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The COVID-19 pandemic has imposed a global emergency and also has raised issues with waste management practices. This study emphasized the challenges of increased waste disposal during the COVID-19 crisis and its response practices. Data obtained from the scientific research papers, publications from the governments and multilateral organizations, and media reports were used to quantify the effect of the pandemic towards waste generation. A huge increase in the amount of used personal protective equipments (facemasks, gloves, and other protective stuffs) and wide distribution of infectious wastes from hospitals, health care facilities, and quarantined households was found. The amount of food and plastic waste also increased during the pandemic. These factors caused waste treatment facilities to be overwhelmed, forcing emergency treatment and disposals (e.g., co-disposal in a municipal solid waste incinerator, cement kilns, industrial furnaces, and deep burial) to ramp up processing capacity. This paper discussed the ways the operation of those facilities must be improved to cope with the challenge of handling medical waste, as well as working around the restrictions imposed due to COVID-19. The study also highlights the need for short, mid, and longer-term responses towards waste management during the pandemic. Furthermore, the practices discussed in this paper may provide an option for alternative approaches and development of sustainable strategies for mitigating similar pandemics in the future. [Display omitted] • COVID-19 exhibited great challenges and practices on waste management. • The discarded facemask was estimated during COVID-19 pandemic. • Immediate responses and technological approach for COVID-19 crisis were reviewed. • MSW incinerator, industrial furnace, cement kiln can be used as emergency disposal. • Short and mid-longer term responses in waste management were provided. [ABSTRACT FROM AUTHOR]

In recent years, municipal authorities especially in the developing nations are battling to select the best health care waste (HCW) disposal technique for the effective treatment of the medical wastes during and post COVID-19 era. As evaluation of various disposal alternatives of HCW and selection of the best technique requires considering various tangible and intangible criteria, this can be framed as multi-criteria decision-making (MCDM) problem. In this paper, we propose an assessment framework for the selection of the best HCW disposal technique based on socio-technical and triple bottom line perspectives. We have identified 10 criteria on which the best HCW disposal techniques to be selected based on extant literature review. Next, we use Fuzzy VIKOR method to evaluate 9 HCW disposal alternatives. The effectiveness of the proposed framework has been demonstrated with a real-life case study in Indian context. To check the robustness of the proposed methodology, we have compared the results obtained with Fuzzy TOPSIS (Technique of Order Preference Similarity to the Ideal Solution). The results help the municipal authorities to establish a methodical approach to choose the best HCW disposal techniques. Our findings indicate that incineration is the best waste disposal technique among the available alternatives. Even if the dataset indicates 'incineration' is the best method, we must not forget about the environmental concerns arising from this method. In COVID time, incineration may be the best method as indicated by the data analysis, but "COVID" should not be an excuse for causing "Environmental Pollution". • Health care waste disposal technique selection is a serious concern during COVID-19. • We propose Fuzzy VIKOR based method for selecting the best disposal technique. • This work has been grounded on Triple Bottom Line and Socio-Technical perspectives. • The proposed framework has been validated with a real-life case study. • The effectiveness of the proposed method has been compared with Fuzzy TOPSIS. [ABSTRACT FROM AUTHOR]

Generation of healthcare waste from different patient care activities in hospitals, pathology labs and research centres has been a matter of great concern for environmental and social bodies across the world. This concern comes from its infectious and hazardous nature which brings life taking disease such as human immunodeficiency virus and Hepatitis-B. Moreover, with the outbreak of corona virus disease 2019 (COVID-19) pandemic across the world, healthcare waste has become even more infectious like never before and showing its potential for claiming lives if not disposed properly. Additionally, the COVID-19 has put up another challenge in terms of exponentially increasing demand for personal protective equipments for healthcare workers such as doctors, nurses, ward boys, and sanitation workers. In this paper, seven criteria related to smart healthcare waste disposal system infused by circular economy aspects to recover value from disposables are identified and analysed using a decision making trial and evaluation laboratory (DEMATEL) method. The criteria have been prioritized by its importance and net cause and effect relationship through a causal diagram. Two criteria, (i) digitally connected healthcare centres, waste disposal firms and pollution control board, and (ii) providing a pollution control board's feedback app to public and other stakeholders, feature as strong reasons for a smart healthcare waste disposal system. Conclusively, this study provides a causal relationship model among the intertwined drivers of industry 4.0 and circular economy for developing a smart healthcare waste disposal system enriched with the benefits of circular economy. [ABSTRACT FROM AUTHOR]

• A novel healthcare waste location-routing problem is developed with a new perspective in healthcare logistics networks. • A stochastic essence for the emission of contamination is considered. • The management of medical wastes in Coronavirus Disease 2019 is focused. • A real case study is modeled to manage the logistics of infectious and non-infectious healthcare wastes. • A Multi-Objective Water-Flow like Algorithm with novel operators is developed and compared with the others. This paper presents a novel healthcare waste location-routing problem by concentrating on a new perspective in healthcare logistics networks. In this problem, there are healthcare, treatment, and disposal centers. Locations of healthcare centers are known, however, it is required to select appropriate locations for treatment, recycling, and disposal centers. Healthcare wastes are divided into infectious and non-infectious wastes. Since a great volume of healthcare wastes are infectious, the emission of contamination can have obnoxious impacts on the environment. The proposed problem considers a stochastic essence for the emission of contamination which depends on the transferring times. In this respect, transferring times between healthcare and treatment centers have been considered as normal random variables. As transferring time increases, it is more likely for the contamination to spread. Having visited a treatment center, infectious wastes are sterilized and they will no longer be harmful to the environment. This research develops a bi-objective mixed-integer mathematical formulation to tackle this problem. The objectives of this model are minimization of total costs and emission of contamination, simultaneously. Complexity of the proposed problem led the researchers to another contribution. This study also develops a Multi-Objective Water-Flow like Algorithm (MOWFA), which is a meta -heuristic, to solve the problem. This algorithm uses a procedure based on the Analytical Hierarchy Process (AHP) to rank the non-dominated solutions in the archive set. By means of a developed mating operator, the MOWFA utilizes the best ranked solutions of the archive in order to obtain high quality offspring. Two neighborhood operators have been designed for the MOWFA as the local search methods. Extensive computational experiments have been conducted to evaluate the effectiveness of the MOWFA on several test problems compared with other meta -heuristics, namely the Multi-Objective Imperialist Competitive Algorithm (MOICA) and Multi-Objective Simulated Annealing (MOSA). These experiments also include a real healthcare waste logistic network in Iran. The computational experiments demonstrate that our proposed algorithm prevails these algorithms in terms of some well-known performance evaluation measures. [ABSTRACT FROM AUTHOR]