Mapping healthcare waste management research: Past evolution, current challenges, and future perspectives towards a circular economy transition

Improper healthcare waste (HCW) management poses significant risks to the environment, human health, and socio-economic sustainability due to the infectious and hazardous nature of HCW. This research aims at rendering a comprehensive landscape of the body of research on HCW management by (i) mapping the scientific development of HCW research, (ii) identifying the prominent HCW research themes and trends, and (iii) providing a research agenda for HCW management towards a circular economy (CE) transition and sustainable environment. The analysis revealed four dominant HCW research themes: (1) HCW minimization, sustainable management, and policy-making; (2) HCW incineration and its associated environmental impacts; (3) hazardous HCW management practices; and (4) HCW handling and occupational safety and training. The results showed that the healthcare industry, despite its potential to contribute to the CE transition, has been overlooked in the CE discourse due to the single-use mindset of the healthcare industry in the wake of the infectious, toxic, and hazardous nature of HCW streams. The findings shed light on the HCW management domain by uncovering the current status of HCW research, highlighting the existing gaps and challenges, and providing potential avenues for further research towards a CE transition in the healthcare industry and HCW management

DNA commission of the International Society of Forensic Genetics: Recommendations on the evaluation of STR typing results that may include drop-out and/or drop-in using probabilistic methods

DNA profiling of biological material from scenes of crimes is often complicated because the amount of DNA is limited and the quality of the DNA may be compromised. Furthermore, the sensitivity of STR typing kits has been continuously improved to detect low level DNA traces. This may lead to (1) partial DNA profiles and (2) detection of additional alleles. There are two key phenomena to consider: allelic or locus 'drop-out', i.e. 'missing' alleles at one or more genetic loci, while 'drop-in' may explain alleles in the DNA profile that are additional to the assumed main contributor(s). The drop-in phenomenon is restricted to 1 or 2 alleles per profile. If multiple alleles are observed at more than two loci then these are considered as alleles from an extra contributor and analysis can proceed as a mixture of two or more contributors. Here, we give recommendations on how to estimate probabilities considering drop-out, Pr(D), and drop-in, Pr(C). For reasons of clarity, we have deliberately restricted the current recommendations considering drop-out and/or drop-in at only one locus. Furthermore, we offer recommendations on how to use Pr(D) and Pr(C) with the likelihood ratio principles that are generally recommended by the International Society of Forensic Genetics (ISFG) as measure of the weight of the evidence in forensic genetics. Examples of calculations are included. An Excel spreadsheet is provided so that scientists and laboratories may explore the models and input their own data. (C) 2012 Elsevier Ireland Ltd. All rights reserved