The evolutionary path of medical waste management research: Insights from co-citation and co-word analysis

Over the past decades, medical waste management (MWM) has evolved into a paramount global challenge, intertwining environmental sustainability and public health dimensions. This manuscript traces the paradigm shift from the foundational Basel Convention of 1989 to the significant sway of World Health Organization publications on contemporary debates. Utilizing a mixed approach strategy that blended qualitative and quantitative techniques, the research employed extensive literature review, co-citation and co-word analysis methodologies to ascertain the direction of contemporary trends in MWM. Within the scope of the research findings, current strategies reveal noticeable gaps, especially those that lack sound policy structures, comprehensive insights and effective operational frameworks. Co-citation evaluations spotlight predominant themes in academic references. Foremost among them are the socioeconomic factor, environmental significance, medical waste (MW) stabilization and sustainable society, sequenced by cluster magnitude. Co-word analysis unveils that, despite the long-standing presence of incineration plants, pyrolysis has, since 2016, prioritized environmental considerations. The recycling ethos peaked in 2014, but the sustainability paradigm burgeoned in 2020, with the 'circular economy' gaining momentum in 2021. Emerging trend analysis underscores the mounting significance of circular waste technologies and sustainability as indispensable solutions. Results demonstrate MW advancements and highlight emerging trends shaping the future of the field. The research concludes by accentuating the necessity of global collaborative efforts, integrating cutting-edge technologies and infusing sustainability and circularity tenets into societal frameworks to navigate MWM's intricate landscape. Future research trajectories, including wastewater governance, novel mobile waste disposal strategies and a cyclic waste classification paradigm, are proposed.