Wastewater Surveillance of Antimicrobial Resistance in Human Populations: A Systematic Review

Abstract

Wastewater-based surveillance of antimicrobial resistance (AMR) may facilitate convenient monitoring of population-level AMR prevalence without the healthcare-associated bias and data collection restrictions inherent to clinically oriented systems. However, differences in study design and methodology likely contribute to differences in outcomes and interpretation, limiting reproducibility, reliability and meta-analysis. We therefore systematically reviewed studies using wastewater for AMR surveillance in human populations to identify optimal practices to detect wastewater-human AMR correlations. We evaluated 7,063 records and 174 full-text methods in a two-stage screen; 20 studies were included. Risk of bias assessment divided studies into high-risk (n=3), low-risk (n=3) and unclear-risk (n=14). Most studies detected wastewater-human AMR correlations (n=15) but only six studies identified statistically significant associations, most via culture-independent approaches (n=5). Genomic approaches also facilitated higher-resolution AMR monitoring whereas culture-based studies primarily undertook observational comparisons of specific organisms and phenotypic AMR profiles. Studies identifying wastewater-human AMR correlations were consistently associated with sampling wastewater influent irrespective of other methodological approaches. For longitudinal studies, a timeframe of >=6 months was similarly associated. Most influent studies identifying wastewater-human AMR correlations used composite (n=5) or flow-proportional wastewater sampling methods (n=4); however, grab sampling was commonest overall (n=6) and generally appeared similarly effective.Wastewater-based surveillance of AMR in human populations appears relatively robust, with most included studies reporting a correlation despite high diversity in study design and methodology. Our review supports sampling of wastewater influent using composite sampling (at a minimum) as a standard. Impacts of other methodological approaches are less clear; however, a minimum timeframe of six months for longitudinal studies, and increased sampling coverage for culture-independent studies to enable adequate biostatistical analyses appear sensible. As this relatively new field grows, more studies with clear wastewater-based population-level AMR surveillance aims are needed to better determine the impact of confounding features and validate comprehensive “best practice” protocols.

Secrets of the Hospital Underbelly: Patterns of Abundance of Antimicrobial Resistance Genes in Hospital Wastewater Vary by Specific Antimicrobial and Bacterial Family

“…The use of metagenomics is a key strength of this study, allowing quantification of resistance genes to a wide range of antibiotics and retrospective investigation if new resistance genes emerge. The 24-h composite samplers provide a representative sample of the hospital (Chau et al, 2020), although hospital staff, outpatients, and visitors will have also contributed to the effluent. In addition, some patients will have moved around the hospital during the sampling period.…”

Secrets of the hospital underbelly: patterns of abundance of antimicrobial resistance genes in hospital wastewater vary by specific antimicrobial and bacterial family

“…The use of metagenomics is a key strength of this study, allowing quantification of resistance genes to a wide range of antibiotics and retrospective investigation if new resistance genes emerge. The 24-hour composite samplers provide a representative sample of the hospital (Chau et al 2020), although hospital staff, outpatients and visitors will have also contributed to the effluent. In addition, some patients will have moved around the hospital during the sampling period.…”