Background: Wastewater-based epidemiology (WBE) has become crucial for early microbial outbreak detection and public health surveillance globally, underscored by the COVID-19 pandemic. However, despite advancements in sampling and analyses, interpreting results and estimating infection rates pose challenges. Enhancements in sewer system engineering, understanding the wastewater environment, and addressing the impact of the environment on the accuracy of results are needed. Objective: This scoping review aims to identify engineering knowledge gaps in WBE to guide future study designs. Design: Research on “wastewater-based epidemiology” involving “engineering”, published between 2015 and 2023, was extracted from the Scopus database. Results: This scoping review examines elements influencing WBE’s precision and reliability, especially in identifying and measuring SARS-CoV-2 RNA. It identifies significant effects of engineering, analytical practices, and the wastewater’s composition on WBE performance. Conclusions: This review calls for further investigation into economical evaluation methods of these factors to enhance WBE data normalization and interpretation, utilizing existing wastewater treatment plant data used for treatment control, which could be a cost-effective approach over more expensive population biomarkers. This approach, aside from SARS-CoV-2, holds potential for application to a broader number and types of diseases, as well as population consumption habits.

The effluent from wastewater treatment plants (WWTPs) is a primary source of pharmaceuticals in aquatic systems. The ongoing challenge of managing pharmaceuticals in wastewater highlights the need for advanced treatment techniques and constant monitoring. Despite ongoing research, no current technologies can achieve 100% removal of all pharmaceuticals, while certain compounds persist through both conventional and advanced processes. A possible solution is to enhance WWTPs by incorporating additional tertiary and post-treatment methods such as combining treatment methods, e.g., fungal treatment with activated carbon. Filamentous fungi possess several characteristics including the ability to degrade and adsorb pharmaceutical substances. This article reviews filamentous fungi with conventional and advanced wastewater treatment methods, evaluating their efficacy and sustainability in removing pharmaceutical substances. Additionally, a qualitative environmental impact assessment based on available life-cycle assessment literature on fungal treatment systems for pharmaceutical substances was conducted, highlighting both environmental impacts and potential benefits. To better understand the wastewater management of advanced wastewater treatment methods for pharmaceutical removal, the European legislation governing hazardous substances was analyzed. This critical review aims to provide insights into optimizing fungal-based treatment systems and identify future research directions to enhance the integration of fungal-based methods into existing wastewater treatment plants for pharmaceutical removal.

Antimicrobial resistance (AMR) poses a global health threat, with urban wastewater systems serving as key reservoirs for resistance dissemination. This study aimed to investigate the relationships among urban environments, bacterial communities, and AMR patterns, and evaluate the specific municipal-scale drivers of resistance gene distribution. Shotgun metagenomic analysis was conducted on 45 wastewater samples collected from 15 municipalities across Latvia to determine the composition of the resistome and its correlation with local factors. The analysis identified 417 distinct antibiotic resistance genes (ARGs) belonging to 108 families, with geographic location serving as the primary driver of ARG distribution, which explained 65.87% of community variation (p = 0.001). Local industrial factors demonstrated significant effects, with food industry wastewater significantly influencing both bacterial taxonomy and ARG profiles (p < 0.05). While the presence of a regional hospital did not shape the overall municipal resistome, hospital-associated wastewater showed 19 overlapping ARGs, including clinically critical carbapenemases. Municipal wastewater systems function as geographically structured reservoirs of AMR that are shaped by localized industrial and healthcare outputs. These findings support wastewater-based AMR surveillance as a valuable tool for tracking specific resistance sources.

Antimicrobial resistance (AMR) poses a global health threat, with urban wastewater systems serving as key reservoirs for resistance dissemination. This study aimed to investigate the relationships among urban environments, bacterial communities, and AMR patterns, and evaluate the specific municipal-scale drivers of resistance gene distribution. Shotgun metagenomic analysis was conducted on 45 wastewater samples collected from 15 municipalities across Latvia to determine the composition of the resistome and its correlation with local factors. The analysis identified 417 distinct antibiotic resistance genes (ARGs) belonging to 108 families, with geographic location serving as the primary driver of ARG distribution, which explained 65.87% of community variation (p = 0.001). Local industrial factors demonstrated significant effects, with food industry wastewater significantly influencing both bacterial taxonomy and ARG profiles (p < 0.05). While the presence of a regional hospital did not shape the overall municipal resistome, hospital-associated wastewater showed 19 overlapping ARGs, including clinically critical carbapenemases. Municipal wastewater systems function as geographically structured reservoirs of AMR that are shaped by localized industrial and healthcare outputs. These findings support wastewater-based AMR surveillance as a valuable tool for tracking specific resistance sources.

Diagram showing how population, weather and urban activities influence wastewater composition, where parameters BOD5, COD, N, NH4-N, P and PO4-P are analysed to support wastewater-based epidemiology normalization. Wastewater-based epidemiology uses data from wastewater treatment plants to monitor the health of a population, but requires accurate normalization to provide per-capita, or individual-based, health indicators. This study assessed the long-term stability and suitability of key wastewater parameters for population normalization using data from 45 treatment plants across Latvia over a ten-year period, representing two-thirds of the national population. Specific pollutant loads were calculated for biochemical oxygen demand, chemical oxygen demand, total nitrogen, ammonium nitrogen, total phosphorus, and orthophosphate. Overall, pollutant loads remained stable during the study period, though an increase was observed in recent years, with ammonium rising by 27%, total nitrogen by 15%, and phosphorus by 11%. Industrial plants consistently showed higher pollutant loads than municipal facilities. Nitrogen exhibited the lowest variability among the evaluated hydrochemical parameters, suggesting its suitability as a robust normalization indicator within the studied dataset, while chemical oxygen demand can serve as a supporting indicator. In contrast, biochemical oxygen demand and phosphorus were less suitable due to operational sensitivity and high variability. The study recommends using rolling, plant-specific median values over two to three years to enhance the precision and comparability of population-normalized wastewater-based health assessments.