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Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies

Based on the medical waste quantity and patient data during the corona virus disease 2019 (COVID-19) outbreak in China, this study used scenario analysis to quantitatively analyze the temporal and spatial evolution of medical waste generation during the pandemics. First, the results show that the es...

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Autores principales: Wang, Fang, Yu, Lean, Long, Junhong, Bu, Haoyue, He, Changhua, Wu, Aiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Japan 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589721/
https://www.ncbi.nlm.nih.gov/pubmed/36310674
http://dx.doi.org/10.1007/s10163-022-01523-5
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author Wang, Fang
Yu, Lean
Long, Junhong
Bu, Haoyue
He, Changhua
Wu, Aiping
author_facet Wang, Fang
Yu, Lean
Long, Junhong
Bu, Haoyue
He, Changhua
Wu, Aiping
author_sort Wang, Fang
collection PubMed
description Based on the medical waste quantity and patient data during the corona virus disease 2019 (COVID-19) outbreak in China, this study used scenario analysis to quantitatively analyze the temporal and spatial evolution of medical waste generation during the pandemics. First, the results show that the estimated medical waste per capita reached 15.4 kg/day if only patients were considered in Scenario 1, while the figures were reduced to 3.2 kg/day in Scenario 2 and 2.5 kg/day in Scenario 3 when the effects of both the patient type and the number of medical staffs were considered. The estimated results also demonstrated that the per capita medical waste related to the epidemic showed the characteristics of a U-shaped and trailing phenomenon over time. Then, the amount of medical waste related to the COVID-19 generated that generated due to COVID-19 was estimated in Hubei, Heilongjiang, Zhejiang, Henan and Hunan provinces under Scenario 2 and Scenario 3. The results indicated that the spatiotemporal evolution characteristics of five provinces show the significant differences, and the patient type has a remarkable influence on the generation of medical waste. Finally, a novel decomposition-ensemble approach was designed to make a better short-term forecasting effect for future medical waste generation in different provinces. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10163-022-01523-5.
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spelling pubmed-95897212022-10-24 Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies Wang, Fang Yu, Lean Long, Junhong Bu, Haoyue He, Changhua Wu, Aiping J Mater Cycles Waste Manag Original Article Based on the medical waste quantity and patient data during the corona virus disease 2019 (COVID-19) outbreak in China, this study used scenario analysis to quantitatively analyze the temporal and spatial evolution of medical waste generation during the pandemics. First, the results show that the estimated medical waste per capita reached 15.4 kg/day if only patients were considered in Scenario 1, while the figures were reduced to 3.2 kg/day in Scenario 2 and 2.5 kg/day in Scenario 3 when the effects of both the patient type and the number of medical staffs were considered. The estimated results also demonstrated that the per capita medical waste related to the epidemic showed the characteristics of a U-shaped and trailing phenomenon over time. Then, the amount of medical waste related to the COVID-19 generated that generated due to COVID-19 was estimated in Hubei, Heilongjiang, Zhejiang, Henan and Hunan provinces under Scenario 2 and Scenario 3. The results indicated that the spatiotemporal evolution characteristics of five provinces show the significant differences, and the patient type has a remarkable influence on the generation of medical waste. Finally, a novel decomposition-ensemble approach was designed to make a better short-term forecasting effect for future medical waste generation in different provinces. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10163-022-01523-5. Springer Japan 2022-10-21 2023 /pmc/articles/PMC9589721/ /pubmed/36310674 http://dx.doi.org/10.1007/s10163-022-01523-5 Text en © Springer Japan KK, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Article
Wang, Fang
Yu, Lean
Long, Junhong
Bu, Haoyue
He, Changhua
Wu, Aiping
Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
title Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
title_full Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
title_fullStr Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
title_full_unstemmed Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
title_short Quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
title_sort quantifying the spatiotemporal evolution characteristics of medical waste generation during the outbreak of public health emergencies
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589721/
https://www.ncbi.nlm.nih.gov/pubmed/36310674
http://dx.doi.org/10.1007/s10163-022-01523-5
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