Infectious diseases are acknowledged as one of the most critical threats to global public health today. Climate change, unprecedented population growth with accelerated rates of antimicrobial resistance, have resulted in both the emergence of novel pathogenic organisms and the re-emergence of infections that were once controlled. The consequences have led to an increased vulnerability to infectious diseases globally. The ability to rapidly monitor the spread of diseases is key for prevention, intervention and control, however several limitations exist for current surveillance systems and the capacity to cope with the rapid population growth and environmental changes. Wastewater-Based Epidemiology (WBE) is a new epidemiology tool that has potential to act as a complementary approach for current infectious disease surveillance systems and an early warning system for disease outbreaks. WBE postulates that through the analysis of population pooled wastewater, infectious disease and resistance spread, the emergence of new disease outbreak to the community level can be monitored comprehensively and in real-time. This manuscript provides critical overview of current infectious disease surveillance status, as well as it introduces WBE and its recent advancements. It also provides recommendations for further development required for WBE application as an effective tool for infectious disease surveillance.

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Increasing usage of antimicrobials is a significant contributor to the emergence and dissemination of antimicrobial resistance. Wastewater-based epidemiology is a useful tool for evaluating public health, via the monitoring of chemical and biological markers in wastewater influent, such as antibiotics. Chemical analyses are used to determine sampled drug concentrations; measured daily flows then enable quantitation of analyte mass/day; and population estimates are utilised to calculate mass/day/1000inhabitants. These data allow for effective evaluations of drug presence and temporal trends, but do not fully represent the total quantity of drugs being consumed, i.e., human intake. Factors such as drug metabolism and physiochemical stability significantly decrease the quantity of parent drug that reaches wastewater treatment plants, leading to potential underestimations of community usage. A case study of 16 antimicrobials, and their metabolites was conducted in this study: including sulfonamides, trimethoprim, metronidazole, quinolones, nitrofurantoin, cyclines, and antiretrovirals. Correction factors (CFs) for human drug excretion, for various metabolite forms, were determined via a systematic literature review of pharmacokinetic research. Analyte stability was examined over a 24 h study. The estimation of community-wide drug intake was evaluated using the associated catchment prescription data. Overall, antimicrobials excreted in an unchanged form were often observed to over-estimate daily intake. This could be attributed to biotransformation, e.g., via glucuronide cleavage, or direct disposal of unused drugs. Acetyl-sulfonamides, trimethoprim, hydroxy-metronidazole, clarithromycin, ciprofloxacin, ofloxacin, tetracycline, and oxytetracycline generally performed well in the estimation of drug intake, relative to prescription records. The low prevalence of quinolone and trimethoprim metabolites, and the low stability of nitrofurantoin, limited the ability to evaluate these metabolites and their respective CFs. CFs established in the systematic literature review could not be validated for some metabolites in the case study due to lack of available prescription data (lamivudine, emtricitabine); an inability to quantify biomarkers (nitrofurantoin, doxycycline); being excreted at too low levels (hydroxy-trimethoprim, ofloxacin-N-oxide, desethylene-ciprofloxacin); or insufficient pharmacokinetic literature sources (the nitrofurantoin metabolite, NPAHD). Further work is currently underway to apply established CFs in other catchment with higher prevalence of antimicrobials usage.

We systematically reviewed studies using wastewater for AMR surveillance in human populations, to determine: (i) the strength of the evidence for a wastewater-human AMR association, and (ii) methodological approaches which optimised identifying such an association, and which could be recommended as standard. We used Lin’s concordance correlation coefficient (CCC) to quantify agreement between AMR prevalence in wastewater and human compartments, and logistic regression to identify study features (e.g. sampling methods) associated with high-agreement (defined as wastewater-human AMR prevalences within ±10%). Of 8,867 records and 232 full-text methods reviewed, 29 studies were included. AMR prevalence data was extractable from 20 studies conducting phenotypic-only (n=11), genotypic-only (n=1) or combined (n=8) AMR detection. Overall wastewater-human AMR concordance was reasonably high for both phenotypic (CCC=0.81 [95% CI 0.74-0.87]) and genotypic comparisons (CCC=0.88 (95% CI 0.85-0.91)) despite diverse species-phenotypes/genotypes and study design. Logistic regression was limited by inconsistent reporting of study features, and limited sample size; no significant relationships between study features and high wastewater-human AMR agreement were identified. Based on descriptive synthesis, composite/flow-proportional sampling of wastewater influent, longitudinal sampling >12 months, and time/location-matched comparisons generally had higher-agreement. Further research and clear and consistent reporting of study methods is required to confirm optimal practice.

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