The Impact of Air Quality and Meteorology on COVID-19 Cases at Kuala Lumpur and Selangor, Malaysia and Prediction Using Machine Learning
Juliana Jalaludin, Wan Nurdiyana Wan Mansor, Nur Afizan Abidin, Nur Faseeha Suhaimi, How-Ran Chao
Atmosphere, doi:10.3390/atmos14060973
Emissions from motor vehicles and industrial sources have contributed to air pollution worldwide. The effect of chronic exposure to air pollution is associated with the severity of the COVID-19 infection. This ecological investigation explored the relationship between meteorological parameters, air pollutants, and COVID-19 cases among residents in Selangor and Kuala Lumpur between 18 March and 1 June in the years 2019 and 2020. The air pollutants considered in this study comprised particulate matter (PM 2.5 , PM 10 ), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ), and carbon monoxide (CO), whereas wind direction (WD), ambient temperature (AT), relative humidity (RH), solar radiation (SR), and wind speed (WS) were analyzed for meteorological information. On average, air pollutants demonstrated lower concentrations than in 2019 for both locations except PM 2.5 in Kuala Lumpur. The cumulative COVID-19 cases were negatively correlated with SR and WS but positively correlated with O 3 , NO 2 , RH, PM 10 , and PM 2.5 . Overall, RH (r = 0.494; p < 0.001) and PM 2.5 (r = -0.396, p < 0.001) were identified as the most significant parameters that correlated positively and negatively with the total cases of COVID-19 in Kuala Lumpur and Selangor, respectively. Boosted Trees (BT) prediction showed that the optimal combination for achieving the lowest Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Error (MAE) and a higher R-squared (R 2 ) correlation between actual and predicted COVID-19 cases was achieved with a learning rate of 0.2, a minimum leaf size of 7, and 30 learners. The model yielded an R 2 value of 0.81, a RMSE of 0.44, a MSE of 0.19, and a MAE of 0.35. Using the BT predictive model, the number of COVID-19 cases in Selangor was projected with an R 2 value of 0.77. This study aligns with the existing notion of connecting meteorological factors and chronic exposure to airborne pollutants with the incidence of COVID-19. Integrated governance for holistic approaches would be needed for air quality management post-COVID-19 in Malaysia.
Author Contributions: Conceptualization, J.J.; methodology, J.J. and N.F.S.; software, J.J.; & W.N.W.M.; validation, J.J.; N.F.S., and N.A.A.; formal analysis, J.J.; N.F.S. and W.N.W.M.; investigation, J.J. and N.A.A.; resources, J.J.; data curation, J.J.; N.F.S. writing-original draft preparation, J.J., N.F.S. and N.A.A.; writing-review and editing, J.J. & H.-R.C.; visualization, J.J. & W.N.W.M.; supervision, J.J. project administration, J.J.; funding acquisition, J.J. All authors have read and agreed to the published version of the manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
References
Abdelhafez, Dabbour, Hamdan, The Effect of Weather Data on the Spread of COVID-19 in Jordan, Environ. Sci. Pollut. Res,
doi:10.1007/s11356-020-12338-y
Abdullah, Ismail, Fong, Multiple Linear Regression (MLR) Models for Long Term PM10 Concentration Forecasting During Different Monsoon Seasons, J. Sustain. Sci. Manag
Abdullah, Mansor, Napi, Mansor, Ahmed et al., Air Quality Status during 2020 Malaysia Movement Control Order (MCO) Due To 2019 Novel Coronavirus (2019-NCoV) Pandemic, Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.139022
Abdullah, Napi, Ahmed, Mansor, Mansor et al., Development of Multiple Linear Regression for Particulate Matter (PM10) Forecasting during Episodic Transboundary Haze Event in Malaysia,
doi:10.3390/atmos11030289
Abdulrahman, Ibrahim, Gital, Zambuk, Ja Afaru et al., A Review on Deep Learning with Focus on Deep Recurrent Neural Network for Electricity Forecasting in Residential Building, Procedia Comput. Sci,
doi:10.1016/j.procs.2021.10.014
Al Alkeem, Kim, Yeun, Zemerly, Poon et al., An Enhanced Electrocardiogram Biometric Authentication System Using Machine Learning, IEEE Access,
doi:10.1109/ACCESS.2019.2937357
Alkhowailed, Shariq, Alqossayir, Alzahrani, Rasheed et al., Impact of Meteorological Parameters on COVID-19 Pandemic: A Comprehensive Study from Saudi Arabia: Impact of Weather on COVID-19, Inform. Med. Unlocked,
doi:10.1016/j.imu.2020.100418
Arphorn, Ishimaru, Hara, Mahasandana, Considering the Effects of Ambient Particulate Matter on The Lung Function of Motorcycle Taxi Drivers in Bangkok, Thailand. J. Air Waste Manag. Assoc,
doi:10.1080/10962247.2017.1359217
Awang, Elbayoumi, Ramli, Yahaya, Diurnal Variations of Ground-Level Ozone in Three Port Cities in Malaysia, Air Qual. Atmos. Health,
doi:10.1007/s11869-015-0334-7
Awang, Ramli, Yahaya, Elbayoumi, Multivariate Methods to Predict Ground Level Ozone During Daytime, Nighttime, and Critical Conversion Time in Urban Areas, Atmos. Pollut. Res,
doi:10.5094/APR.2015.081
Banan, Latif, Juneng, Ahamad, Characteristics of Surface Ozone Concentrations at Stations with Different Backgrounds in the Malaysian Peninsula, Aerosol Air Qual. Res,
doi:10.4209/aaqr.2012.09.0259
Bashir, Ma, Bilal; Komal, Bashir, Farooq et al., Correlation between Environmental Pollution Indicators and COVID-19 Pandemic: A Brief Study in Californian Context, Environ. Res,
doi:10.1016/j.envres.2020.109652
Bouabdallaoui, Lafhaj, Yim, Ducoulombier, Bennadji, Predictive Maintenance in Building Facilities: A Machine Learning-Based Approach, Sensors,
doi:10.3390/s21041044
Cdc, Symptoms of Coronavirus
Chan, Peiris, Lam, Poon, Yuen et al., The Effects of Temperature and Relative Humidity on the Viability of the SARS Coronavirus, Adv. Virol,
doi:10.1155/2011/734690
Chen, Liang, Yuan, Hu, Xu et al., Roles of Meteorological Conditions in COVID-19 Transmission on a Worldwide Scale, BMJ Open,
doi:10.1101/2020.03.16.20037168
Chicco, Warrens, Jurman, The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation, PeerJ Comput. Sci,
doi:10.7717/peerj-cs.623
Clouston, Morozova, Meliker, A Wind Speed Threshold for Increased Outdoor Transmission of Coronavirus: An Ecological Study, BMC Infect. Dis,
doi:10.1186/s12879-021-06796-z
Conticini, Frediani, Caro, Can Atmospheric Pollution Be Considered a Co-Factor in Extremely High Level of SARS-CoV-2 Lethality in Northern Italy?, Environ. Pollut,
doi:10.1016/j.envpol.2020.114465
Dantas, Siciliano, França, Da Silva, Arbilla, The Impact of COVID-19 Partial Lockdown on the Air Quality of the City of Rio de Janeiro, Brazil. Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.139085
Fang, Xiao, Sun, Liu, Zhang et al., Characteristics of Ground-Level Ozone from 2015 to 2018 in BTH Area, China. Atmosphere,
doi:10.3390/atmos11020130
Fehr, Perlman, Coronaviruses: An Overview of Their Replication and Pathogenesis
Frontera, Cianfanelli, Vlachos, Landoni, Cremona, Severe Air Pollution Links to Higher Mortality in COVID-19 Patients: The "Double-Hit" Hypothesis, J. Infect,
doi:10.1016/j.jinf.2020.05.031
Gautam, Samuel, Gautam, Kumar, Strong Link between Coronavirus Count and Bad Air: A Case Study of India, Environ. Dev. Sustain,
doi:10.1007/s10668-021-01366-4
Genc, Zadeoglulari, Fuss, Genc, The Adverse Effects of Air Pollution on the Nervous System, J. Toxicol,
doi:10.1155/2012/782462
Grimaldo, Novak, Combining Machine Learning with Visual Analytics for Explainable Forecasting of Energy Demand in Prosumer Scenarios, Procedia Comput. Sci,
doi:10.1016/j.procs.2020.07.074
Jiang, Wu, Guan, Effect of Ambient Air Pollutants and Meteorological Variables on COVID-19 Incidence, Infect. Control Hosp. Epidemiol,
doi:10.1017/ice.2020.222
Kim, Yeun, Yoo, An Enhanced Machine Learning-Based Biometric Authentication System Using RR-Interval Framed Electrocardiograms, IEEE Access,
doi:10.1109/ACCESS.2019.2954576
Latif, Dominick, Ahamad, Khan, Juneng et al., Long Term Assessment of Air Quality from a Background Station on the Malaysian Peninsula, Sci. Total Environ,
doi:10.1016/j.scitotenv.2014.02.132
Lefohn, Malley, Simon, Wells, Xu et al., Responses of Human Health and Vegetation Exposure Metrics to Changes in Ozone Concentration Distributions in the European Union, United States, and China, Atmos. Environ,
doi:10.1016/j.atmosenv.2016.12.025
Liu, Zhou, Yao, Zhang, Li et al., Impact of Meteorological Factors on the COVID-19 Transmission: A Multi-City Study in China, Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.138513
Ma, Pei, Shaman, Dubrow, Chen, Role of Meteorological Factors in the Transmission of SARS-CoV-2 in the United States, Nat. Commun. 2021,
doi:10.1038/s41467-021-23866-7
Ma, Zhao, Liu, He, Wang et al., Effects of Temperature Variation and Humidity on the Death of COVID-19 in Wuhan, China. Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.138226
Manisalidis, Stavropoulou, Stavropoulos, Bezirtzoglou, Environmental and Health Impacts of Air Pollution: A Review, Front. Public Health,
doi:10.3389/fpubh.2020.00014
Mohd Nadzir, Ooi, Alhasa, Abu Bakar, Ahmad Mohtar et al., The Impact of Movement Control Order (MCO) during Pandemic COVID-19 on Local Air Quality in an Urban Area of Klang Valley, Malaysia. Aerosol Air Qual. Res,
doi:10.4209/aaqr.2020.04.0163
Nurdiyana Wan Mansor, Abdullah, Ashraf Razali, Albani, Ramli et al., Prediction of Emissions of a Dual Fuel Engine with Artificial Neural Network (ANN)
Otmani, Benchrif, Tahri, Bounakhla, Chakir et al., Impact of Covid-19 Lockdown on PM10, SO2 and NO2 Concentrations in Salé City (Morocco), Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.139541
Paital, Agrawal, Air Pollution by NO 2 and PM2.5 Explains COVID-19 Infection Severity by Overexpression of Angiotensin-Converting Enzyme 2 in Respiratory Cells: A Review, Environ. Chem. Lett,
doi:10.1007/s10311-020-01091-w
Paoletti, De Marco, Beddows, Harrison, Manning, Ozone Levels in European and USA Cities Are Increasing More than at Rural Sites, While Peak Values Are Decreasing, Environ. Pollut,
doi:10.1016/j.envpol.2014.04.040
Rachman, Santoso, Djajadi, Machine Learning Mini Batch K-Means and Business Intelligence Utilization for Credit Card Customer Segmentation, Int. J. Adv. Comput. Sci. Appl. 2021,
doi:10.14569/IJACSA.2021.0121024
Razali, Shamsaimon, Ishak, Ramli, Amran et al., Techniques and Evaluation: Traffic Flow Prediction Using Machine Learning and Deep Learning, J. Big Data,
doi:10.1186/s40537-021-00542-7
Rudke, De Almeida, Alves, Beal, Martins et al., Impacts of Strategic Mobility Restrictions Policies during 2020 COVID-19 Outbreak on Brazil's Regional Air Quality, Aerosol Air Qual. Res,
doi:10.4209/aaqr.210351
Sahoo, Mangla, Pathak, Salãmao, Sarkar, Pre-to-Post Lockdown Impact on Air Quality and The Role of Environmental Factors in Spreading the COVID-19 Cases-A Study from A Worst-Hit State of India, Int. J. Biometeorol,
doi:10.1007/s00484-020-02019-3
Sahoo, Powell, Mittal, Garg, Is the Transmission of Novel Coronavirus Disease (COVID-19) Weather Dependent?, J. Air Waste Manag. Assoc,
doi:10.1080/10962247.2020.1823763
Sangkham, Thongtip, Vongruang, Influence of Air Pollution and Meteorological Factors on the Spread of COVID-19 in the Bangkok Metropolitan Region and Air Quality during the Outbreak, Environ. Res,
doi:10.1016/j.envres.2021.111104
Stirnberg, Cermak, Fuchs, Andersen, Mapping and Understanding Patterns of Air Quality Using Satellite Data and Machine Learning, J. Geophys. Res. Atmos,
doi:10.1029/2019JD031380
Suhaimi, Jalaludin, Latif, Demystifying A Possible Relationship between COVID-19, Air Quality and Meteorological Factors: Evidence from Kuala Lumpur, Malaysia. Aerosol Air Qual. Res,
doi:10.4209/aaqr.2020.05.0218
Tiwari, Dahiya, Kumar, Investigation into Relationships among NO, NO 2 , NOx, O 3 , and CO at an Urban Background Site in Delhi, India. Atmos. Res,
doi:10.1016/j.atmosres.2015.01.008
Tobías, Carnerero, Reche, Massagué, Via et al., Changes in Air Quality During the Lockdown in Barcelona (Spain) One Month into The SARS-CoV-2 Epidemic, Sci. Total Environ
Tsai, Riediker, Berchet, Paccaud, Waeber et al., Effects of Short-and Long-Term Exposures to Particulate Matter on Inflammatory Marker Levels in the General Population, Environ. Sci. Pollut. Res,
doi:10.1007/s11356-019-05194-y
Usmani, Saeed, Abdullahi, Pillai, Jhanjhi et al., Air Pollution and Its Health Impacts in Malaysia: A Review, Air Qual. Atmos. Health,
doi:10.1007/s11869-020-00867-x
Van Doremalen, Bushmaker, Munster, Stability of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) under Different Environmental Conditions. Eurosurveillance,
doi:10.2807/1560-7917.ES2013.18.38.20590
Varad, Thalkar Customer Segmentation Using Machine Learning, Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol
Wang, Ying, Hu, Zhang, Spatial and Temporal Variations of Six Criteria Air Pollutants in 31 Provincial Capital Cities in China during 2013-2014, Environ. Int,
doi:10.1016/j.envint.2014.08.016
Waring, Lindvall, Umeton, Automated Machine Learning: Review of the State-of-the-Art and Opportunities for Healthcare, Artif. Intell. Med,
doi:10.1016/j.artmed.2020.101822
Who, Coronavirus Disease (COVID-19
Wu, Jing, Liu, Ma, Yuan et al., Effects of Temperature and Humidity on The Daily New Cases and New Deaths of COVID-19 in 166 Countries, Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.139051
Wu, Mcgoogan, Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72314 Cases from the Chinese Center for Disease Control and Prevention, JAMA-J. Am. Med. Assoc,
doi:10.1001/jama.2020.2648
Zaręba, Danek, Analysis of Air Pollution Migration during COVID-19 Lockdown in Krakow, Poland. Aerosol Air Qual. Res,
doi:10.4209/aaqr.210275
Zhu, Xie, Huang, Cao, Association between Short-Term Exposure to Air Pollution and COVID-19 Infection: Evidence from China, Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.138704
Zoran, Savastru, Savastru, Tautan, Assessing the Relationship between Surface Levels of PM2.5 and PM10 Particulate Matter Impact on COVID-19 in, Sci. Total Environ,
doi:10.1016/j.scitotenv.2020.139825