Healthcare waste management at primary health centres in Mon State, Myanmar: the comparisons between hospital and non-hospital type primary health centres

Evolutionary Game Analysis of Medical Waste Disposal in China under Different Reward and Penalty Models

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.

Healthcare Waste Management Practices and Associated Factors in Private Clinics in Addis Ababa, Ethiopia

BACKGROUND

Healthcare waste management requires special attention and every healthcare teams should be involved in handling of wastes at point of generation. However, less attention is given to healthcare waste management in Ethiopia and there is no evidence about healthcare waste management practices in private clinics in Addis Ababa. Accordingly, this study was conducted to assess healthcare waste management practices and associated factors in private clinics in Addis Ababa, Ethiopia.

METHODS

A health facility-based cross-sectional study was conducted in 278 randomly selected private clinics in Addis Ababa. Data were collected using questionnaire and observational checklists. Multivariable binary logistic regression analysis was used to identify factors associated with healthcare waste management practices on the basis of adjusted odds ratio (AOR) with 95% confidence interval (CI) and P-values <.05.

RESULT

Results showed that 61.2% of the surveyed clinics had poor healthcare waste management practices, out of which, 56.8% had poor waste segregation practice, 55.0% had poor waste collection practice, 85.6% had poor waste transportation practice, 63.3% had poor waste storage practice, 61.9% had poor waste treatment, and 57.9% had poor disposal system. Healthcare waste management practice in the surveyed clinics was significantly associated with presence of guidelines (AOR: 1.98, 95% CI: 1.06, 3.69), budget allocation (AOR: 2.05, 95%, CI: 1.20, 3.49), and inspection by the regulatory bodies (AOR: 2.47, 95% CI: 1.26, 4.84).

CONCLUSION

Healthcare waste management practice was poor in the surveyed clinics. This suggests that the healthcare industries in the studied region may create health treats to healthcare workers, waste handlers, patients, the community, and the environment at large. The following key elements are needed to improve healthcare waste management practices in private clinics: promoting practices that reduce the volume of waste generated and ensure proper waste segregation; developing strategies and systems, as well as strong oversight and regulation, to incrementally improve waste segregation, destruction, and disposal practices with the ultimate goal of meeting national and international standards; and selecting safe and environmentally-friendly management options, to protect people from hazards when collecting, handling, storing, transporting, treating or disposing of waste.

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.

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.