Systematic Review on Monitoring Antibiotic-resistant Pathogens in Wastewater

The World Health Organization identifies antimicrobial-resistance (AMR) among the top ten global health threats, potentially causing 10 million deaths annually by 2050. New global infections have created the need to track disease outbreaks and antibiotic-resistance to develop effective public health solutions. This systematic review aims to update the knowledge on antibiotic-resistant bacterial pathogens through wastewater surveillance carried out at different levels and geographical locations. The study initially screened 4467 articles based on the search criteria set for the current study after eliminating duplicates, review articles, systematic reviews, and articles published in languages other than English. Finally, we identified 156 articles, of which 53 were relevant articles for the systematic review and contained wastewater surveillance along with a comparison with clinical strains. After a careful review of the articles, we found two levels that were very important for antibiotic-resistance, one being the level of wastewater surveillance and the other being the method of screening for antibiotic- resistance, such as culture-based methods or genomic screening approaches. From these studies, we found that 52% were conducted at the single-sewer level, followed by clinical settings and international studies. Most international studies used the genomic screening approach, while, as regional studies, national-level studies used culture-based approaches. Although advanced genomic approaches, such as next-generation sequencing, offer greater advantages in predicting antibiotic-resistance genes and AMR surveillance, they cannot overcome the limitations associated with AMR monitoring, such as contamination from animal sources. Overall, this study indicates that the Enterobacteriaceae family is a highly evolving antibiotic-resistant pathogen, followed by the Enterococcaceae family. The use of research with clinical comparisons in wastewater surveillance avoids false-positive predictions and simplifies the process and interpretation of data.