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

• Published in: Journal of material cycles and waste management Vol. 25; no. 1; pp. 221 - 234
• Main Authors: Wang, Fang, Yu, Lean, Long, Junhong, Bu, Haoyue, He, Changhua, Wu, Aiping
• Format: Journal Article
• Language: English
• Published: Tokyo Springer Japan 01.01.2023; Springer Nature B.V
• Subjects: Civil Engineering; Coronaviruses; COVID-19; Emergency medical services; Engineering; Environmental Management; Epidemics; Evolution; Medical wastes; Original; Original Article; Outbreaks; Pandemics; Public health; Viral diseases; Waste Management/Waste Technology; COVID-19; Decomposition-ensemble approach; Scenario analysis; Per capita medical waste; Public health emergencies; Medical waste
• ISSN: 1438-4957; 1611-8227
• DOI: 10.1007/s10163-022-01523-5

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.