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COVID-19 has swept across the globe and disrupted all vectors of social life. Every informed measure must be taken to stop its spread, bring down number of new infections and move to normalization of daily life. Contemporary research has not identified waste management as one of the critical transmission vectors for COVID-19 virus. However, most underdeveloped countries are facing problems in waste management processes due to the general inadequacy and inability of waste management. In that context, smart intervention will be needed to contain possibility of the COVID-19 spread due to inadequate waste management. This paper presents a comparative study of the artificial intelligence/ machine learning based techniques, and potential applications in the COVID-19 waste management cycle (WMC). A general integrated solid waste management (ISWM) strategy is mapped for both short-term and long-term goals of COVID-19 WMC, making use of the techniques investigated. By aligning current health/waste-related guidelines from health organizations and governments worldwide and contemporary, relevant research in area, the challenge of COVID-19 waste management and, subsequently, slowing the pandemic down may be assisted.