System dynamics approach for the relationship between different types of hospitals and hospital waste management (case study: Tabriz)

Musavi, Seyed Mehdi; Khosropour, Reza; Musavi, Seyed Abolfazl; Ahmadvand, A M

doi:10.1504/pie.2019.098765

Cited by 4 publications

(4 citation statements)

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“…Big data and other data-driven statistical modeling methods can be used to analyze extensive biological data from hospitals, healthcare facilities, and pharmaceutical industries by integrating artificial intelligence with computational methods ( Chowdhury et al, 2020 ; Musavi et al, 2019 ; Romero et al, 2017 ). Assessment of the risk related to the presence of dangerous chemicals in the environment is both important and difficult.…”

Section: Computational Modelingmentioning

confidence: 99%

“…Computational methods have been used for analyzing data sets that are too large or complex for traditional data-processing application software to handle. Researchers have successfully implemented big data tools and computational technologies to address issues in the water and wastewater utility sector ( Choudhury et al, 2021 ; Chowdhury et al, 2010 ; Musavi et al, 2019 ; Romero et al, 2017 ).…”

Section: Computational Modelingmentioning

confidence: 99%

“…Systems dynamics modeling, in combination with experimental computer design and statistical analysis, can provide quick and quantitative results for decision-making ( Fair et al, 2021 ; Jia et al, 2021 ). Recently, Musavi et al (2019) evaluated the performance of a system dynamics model by using “Vensim” software for the future prediction of different categories of waste produced from different hospitals of Iran. The fundamental modeling part of the software is an appropriate simulation of stock and flow diagrams.…”

Section: Computational Modelingmentioning

confidence: 99%

“…The obtained model effectively overcame the prediction problems using dynamic simulation modeling with only partially available information. The model predicts the quantity of each type of waste produced based on the type of hospital, making it easier for stakeholders and government officials to find ways to reduce the negative effects of such wastes on human health and the environment ( Musavi et al, 2019 ).…”

Section: Computational Modelingmentioning

confidence: 99%

See 3 more Smart Citations

An assessment of hospital wastewater and biomedical waste generation, existing legislations, risk assessment, treatment processes, and scenario during COVID-19

Parida

Sikarwar

Majumder

et al. 2022

Journal of Environmental Management

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Hospitals release significant quantities of wastewater (HWW) and biomedical waste (BMW), which hosts a wide range of contaminants that can adversely affect the environment if left untreated. The COVID-19 outbreak has further increased hospital waste generation over the past two years. In this context, a thorough literature study was carried out to reveal the negative implications of untreated hospital waste and delineate the proper ways to handle them. Conventional treatment methods can remove only 50%–70% of the emerging contaminants (ECs) present in the HWW. Still, many countries have not implemented suitable treatment methods to treat the HWW in-situ. This review presents an overview of worldwide HWW generation, regulations, and guidelines on HWW management and highlights the various treatment techniques for efficiently removing ECs from HWW. When combined with advanced oxidation processes, biological or physical treatment processes could remove around 90% of ECs. Analgesics were found to be more easily removed than antibiotics, β-blockers, and X-ray contrast media. The different environmental implications of BMW have also been highlighted. Mishandling of BMW can spread infections, deadly diseases, and hazardous waste into the environment. Hence, the different steps associated with collection to final disposal of BMW have been delineated to minimize the associated health risks. The paper circumscribes the multiple aspects of efficient hospital waste management and may be instrumental during the COVID-19 pandemic when the waste generation from all hospitals worldwide has increased significantly.

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Section: Computational Modelingmentioning

confidence: 99%