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Assessment of medical waste generation, associated environmental impact, and management issues after the outbreak of COVID-19: A case study of the Hubei Province in China.
Ye, Jinquan; Song, Yifan; Liu, Yurong; Zhong, Yun.
  • Ye J; School of Management, Nanchang University, Nanchang, 330031, PR China.
  • Song Y; Ji luan Academy, Nanchang University, Nanchang, 330031, PR China.
  • Liu Y; School of Economics and Management, Nanchang University, Nanchang, 330031, PR China.
  • Zhong Y; Ji luan Academy, Nanchang University, Nanchang, 330031, PR China.
PLoS One ; 17(1): e0259207, 2022.
Article in English | MEDLINE | ID: covidwho-1648363
ABSTRACT
COVID-19 greatly challenges the human health sector, and has resulted in a large amount of medical waste that poses various potential threats to the environment. In this study, we compiled relevant data released by official agencies and the media, and conducted data supplementation based on earlier studies to calculate the net value of medical waste produced in the Hubei Province due to COVID-19 with the help of a neural network model. Next, we reviewed the data related to the environmental impact of medical waste per unit and designed four scenarios to estimate the environmental impact of new medical waste generated during the pandemic. The results showed that a medical waste generation rate of 0.5 kg/bed/day due to COVID-19 resulted in a net increase of medical waste volume by about 3366.99 tons in the Hubei Province. In the four scenario assumptions, i.e., if the medical waste resulting from COVID-19 is completely incinerated, it will have a large impact on the air quality. If it is disposed by distillation sterilization, it will produce a large amount of wastewater and waste residue. Based on the results of the study, we propose three policy

recommendations:

strict control of medical wastewater discharge, reduction and transformation of the emitted acidic gases, and attention to the emission of metallic nickel in exhaust gas and chloride in soil. These policy recommendations provide a scientific basis for controlling medical waste pollution.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Neural Networks, Computer / Waste Management / Air Pollution / Environmental Pollution / Wastewater / COVID-19 / Medical Waste Type of study: Case report / Experimental Studies / Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Neural Networks, Computer / Waste Management / Air Pollution / Environmental Pollution / Wastewater / COVID-19 / Medical Waste Type of study: Case report / Experimental Studies / Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2022 Document Type: Article