust regression techniques showed strong performance in Kuala Lumpur (R² > 0.9) but exhibited overfitting tendencies in Jakarta, suggesting the need for a longer study period for more accurate results.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article