Sustainable Ambient Environment to Prevent Future Outbreaks: How Ambient Environment Relates to COVID-19 Local Transmission in Lima, Peru

Tsai-Chi Kuo, Ana Maria Pacheco, Aditya Prana Iswara, Denny Dermawan, Gerry Andhikaputra and Lin-Han Chiang Hsieh
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Tsai-Chi Kuo: Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
Ana Maria Pacheco: Department of Environmental Engineering, College of Engineering, Chung Yuan Christian University, 200 Chung-Pei Road, Zhongli 320, Taiwan
Aditya Prana Iswara: Department of Environmental Engineering, College of Engineering, Chung Yuan Christian University, 200 Chung-Pei Road, Zhongli 320, Taiwan
Denny Dermawan: Department of Waste Treatment Engineering, Shipbuilding Institute of Polytechnic Surabaya, Sukolilo 60111, Indonesia
Gerry Andhikaputra: Department of Environmental Engineering, College of Engineering, Chung Yuan Christian University, 200 Chung-Pei Road, Zhongli 320, Taiwan
Lin-Han Chiang Hsieh: Department of Environmental Engineering, College of Engineering, Chung Yuan Christian University, 200 Chung-Pei Road, Zhongli 320, Taiwan

Sustainability, 2020, vol. 12, issue 21, 1-13

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), universally recognized as COVID-19, is currently is a global issue. Our study uses multivariate regression for determining the relationship between the ambient environment and COVID-19 cases in Lima. We also forecast the pattern trajectory of COVID-19 cases with variables using an Auto-Regressive Integrated Moving Average Model (ARIMA). There is a significant association between ambient temperature and PM 10 and COVID-19 cases, while no significant correlation has been seen for PM 2.5 . All variables in the multivariate regression model have R 2 = 0.788, which describes a significant exposure to COVID-19 cases in Lima. ARIMA (1,1,1), during observation time of PM 2.5 , PM 10 , and average temperature, is found to be suitable for forecasting COVID-19 cases in Lima. This result indicates that the expected high particle concentration and low ambient temperature in the coming season will further facilitate the transmission of the coronavirus if there is no other policy intervention. A suggested sustainable policy related to ambient environment and the lessons learned from different countries to prevent future outbreaks are also discussed in this study.

Keywords: COVID-19; correlation; forecasting; ambient temperature; PM 2.5; PM 10 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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