Occupational health and safety-oriented medical waste management: A case study of Istanbul

Designing a sustainable reverse logistics network for used cell phones based on offline and online trading systems

Unsustainable production and consumption are driving a significant increase in global electronic waste, posing substantial environmental and human health risks. Even in more developed nations, there is the challenge of low collection rates. In response, we integrate offline and online trading systems and design a material efficiency strategy for used cell phones. We propose a new multi-objective optimization framework to maximize profit, carbon emissions reduction, and circularity in the process of recycling and treatment. Considering multi-period, multi-product, multi-echelon features, as well as price sensitive demand, incentives, and qualities, we established a new multi-objective mixed-integer nonlinear programming optimization model. An enhanced, Fast, Non-Dominated Solution Sorting Genetic Algorithm (ASDNSGA-II) is developed for the solution. We used operational data from a leading Chinese Internet platform to validate the proposed optimization framework. The results demonstrate that the reverse logistics network designed achieves a win-win situation regarding profit and carbon emission reduction. This significantly boosts confidence and motivation for engaging in recycling efforts. Online recycling shows robust profitability and carbon reduction capabilities. An effective coordination mechanism for pricing in both online and offline channels should be established, retaining offline methods while gradually transitioning towards online methods. To increase the collection rate, it is essential to jointly implement a transitional strategy, including recycling incentives and subsidy policies. Additionally, elevating customer environmental awareness should be viewed as a long-term strategy, mitigating the cost of increasing collection rates during the market maturity stage (high collection rates).

Multi-criteria evaluation of medical waste management process under intuitionistic fuzzy environment: A case study on hospitals in Turkey

Waste management has come to the fore in the whole world with the increasing impact of the Covid-19 pandemic along with concerns about human health, environmental threats, and socio-economic factors, etc. Medical waste is one of the waste types that need special management processes including particularly collection, storage, separation, and disposal. Healthcare activities create a great amount of medical waste deriving from the hospitals. This study aims to determine the hospital that carries out medical waste management in the most effective way in Erzurum, Turkey. To handle intense uncertainty in the evaluation process, the case is analyzed by Intuitionistic Fuzzy Multi-Criteria Decision-Making (IFMCDM) methods. The present study contributes to the literature by focusing on a real case problem under IF environment in a Group Decision-Making (GDM) framework. Additionally, based on the literature review and expert judgments, the evaluation criteria relevant to the case are defined in this paper. To this end, a four-phased integrated methodology that involves Intuitionistic Fuzzy Weighted Averaging (IFWA), IF Analytical Hierarchy Process (IFAHP), IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS) and One-Dimensional Sensitivity Analysis, is conducted. Firstly, IFWA is aimed to express the significance levels of decision makers (DMs) based on their knowledge, qualifications and experiences. Secondly, IFAHP is used to calculate the importance weights of the decision criteria and IFTOPSIS is preferred to rank the available hospitals. Then, sensitivity analysis is employed to display robustness. According to the results, the most important criteria are Qualified personnel, Health institution infrastructure, and Control of waste, respectively and the most efficient hospital is determined.

Designing a sustainable logistics network for hazardous medical waste collection a case study in COVID-19 pandemic

The process of collecting and transporting hazardous medical waste poses a potential threat to the environment and public safety. Furthermore, the waste management system faces higher transportation costs due to the increasing human activities related to rapid population growth. The absence of an efficient and safe logistics network for the timely collection and transportation of hazardous wastes may have negative effects on the environment and public health. Therefore, more sustainable transportation of hazardous waste services is a necessity This paper attempts to design a sustainable network for hazardous medical waste collection services during the COVID-19 pandemic. An electric medical waste collection vehicle routing problem is introduced to construct optimal routes and rosters for a fleet of electric vehicles as well as cover their choice of charging technologies, times and locations. This problem allows us to minimize the health risk of hazardous medical waste while providing cost-effective, zero-emission waste management logistics. Therefore, this problem covers environmental and economic objectives to achieve sustainable development. An effective heuristic that covers adaptive large neighbourhood search and a local search is designed to deal with the complex problem. A series of extensive computational experiments is carried out using real-life benchmark instances to assess the performance of the algorithm. A sensitivity analysis is also conducted to investigate the effect of multiple charger types on the cost and risk objectives. The experiment results indicate that mixed-use of different charger types can reduce the total energy cost and transport risk compared to the case of using only a single charger.

Occupational Health Development and Safety Management of Enterprise Employees Based on the Perspective of Sustainable Environment

In recent years, the economy of enterprises has developed rapidly. Most enterprises focus on economic interests and ignore the occupational health of employees, resulting in an increase in the occupational morbidity rate of employees. Occupational insecurity of corporate employees will reduce the work efficiency of employees. In turn, it will affect the economic development of the enterprise. Paying attention to the occupational health and safety development of corporate employees is a necessary measure for corporate economic development. The main reasons that endanger the occupational health of employees are the unreasonable discharge of pollutants and the substandard treatment of pollutants. The sustainable environmental strategy of enterprise development can well control the risk factors that endanger the occupation of enterprise employees, and it is conducive to the health and safety development of enterprise employees and enterprises. This paper studied the impact of sustainable environmental factors on the occupational health and safety development of enterprise employees through the fuzzy analytic hierarchy process and analyzed the impact on the occupation of enterprise employees according to the larger influencing factors. The experimental results showed that heavy metal wastewater, dust, hydrogen sulfide gas, and high-temperature radiation are the four most weighted impact indicators. Different concentrations of these four indicators are tested; when the concentration value of these impact indicators is low, it has little impact on the occupational safety and development of enterprise employees. However, when the concentration increases, the occupational safety and development of enterprise employees are seriously reduced. When the safety is the lowest, it is only 20%, and the development is only 23%. Carrying out sustainable environmental development can reduce the discharge of industrial waste; hence, while protecting the environment, the occupational health and safety and development potential of employees can be improved.

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts - factory, consumers' and recycling centres - each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

Third-party Logistics in Bio-medical Waste System: a Path Towards a Risk-free Sector

After the sudden advent of COVID-19, the amount of medical waste has escalated to a great extent. The incremented medical waste amidst the pandemic exposes the improper waste management system of various developing countries. India, being one of the prominent developing countries, produces the largest waste in the world. Nonetheless, the Indian waste management system is not able to manage the massive amount of waste generated. Henceforth, this research study approaches to reveal the prominent factors which are causing failure in the system of medical waste management in India. This manuscript mainly focuses on two aspects. Firstly, this paper illuminates the factors which are hindering medical waste management by third-party logistics (3PL). Secondly, this study discusses a unique interval-value intuitionistic fuzzy set (IVIFS) based on Decision Making Trial and Evaluation Laboratory (DEMATEL) to depict graphical causal interrelationships among the factors. In addition, the analytic network process (ANP) is utilized to estimate the influence ranking of each factor. The results of this research anticipate that the transportation and disposal-related constraining factors require more attention from 3PL managers. The current study is unique as it enriches the various hindering factors on 3PL BMW management by discussing the ranking and relationship among factors.

Safe distance-based vehicle routing problem: Medical waste collection case study in COVID-19 pandemic

In addition to the increasing population and rapid urbanization, the amount and variety of medical waste are rapidly increasing due to the coronavirus disease (COVID-19) pandemic affecting the whole world. COVID-19 does not only increase the amount of medical waste produced, medical wastes generated in the care of COVID-19 carries a high risk of transmission as well. In this regard, the safe and effective management of medical wastes has become a serious health and safety issue. This research aims to determine the safest and shortest transportation routes for medical waste vehicles. The safety scores used in this study were obtained in our previous study. The resulting safety scores were used in a multi-objective traveling salesman problem for deriving two objective functions, which are based on safety scores and total transportation distance. A conciliating solution was obtained by solving this linear programming model. The proposed model faced by health institutions in Istanbul has been applied for a specific district. According to the obtained results, suggestions for the direction of medical waste vehicles have been proposed.

Sustainable production and waste management policies for COVID-19 medical equipment under uncertainty: A case study analysis

Unfortunately, an abrupt corona-virus disease (COVID-19) outbreak brought a drastic change in human lives. Almost every sector of human-beings and their related activities are severely infected and affected by this COVID-19 pandemic. As days are passing, the impact of the COVID-19 epidemic is going to be more severe. The fundamental needs for personal protective equipment (PPEs) are rising drastically all over the world. In India, many non-pharmaceutical companies or organizations such as automobile companies are engaged in producing the PPEs at a very marginal rate. Thus this paper proposes a modeling and optimization framework for sustainable production and waste management (SPWM) decision-making model for COVID-19 medical equipment under uncertainty. To quantify the uncertainties among parameter values, we have taken advantage of the intuitionistic fuzzy set theory. A robust ranking function is presented to obtain a crisp version of it. Furthermore, a novel interactive intuitionistic fuzzy programming approach is developed to solve the proposed SPWM model. An ample opportunity to generate the desired solution sets are also depicted. The performance analysis based on multiple criteria such as savings from baseline, co-efficient of variations, and desirability degrees is also introduced. Practical managerial implications are also discussed based on the significant findings after applying to the real case study data-set. Finally, conclusive remarks and the future research direction are also addressed on behalf of the current contributing study.

Emergency response to the explosive growth of health care wastes during COVID-19 pandemic in Wuhan, China

During the Coronavirus Disease 2019 (COVID-19) as a worldwide pandemic, the security management of health care wastes (HCWs) has attracted increasing concern due to their high risk. In this paper, the integrated management of HCWs in Wuhan, the first COVID-19-outbreaking city with over ten millions of people completely locking down, was collected, investigated and analyzed. During the pandemic, municipal solid wastes (MSWs) from designated hospitals, Fangcang shelter hospitals, isolation locations and residential areas (e.g. face masks) were collected and categorized as HCWs due to the high infectiousness and strong survivability of COVID-19, and accordingly the average production of HCWs per 1000 persons in Wuhan explosively increased from 3.64 kg/d to 27.32 kg/d. Segregation, collection, storage, transportation and disposal of HCWs in Wuhan were discussed and outlined. Stationary facilities, mobile facilities, co-processing facilities (Incineration plants for MSWs) and nonlocal disposal were consecutively utilized to improve the disposal capacity, from 50 tons/d to 280.1 tons/d. Results indicated that stationary and co-processing facilities were preferential for HCWs disposal, while mobile facilities and nonlocal disposal acted as supplementary approaches. Overall, the improved system of HCWs management could meet the challenge of the explosive growth of HCWs production during COVID-19 pandemic in Wuhan. Furthermore, these practices could provide a reference for other densely populated metropolises.

Health Care Waste Management Improvement Interventions Specifications and Results: A Systematic Review and Meta-Analysis

Background

Given the importance of proper management of Health Care Waste Management (HCWM), comprehensive information on interventions in this field is necessary. Therefore, we aimed to systematically review and meta-analysis of characteristics and results of interventions in the field of HCWM.

Methods

The required data were gathered through searching the keywords such as waste management, biomedical waste, hospitals waste, health care waste, infectious waste, medical waste, Waste Disposal Facilities, Garbage, Waste Disposal Facilities, Hazardous Waste Sites in PubMed, Scopus, EMBASE, Google scholar, Cochrane library, Science Direct, web of knowledge, SID and MagIran and hand searching in journals, reference by reference, and search in Gray literatures between 2000 and 2019. CMA software: 2 (Comprehensive Meta-Analysis) was used to perform the meta-analysis.

Results

Twenty-seven interventions were evaluated. Most of the studies were conducted after 2010, in the form of pre and post study, without control group, and in hospital. Interventions were divided into two categories: educational interventions (19 studies) and multifaceted managerial interventions (8 studies). The most studied outcome (in 11 studies) was KAP (knowledge, attitude and practice). The mean standard difference of interventions on KAP was estimated 3.04 (2.54-3.54) which was significant statistically (P<0.05). Also, interventions were considerably effective in improving the indicators of waste production amount, waste management costs and overall waste management performance.

Conclusion

Despite positive effect of interventions, due to the methodological deficiencies of published studies and high heterogeneity in results of studies, caution should be exercised in interpreting and using the results of the studies.