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Healthcare waste (HCW) is generated in different healthcare facilities (HCFs), such as hospitals, laboratories, veterinary clinics, research centres and nursing homes. It has been assessed that the majority of medical waste does not pose a risk to humans. It is estimated that 15% of the total amount of produced HCW is hazardous and can be infectious, toxic or radioactive. Hazardous waste is a special type of waste which, if not properly treated, can pose a risk to human health and to the environment. HCW contains potentially harmful microorganisms that can be spread among healthcare personnel, hospital patients and the general public, causing serious illnesses. Healthcare personnel are the specialists especially exposed to this risk. The most common medical procedure, which pose the highest risk, is injection (i.e, intramuscular, subcutaneous, intravenous, taking blood samples). The World Health Organization (WHO) estimates that around 16 billion injections are administered worldwide each year. However, if safety precautions are not followed, and needles and syringes are not properly disposed of, the risk of sharps injuries increases among medical staff, waste handlers and waste collectors. What is more, sharps injuries increase the risk of human immunodeficiency virus (HIV), hepatitis B and C viruses (HBV/HCV), tuberculosis (TB), diphtheria, malaria, syphilis, brucellosis and other transmissions. Disposing of medical waste in a landfill without segregation and processing will result in the entry of harmful microorganisms, chemicals or pharmaceuticals into soil and groundwater, causing their contamination. Open burning or incinerator malfunctioning will result in the emission of toxic substances, such as dioxins and furans, into the air. In order to reduce the negative impact of medical waste, waste management principles should be formulated. To minimize health risks, it is also important to build awareness among health professionals and the general public through various communication and educational methods. The aim of this paper is to present a general overwiev of medical waste, its categories, the principles of its management and the risks to human health and the environment resulting from inappropriate waste management. [ABSTRACT FROM AUTHOR]

More and more serious games have been developed in recent years for patients with aging, rehabilitation, mental, and other healthcare needs. Often, such healthcare games have different experiments or evaluations associated. Rapid advancements in healthcare games see increased regulatory concerns. Unfortunately, there is no authority like the Food and Drug Administration (FDA) in United States for regulatory approvals of healthcare games. Yet, it is not appropriate to use the traditional pharmaceutical FDA approval, which is a tedious and time-consuming process, for healthcare games. We propose a Healthcare Game Blockchain (HGB) to support game developers, healthcare providers, healthcare authorities, and patients. For healthcare game developers, HGB is a common platform to deposit healthcare game prototypes or products. HGB can collect feedback data for analysis similar to drug clinical trials on efficacy and toxicity. Volunteers can be recruited for clinical trials using the healthcare games available on HGB. Once the healthcare games are accepted with a recommended usage, patient gamers can leverage the same HGB platform for treatments following the instructions of healthcare providers. HGB allows healthcare professionals to track the patient responses during their healthcare game medication. Big data analytics can be developed to monitor patient outcomes and healthcare game efficacy. Security and privacy issues are critical in healthcare data handling. HGB has the potential to resolve these limitations and inefficiencies improving data collection, data sharing, and data security by leveraging on the intrinsic properties that blockchain technology provides. This paper explores the possibility of integrating blockchain and healthcare games supporting clinical trials and treatment monitoring. [ABSTRACT FROM AUTHOR]

The healthcare sector is an ever-growing industry which produces a vast amount of waste each year, and it is crucial for healthcare systems to have an effective and sustainable medical waste management system in order to protect public health. Greek public hospitals in 2018 produced 9500 tons of hazardous healthcare wastes, and it is expected to reach 18,200 tons in 2025 and exceed 18,800 tons in 2030. In this paper, we investigated the factors that affect healthcare wastes. We obtained data from all Greek public hospitals and conducted a regression analysis, with the management cost of waste and the kilos of waste as the dependent variables, and a number of variables reflecting the characteristics of each hospital and its output as the independent variables. We applied and compared several models. Our study shows that healthcare wastes are affected by several individual-hospital characteristics, such as the number of beds, the type of the hospital, the services the hospital provides, the number of annual inpatients, the days of stay, the total number of surgeries, the existence of special units, and the total number of employees. Finally, our study presents two prediction models concerning the management costs and quantities of infectious waste for Greece's public hospitals and proposes specific actions to reduce healthcare wastes and the respective costs, as well as to implement and adopt certain tools, in terms of sustainability.

At present, strategies for controlling the COVID-19 pandemic have made significant and strategic strides; however, and the large quantities of healthcare treatment waste have become another important "battlefield". For example, in Wuhan, the production rate of healthcare waste in hospitals, communities, temporary storage, and other units was much faster than the disposal rate during the COVID-19 pandemic. Improving the efficiency of healthcare waste transfer and treatment has become an important task for government health and environmental protection departments at all levels. Based on the situation of healthcare waste disposal in Wuhan during the critical period of the pandemic, this paper analyzes and studies green governance principles and summarizes the problems that exist in the current healthcare waste management system. Through the establishment of temporary storage facilities along transit routes, digital simulation and bionic experiments were carried out in the Hongshan District of Wuhan to improve the efficiency of healthcare waste transfer. Furthermore, this study discusses the coordination and cooperation of government, hospitals, communities, and other departments in the healthcare waste disposal process and provides guiding suggestions for healthcare waste disposal nationwide in order to deal with potential risks and provide effective references in all regions.

Although local governments have issued relevant reward and penalty policies, there are still problems of medical waste disposal in China, particularly in light of the special situation of the COVID-19 pandemic. Furthermore, these problems are generated in the game between local governments and disposal enterprises. Accordingly, based on the evolutionary game theory, this paper establishes and analyzes the game system between local governments and disposal enterprises under four modes: static reward and static penalty, dynamic reward and static penalty, static reward and dynamic penalty, and dynamic reward and dynamic penalty. The theoretical analysis is verified through numerical simulation of a medical waste disposal case in China. The results showed that when local governments choose the static reward and static penalty mode, the game system hardly always has an evolutionary stable state, and the dynamic reward or dynamic penalty mode can make up for the shortcomings of the static reward and static penalty mode. The static reward and dynamic penalty mode is considerably better than the other two dynamic reward and penalty modes, which has the best effect on improving the quality of medical waste disposal. Additionally, if the reward or penalty increases dynamically, local governments tend to implement a "relaxed supervision" strategy, and disposal enterprises will still improve the disposal quality of medical waste. The suggestions proposed based on the research conclusions offer some enlightenment for policymakers to formulate reasonable reward and penalty measures. [ABSTRACT FROM AUTHOR]

In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony-tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China-considered the first city to suffer from COVID-19-was chosen as an example of verification; the two-level model and the immune algorithm-ant colony optimization-tabu search (IA-ACO-TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.

The outbreak of an epidemic disease may pose significant treats to human beings and may further lead to a global crisis. In order to control the spread of an epidemic, the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital importance. However, no research has been conducted with the focus on the design of an epidemic reverse logistics network for dealing with medical waste during epidemic outbreaks, which, if improperly treated, may accelerate disease spread and pose a significant risk for both medical staffs and patients. Therefore, this paper proposes a novel multi-objective multi-period mixed integer program for reverse logistics network design in epidemic outbreaks, which aims at determining the best locations of temporary facilities and the transportation strategies for effective management of the exponentially increased medical waste within a very short period. The application of the model is illustrated with a case study based on the outbreak of the coronavirus disease 2019 (COVID-19) in Wuhan, China. Even though the uncertainty of the future COVID-19 spread tendency is very high at the time of this research, several general policy recommendations can still be obtained based on computational experiments and quantitative analyses. Among other insights, the results suggest installing temporary incinerators may be an effective solution for managing the tremendous increase of medical waste during the COVID-19 outbreak in Wuhan, but the location selection of these temporary incinerators is of significant importance. Due to the limitation on available data and knowledge at present stage, more real-world information are needed to assess the effectiveness of the current solution.

Although medical waste usually accounts for a small fraction of urban municipal waste, its proper disposal has been a challenging issue as it often contains infectious, radioactive, or hazardous waste. This article proposes a two-level hierarchical multicriteria decision model to address medical waste disposal method selection (MWDMS), where disposal methods are assessed against different criteria as intuitionistic fuzzy preference relations and criteria weights are furnished as real values. This paper first introduces new operations for a special class of intuitionistic fuzzy values, whose membership and non-membership information is cross ratio based ]0, 1[-values. New score and accuracy functions are defined in order to develop a comparison approach for ]0, 1[-valued intuitionistic fuzzy numbers. A weighted geometric operator is then put forward to aggregate a collection of ]0, 1[-valued intuitionistic fuzzy values. Similar to Saaty's 1-9 scale, this paper proposes a cross-ratio-based bipolar 0.1-0.9 scale to characterize pairwise comparison results. Subsequently, a two-level hierarchical structure is formulated to handle multicriteria decision problems with intuitionistic preference relations. Finally, the proposed decision framework is applied to MWDMS to illustrate its feasibility and effectiveness., Competing Interests: The authors declare no conflict of interest.

Health-care waste (HCW) management is a major challenge for municipalities, particularly in the cities of developing nations. Selecting the best treatment technology for HCW can be regarded as a complex multi-criteria decision making (MCDM) issue involving a number of alternatives and multiple evaluation criteria. In addition, decision makers tend to express their personal assessments via multi-granularity linguistic term sets because of different backgrounds and knowledge, some of which may be imprecise, uncertain and incomplete. Therefore, the main objective of this study is to propose a new hybrid decision making approach combining interval 2-tuple induced distance operators with the technique for order preference by similarity to an ideal solution (TOPSIS) for tackling HCW treatment technology selection problems with linguistic information. The proposed interval 2-tuple induced TOPSIS (ITI-TOPSIS) can not only model the uncertainty and diversity of the assessment information given by decision makers, but also reflect the complex attitudinal characters of decision makers and provide much more complete information for the selection of the optimum disposal alternative. Finally, an empirical example in Shanghai, China is provided to illustrate the proposed decision making method, and results show that the ITI-TOPSIS proposed in this paper can solve the problem of HCW treatment technology selection effectively.

The colossal increase in environmental pollution and degradation, resulting in ecological imbalance, is an eye-catching concern in the contemporary era. Moreover, the proliferation in the development of smart cities across the globe necessitates the emergence of a robust smart waste management system for proper waste segregation based on its biodegradability. The present work investigates a novel approach for waste segregation for its effective recycling and disposal by utilizing a deep learning strategy. The YOLOv3 algorithm has been utilized in the Darknet neural network framework to train a self-made dataset. The network has been trained for 6 object classes (namely: cardboard, glass, metal, paper, plastic and organic waste). Moreover, for comparative assessment, the detection task has also been performed using YOLOv3-tiny to validate the competence of the YOLOv3 algorithm. The experimental results demonstrate that the proposed YOLOv3 methodology yields satisfactory generalization capability for all the classes with a variety of waste items. [ABSTRACT FROM AUTHOR]

The development of new methods for the correct disposal of waste is unavoidable for any city that aims to become eco-friendly. Waste management is no exception. In the modern era, the treatment and disposal of infectious waste should be seen as an opportunity to generate renewable energy, resource efficiency, and, above all, to improve the population's quality of life. Northern Italy currently produces 66,600 tons/year of infectious waste, mostly treated through incineration plants. This research aims to explore a more ecological and sustainable solution, thereby contributing one more step toward achieving better cities for all. Particularly, this paper presents a conceptual design of the main sterilization chamber for infectious waste. The methodology selected was Design Thinking (DT), since it has a user-centered approach which allows for co-design and the inclusion of the target population. This study demonstrates to the possibility of obtaining feasible results based on the user's needs through the application of DT as a framework for engineering design. [ABSTRACT FROM AUTHOR]

In order to build a more comprehensive emergency disposal and transportation network system for medical waste, it is necessary to consider various uncertain factors and data characteristics. Therefore, in the context of intelligent transportation, this article considers the uncertainty of the quantity and regional population density of infectious medical waste generation as well as the emergency disposal of infectious medical waste under multi-cycle and multi-objective conditions, and it constructs a multi-cycle emergency disposal logistics network optimization model for infectious medical waste under uncertain conditions. Through deterministic transformation of the model and data mining of the medical waste disposal logistics network in Wuhan, China, the multi-objective model under uncertain conditions was also solved and sensitivity analyzed using the MOPSO-NSGA2 intelligent algorithm, verifying the effectiveness and superiority of the algorithm. [ABSTRACT FROM AUTHOR]

This study aims to investigate the potential scope of rural bioenergy production from the valorisation of non-hazardous waste, particularly from institutional health and family planning facilities. A crude bioenergy production potential will be determined, as well as relevant interrelationships with food security, equality and inclusivity, poverty reduction, and their contribution to achieving sustainable development goals (SDGs). Solid waste generation at LAMB Hospital in Bangladesh was assessed. Its energy yield capacity and replacement of conventional, inefficient fuel sources were estimated, analysed, and specified. Results showed that the biogas yield capacity of non-hazardous solid waste from the LAMB hospital is 62 m3, which is equivalent to the gas required to cook 31 family meals. From small-to-medium institutes, such as the LAMB hospital, derived waste has the capacity to meet the cooking energy demand of rural villages. The electrical yield capacity of this amount of gas is 124 kWh, and this amount of energy can replace the use of 41 tonnes of firewood that cause emissions, deforestation, and increases the propensity for flooding. The adoption of Anaerobic Digestion (AD) for biogas production also has an impact on waste management, stimulating improved governance and infrastructure and supporting agriculture through the production of nutrient-dense biofertiliser. Further analysis showed that biogas not only provides a clean and affordable fuel but, in turn, has benefits with regard to health issues. Emissions from traditional cooking fuels have deleterious impacts on health due to Indoor Air Pollution (IAP), which generally affects women to a greater extent. All of these factors contribute to achieving sustainable development goals. This study could help to reduce environmental pollution from the health sector and mitigate climate change impacts, and there is a potential for scaling up this study nationwide. [ABSTRACT FROM AUTHOR]

A hybrid scheme integrating the current waste heat recovery system (WHRS) for a silicon arc furnace with plasma gasification for medical waste is proposed. Combustible syngas converted from medical waste is used to drive the gas turbine for power generation, and waste heat is recovered from the raw syngas and exhaust gas from the gas turbine for auxiliary heating of steam and feed water in the WHRS. Meanwhile, the plasma gasifier can also achieve a harmless disposal of the hazardous fine silica particles generated in polysilicon production. The performance of the proposed design is investigated by energy, exergy, and economic analysis. The results indicate that after the integration, medical waste gave rise to 4.17 MW net power at an efficiency of up to 33.99%. Meanwhile, 4320 t of the silica powder can be disposed conveniently by the plasma gasifier every year, as well as 23,040 t of medical waste. The proposed design of upgrading the current WHRS to the hybrid system requires an initial investment of 18,843.65 K$ and has a short dynamic payback period of 3.94 years. Therefore, the hybrid scheme is feasible and promising for commercial application. [ABSTRACT FROM AUTHOR]

Elevated medical waste has urged the improvement of sustainable medical waste treatments. A bibliometric analysis is initially conducted to investigate scientific development of medical waste management to pinpoint the publication trends, influential articles, journals and countries and study hotspots. Publications on medical waste and its management sharply increased since 2020. The most influential article was written by Klemeš et al., and "Waste Management and Research" is the most productive journal. India, China, the United Kingdom, Iran and Italy have published the most works. The research spotlights have switched from "human" and "sustainable development" in 2019 to "COVID-19" and "circular economy" in 2021. Since government acts essentially in handling medical waste and controlling disease transmission, rule implementations among the abovementioned countries are summarized to seek gaps between scientific advancement and regulatory frameworks. For accomplishing a circular economy, waste-to-energy technologies (incineration, gasification, pyrolysis, plasma-based treatments, carbonization, hydrogenation, liquefaction, biomethanation, fermentation and esterification) are comprehensively reviewed. Incineration, gasification, pyrolysis and carbonization are relatively feasible methods, their characteristics and limitations are further compared. By holistically reviewing current status of medical waste research, the focal points involved in management at the policy and technical level have been highlighted to find proper routes for medical waste valorization. [ABSTRACT FROM AUTHOR]

The paper presents and discusses the issues of medical waste (including hazardous ones) and the problems regarding their proper management in Poland. Inappropriate handling of infectious medical waste directly endangers human health and the environment. Infectious waste must be properly disposed of—in practice, the only method of their disposal available in Poland is a thermal treatment in the incinerators tailored for this purpose. This causes many problems to smaller entities such as the local health centers, but also to the beauty and tattoo salons. As a solution to these problems, the mobile medical waste incinerator was proposed. During designing an incinerator unit, a diverse morphological composition of the medical waste should be taken into account, however, there are no inspection reports available in Poland. Based on a few data concerning the composition of the medical waste, the article presents designing considerations in regard to the incinerator's chamber dimensions. The calculations were carried out for several variants of the waste morphological composition. The own construction of a mobile medical waste incinerator, which conforms to the regulations in Poland and the European Union, was presented. It should be emphasized that it is a novelty on the Polish market, due to the automatic waste feeder into the combustion chamber, adapted to a mobile unit. [ABSTRACT FROM AUTHOR]

Predicting medical waste (MW) properly is vital for an effective waste management system (WMS), but it is difficult because of inadequate data and various factors that impact MW. This study's primary objective was to develop an ensemble voting regression algorithm based on machine learning (ML) algorithms such as random forests (RFs), gradient boosting machines (GBMs), and adaptive boosting (AdaBoost) to predict the MW for Istanbul, the largest city in Turkey. This was the first study to use ML algorithms to predict MW, to our knowledge. First, three ML algorithms were developed based on official data. To compare their performances, performance measures such as mean absolute deviation (MAE), root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R-squared) were calculated. Among the standalone ML models, RF achieved the best performance. Then, these base models were used to construct the proposed ensemble voting regression (VR) model utilizing weighted averages according to the base models' performances. The proposed model outperformed three baseline models, with the lowest RMSE (843.70). This study gives an effective tool to practitioners and decision-makers for planning and constructing medical waste management systems by predicting the MW quantity. [ABSTRACT FROM AUTHOR]

To prevent the spread of the COVID-19 pandemic, 2019 has seen unprecedented demand for medical equipment and supplies. However, the problem of waste treatment has not yet been given due attention, i.e., the traditional waste treatment process is done independently, and it is not easy to share the necessary information. Especially during the COVID-19 pandemic, the interaction between parties is minimized to limit infections. To evaluate the current system at medical centers, we also refer to the traditional waste treatment processes of four hospitals in Can Tho and Ho Chi Minh cities (Vietnam). Almost all hospitals are handled independently, lacking any interaction between the stakeholders. In this article, we propose a decentralized blockchain-based system for automating waste treatment processes for medical equipment and supplies after usage among the relevant parties, named Medical-Waste Chain. It consists of four components: medical equipment and supplies, waste centers, recycling plants, and sorting factories. Medical-Waste Chain integrates blockchain-based Hyperledger Fabric technology with decentralized storage of medical equipment and supply information, and securely shares related data with stakeholders. We present the system design, along with the interactions among the stakeholders, to ensure the minimization of medical waste generation. We evaluate the performance of the proposed solution using system-wide timing and latency analysis based on the Hyperledger Caliper engine. Our system is developed based on the hybrid-blockchain system, so it is fully scalable for both on-chain and off-chain-based extensions. Moreover, the participants do not need to pay any fees to use and upgrade the system. To encourage future use of Medical-Waste Chain, we also share a proof-of-concept on our Github repository. [ABSTRACT FROM AUTHOR]

Increased demand for animal protein is met by increased food animal production resulting in large quantities of manure. Animal producers, therefore, need sustainable agricultural practices to protect environmental health. Large quantities of antimicrobials are used in commercial food animal production. Consequently, antimicrobial-resistant bacteria and the resistance genes emerge and are excreted through feces. Manure management is essential for the safe disposal of animal waste. Lagoons, with or without covers, and anaerobic digesters, with the primary purpose of methane production, and composting, with the primary purpose of producing organic fertilizer, are widely used methods of manure treatment. We reviewed manure management practices and their impact on tetracycline resistance genes. Lagoons are maintained at ambient temperatures; especially uncovered lagoons are the least effective in removing tetracycline resistance genes. However, some modifications can improve the performance of lagoons: sequential use of uncovered lagoons and the use of covered lagoons resulted in a one-log reduction, while post-treatments such as biofiltration following covered lagoon treatment resulted in 3.4 log reduction. Mesophilic digestion of animal manure did not have any significant effect; only a 0.7 log reduction in tet(A) was observed in one study. While thermophilic anaerobic digesters are effective, if properly operated, they are expensive for animal producers. Aerobic thermophilic composting is a promising technology if optimized with its economic benefits. Composting of raw animal manure can result in up to a 2.5 log reduction, and postdigestion composting can reduce tetracycline resistance gene concentration by >80%. In general, manure management was not designed to mitigate antimicrobial resistance; future research is needed to optimize the economic benefits of biogas or organic fertilizer on the one hand and for the mitigation of foodborne pathogens and antimicrobial resistance on the other. [ABSTRACT FROM AUTHOR]

Biomedical waste management is getting significant consideration among treatment technologies, since insufficient management can cause danger to medicinal service specialists, patients, and their environmental conditions. The improvement of waste administration protocols, plans, and policies are surveyed, despite setting up training programs on legitimate waste administration for all healthcare service staff. Most biomedical waste substances do not degrade in the environment, and may also not be thoroughly removed through treatment processes. Therefore, the long-lasting persistence of biomedical waste can effectively have adverse impact on wildlife and human beings, as well. Hence, photocatalysis is gaining increasing attention for eradication of pollutants and for improving the safety and clearness of the environment due to its great potential as a green and eco-friendly process. In this regard, nanostructured photocatalysts, in contrast to their regular counterparts, exhibit significant attributes such as non-toxicity, low cost and higher absorption efficiency in a wider range of the solar spectrum, making them the best candidate to employ for photodegradation. Due to these unique properties of nanophotocatalysts for biomedical waste management, we aim to critically evaluate various aspects of these materials in the present review and highlight their importance in healthcare service settings. [ABSTRACT FROM AUTHOR]

Taiwan offers affordable access to health care through the National Health Insurance (NHI) Program, but this increases the risk of waste of medications and pollution caused by improper disposal. This research aimed to: (1) understand methods of disposal of unused medications, and public awareness of related issues, (2) understand the sources and types of unused medications and reasons for their disposal, and (3) propose improvements to current disposal practices. Data on practices and perspectives on the disposal of medications were collected from members of the public using a questionnaire, and subjected to chi-square analysis of demographic variables. The survey found that many respondents disposed of medications inappropriately, but most believed the government should establish a return system. The majority of discarded medications came from hospitals, and were most frequently discarded because patients had forgotten to take them. Based on these findings, the study proposes that receiving stations be established across Taiwan for the safe and environmentally friendly disposal of unused medications, along with a system of monthly checks and compensation for pharmacists' costs. The study also suggests that pharmacists strengthen medication guidance, spend more time on medication counseling, better understand the reasons for medication waste, and offer health education and advice to physicians and the public. [ABSTRACT FROM AUTHOR]