Two-phase COVID-19 medical waste transport optimisation considering sustainability and infection probability

Forecasting medical waste in Istanbul using a novel nonlinear grey Bernoulli model optimized by firefly algorithm

Waste management has gained global importance, aligning with the escalating impact of the COVID-19 pandemic and the associated concerns regarding medical waste, which poses threats to public health and environmental sustainability. In Istanbul, medical waste is considered a significant concern due to the rising volume of this waste, along with challenges in collection, incineration and storage. At this juncture, precise estimation of the waste volume is crucial for resource planning and allocation. This study, thus, aims to estimate the volume of medical waste in Istanbul using the nonlinear grey Bernoulli model (NGBM(1,1)) and the firefly algorithm (FA). In other words, this study introduces a novel hybrid model, termed as FA-NGBM(1,1), for predicting waste amount in Istanbul. Within this model, prediction accuracy is enhanced through a rolling mechanism and parameter optimization. The effectiveness of this model is compared with the classical GM(1,1) model, the GM(1,1) model optimized with the FA (FA-GM(1,1)), the fractional grey model optimized with the FA (FA-FGM(1,1)) and linear regression. Numerical results indicate that the proposed FA-NGBM(1,1) hybrid model yields lower prediction error with a mean absolute percentage error value 3.47% and 2.57%, respectively, for both testing and validation data compared to other prediction algorithms. The uniqueness of this study is rooted in the process of initially optimizing the parameters for the NGBM(1,1) algorithm using the FA for medical waste estimation in Istanbul. This study also forecasts the amount of medical waste in Istanbul for the next 3 years, indicating a dramatic increase. This suggests that new policies should be promptly considered by decision-makers and practitioners.

Study on sustainable transportation mode of medical waste in big city hospitals based on multi-agent

BackgroundMedical waste should be collected, classified, and transported to the treatment plant within 48 h. If it is not disposed of in time, it will cause cross-infection, increasing the risk of disease transmission and environmental pollution. How to reasonably plan transportation routes to ensure that the medical waste can be transported to the treatment plant in time is very important.ObjectiveThere are usually two modes of transportation, the fastest speed and shortest path, how to reasonably plan the transportation scheme so that medical waste can be transported to the treatment plant for disposal in the specified time is the main purpose of this article.MethodsThe multi-agent modeling method is adopted. AnyLogic simulation software is used to model the transportation routes of 118 Grade III hospitals and 2 treatment plants in Beijing under the two transportation modes of fastest speed and shortest path.ResultsBased on the traffic index in Beijing, the speed range of 20 km/h-32 km/h is set up and divided into 4 parts and 24 levels with 0.5 km/h as the unit, and the 24 levels of medical waste transportation data set is formed. The key speed nodes of 21 km/h, 24 km/h and 29.5 km/h are identified.ConclusionsThe medical waste transportation model and transport data set formed in this paper have enriched the theory and data basis of medical waste transportation management. The key speed nodes of transportation model selection have important practical significance for the transportation management decision of medical waste in big cities.

Identifying methods and challenges of waste management in natural disasters

Natural disasters, depending on their severity, can generate vast amounts of waste. Without proper waste management, these disasters can result in environmental pollution, epidemics of infectious diseases, and reduced resilience and recovery. Although natural disasters are beyond human control, the extent of their impact is often influenced by the effectiveness of governmental and administrative responses. This study aims to identify methods of waste management in disaster scenarios and highlight the existing challenges. This study is designed in three phases to assess the current situation in the world in terms of the amount of natural disasters, waste management in disasters, and investigating the consequences of waste management in disasters. The study analyzes approximately 18,000 raw data points and 223 articles spanning from 1900 to 2023. The results indicate that Asia has experienced the highest number of natural disasters, while Oceania has experienced the lowest. The highest incidence rate, economic burden, mortality, and waste generation are related to hydrological, meteorological, biological, and geophysical disasters, respectively. Although biological disasters occur less frequently, they are not confined to specific locations and impact a larger population. While developed countries like Japan and the USA have valuable experience in disaster waste management, comprehensive waste management programs remain lacking in developing countries. This study emphasizes the need for public education, development of standardized national protocols, infrastructure development, increased interdisciplinary research, improve inter-organizational coordination, improved international relations, optimized equipment, supporting of the non-governmental organizations (NGOs), and the use of emerging technologies to estimate waste production before disasters.

Experimental study on recycling rubber to increase the impact resistance of cement mortar

The COVID-19 pandemic has led to a surge in medical waste generation, posing hazards to both the environment and global health. The impacts of the COVID-19 pandemic's medical waste hazard may persist long after the pandemic itself subsides. Improper disposal of medical waste can contaminate environment, posing risks to ecosystems and public health. Discarded medical rubber gloves, for example, can become a source of infection, improper disposal of these gloves can escalate the spread of infectious diseases and increase the risk of transmission of the virus to the general public. This study proposes an innovative and sustainable method to reinforce cement mortar by adding recycled glove rubber as an additive to cement mortar to increase its resistance to impact loads. This study conducted uniaxial compression tests, separating hopkinson pressure bar (SHPB) experiments and SEM observations to evaluate the quasi-static compressive strength and dynamic stress of recycled rubber fiber mortar (RRFM) with varying recycled rubber fiber (RRF) contents (0, 1%, 2%, 3%). Strain curves, dynamic increase factor (DIF), energy absorption rules, failure modes, and microstructure of RRFM mixtures. The experimental results demonstrate that with the addition of RRF, the dynamic stress-strain curve flattens and the peak strain gradually increases. The RRFM sample shows stronger toughness. In comparison to regular cement mortar (NM), RRFM has a higher DIF and specific absorbed energy, a faster increase in dynamic compressive strength, and the ability to absorb more energy per unit volume. Under the same impact load, RRFM has fewer and smaller cracks than NM. Scanning electron microscopy (SEM) testing also observed that RRF formed a strong connection pattern with the cement mortar matrix.

Optimization of household medical waste recycling logistics routes: Considering contamination risks

The escalating generation of household medical waste, a byproduct of industrialization and global population growth, has rendered its transportation and logistics management a critical societal concern. This study delves into the optimization of routes for vehicles within the household medical waste logistics network, a response to the imperative of managing this waste effectively. The potential for environmental and public health hazards due to improper waste disposal is acknowledged, prompting the incorporation of contamination risk, influenced by transport duration, waste volume, and wind velocity, into the analysis. To enhance the realism of the simulation, traffic congestion is integrated into the vehicle speed function, reflecting the urban roads' variability. Subsequently, a Bi-objective mixed-integer programming model is formulated to concurrently minimize total operational costs and environmental pollution risks. The complexity inherent in the optimization problem has motivated the development of the Adaptive Hybrid Artificial Fish Swarming Algorithm with Non-Dominated Sorting (AH-NSAFSA). This algorithm employs a sophisticated approach, amalgamating congestion distance and individual ranking to discern optimal solutions from the population. It incorporates a decay function to facilitate an adaptive iterative process, enhancing the algorithm's convergence properties. Furthermore, it leverages the concept of crossover-induced elimination to preserve the genetic diversity and overall robustness of the solution set. The empirical evaluation of AH-NSAFSA is conducted using a test set derived from the Solomon dataset, demonstrating the algorithm's capability to generate feasible non-dominated solutions for household medical waste recycling path planning. Comparative analysis with the Non-dominated Sorted Artificial Fish Swarm Algorithm (NSAFSA) and Non-dominated Sorted Genetic Algorithm II (NSGA-II) across metrics such as MID, SM, NOS, and CT reveals that AH-NSAFSA excels in MID, SM, and NOS, and surpasses NSAFSA in CT, albeit slightly underperforming relative to NSGA-II. The study's holistic approach to waste recycling route planning, which integrates cost-effectiveness with pollution risk and traffic congestion considerations, offers substantial support for enterprises in formulating sustainable green development strategies. AH-NSAFSA offers an eco-efficient, holistic approach to medical waste recycling, advancing sustainable management practices.

An application of BWM for risk control in reverse logistics of medical waste

The pollution posed by medical waste complicate the procedures of medical waste logistics (MWL), and the increasingly frequent occurrence of public health emergencies has magnified the risks posed by it. In this study, the authors established an index of the factors influencing the risks posed by MWL along five dimensions: the logistics business, emergency capacity, equipment, personnel, and management. The best-worst case method was used to identify the critical risk-related factors and rank them by importance. Following this, we assessed the risk posed by MWL in four major cities in China as an example and propose the corresponding measures of risk control. The results showed that the linking of business processes was the most important factor influencing the risk posed by MWL. The other critical risk-related factors included the location of the storage site, the capacity for emergency transportation, measures to manage emergencies, and the safety of packaging. Of the cities considered, Beijing was found to be a high-risk city, and its MWL needed to be improved as soon as possible in light of the relevant critical risks. Shanghai, Guangzhou, and Shenzhen were evaluated as general-risk cities, which meant that the risks of MWL were not a priority in these areas, and the other goals of urban development should be comprehensively considered during the long-term planning for MWL in these municipalities.

Pralatrexate inhibited the replication of varicella zoster virus and vesicular stomatitis virus: An old dog with new tricks

Varicella zoster virus (VZV) is associated with herpes zoster (HZ) or herpes zoster ophthalmicus (HZO). All antiviral agents currently licensed for the management of VZV replication via modulating different mechanisms, and the resistance is on the rise. There is a need to develop new antiviral agents with distinct mechanisms of action and adequate safety profiles. Pralatrexate (PDX) is a fourth-generation anti-folate agent with an inhibitory activity on folate (FA) metabolism and has been used as an anti-tumor drug. We observed that PDX possessed potent inhibitory activity against VZV infection. In this study, we reported the antiviral effects and the underlying mechanism of PDX against VZV infection. The results showed that PDX not only inhibited VZV replication in vitro and in mice corneal tissues but also reduced the inflammatory response and apoptosis induced by viral infection. Furthermore, PDX treatment showed a similar anti-VSV inhibitory effect in both in vitro and in vivo models. Mechanistically, PDX inhibited viral replication by interrupting the substrate supply for de novo purine and thymidine synthesis. In conclusion, this study discovered the potent antiviral activity of PDX with a novel mechanism and presented a new strategy for VZV treatment that targets a cellular metabolic mechanism essential for viral replication. The present study provided a new insight into the development of broad-spectrum antiviral agents.

A multi-jurisdictional study on the quantification of COVID-19 household plastic waste in six Latin American countries

This study examines urban plastic waste generation using a citizen science approach in six Latin American countries during a global pandemic. The objectives are to quantify generation rates of masks, gloves, face shields, and plastic bags in urban households using online survey and perform a systematic cross-jurisdiction comparisons in these Latin American countries. The per capita total mask generation rates ranged from 0.179 to 0.915 mask cap-1 day-1. A negative correlation between the use of gloves and masks is observed. Using the average values, the approximate proportion of masks, gloves, shields, and single-use plastic bags was 34:5:1:84. We found that most studies overestimated face mask disposal rate in Latin America due to the simplifying assumptions on the number of masks discarded per person, masking prevalence rate, and average mask weight. Unlike other studies, end-of-life PPE quantities were directly counted and reported by the survey participants. Both of the conventional weight-based estimates and the proposed participatory survey are recommended in quantifying COVID waste. Participant' perception based on the Likert scale is generally consistent with the waste amount generated. Waste policy and regulation appear to be important in daily waste generation rate. The results highlight the importance of using measured data in waste estimates.