Wastewater surveillance (WWS) has emerged as a powerful population-level approach for monitoring public health by capturing chemical and biological signals shed by communities. By analysing municipal wastewater, this approach enables non-invasive tracking of infectious diseases, antimicrobial resistance (AMR), and community exposure to environmental contaminants. Its importance was clearly demonstrated during the COVID-19 pandemic, where SARS-CoV-2 RNA was detected in wastewater prior to reported clinical cases, which highlights its role as an early warning system. This review brings together recent advances in WWS, focusing on its applications in infectious disease monitoring, AMR surveillance, and One Health-based exposure assessment. Attention is given to the movement and transformation of biomarkers across environmental matrices and their interpretation in relation to population health. The review also explores recent developments in analytical methods, including digital PCR, metagenomics, and biosensor-based approaches. At the same time, several challenges continue to limit large-scale implementation, including variability in sampling strategies, lack of standardized protocols, uncertainties in population estimation, and difficulties in linking wastewater signals to epidemiological outcomes. By connecting these methodological limitations with interpretation challenges, this review suggests key gaps that need to be addressed. Future efforts should focus on developing balanced monitoring frameworks, improving data integration with clinical surveillance, and strengthening interdisciplinary collaboration.