A review on medical waste treatment in COVID-19 pandemics: Technologies, managements and future strategies
Bibliographic record
Abstract
Since the outbreak of COVID-19 few years ago, the increasing of the number of medical waste has become a huge issue because of their harmful impact to environment. A major concern associated to the limitation of technologies for dealing with medical waste, especially conventional technologies, are overcapacities since pandemic occurs. Moreover, the outbreak of new viruses from post COVID-19 should become a serious attention to be prevented not only environmental issues but also the spreading of viruses to new pandemic near the future. The high possibility of an outbreak of new viruses and mutation near the future should be prevented based on the experience associated with the SARS-CoV-2 virus in the last three years. This review presented information and strategies for handling medical waste during the outbreak of COVID-19 and post-COVID-19, and also information on the current issues related to technologies, such as incineration, pyrolysis/gasification, autoclaves and microwave treatment for the dealing with high numbers of medical waste in COVID-19 to prevent the transmission of SARS-CoV-2 virus, their advantages and disadvantages. Plasma technology can be considered to be implemented as an alternative technology to deal with medical waste since incinerator is usually over capacities during the pandemic situation. Proper treatment of specific medical waste in pandemics, namely face masks, vaccine vials, syringes, and dead bodies, are necessary because those medical wastes are mediums for transmission of the SARS-CoV-2 virus. Furthermore, emission controls from incinerator and plasma are necessary to be implemented to reduce the high concentration of CO2, NOx, and VOCs during the treatment. Finally, future strategies of medical waste treatment in the perspective of potential outbreak pandemic from new mutation viruses are discussed in this review paper.Statement of Environmental Implication Journal of the air and waste management association may consider our review paper to be published. In this review, we give important information related to the technologies, managements and strategies for handling the medical waste and control the transmission of SARS-CoV-2 virus, starting from proper technology to control the high number of medical waste, their pollutants and many strategies for controlling the spreading of SARS-CoV-2 virus. Moreover, this review also describes some strategies associated with control the transmission not only the SARS-CoV-2 virus but also the outbreak of new viruses near the future.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".