Globally increasing antibiotic resistance (AR) will only be reversed through a suite of multidisciplinary actions (One Health), including more prudent antibiotic use and improved sanitation on international scales. Relative to sanitation, advanced technologies exist that reduce AR in waste releases, but such technologies are expensive, and a strategic approach is needed to prioritize more affordable mitigation options, especially for Low- and Middle-Income Countries (LMICs). Such an approach is proposed here, which overlays the incremental cost of different sanitation options and their relative benefit in reducing AR, ultimately suggesting the “next-most-economic” options for different locations. When considering AR gene fate versus intervention costs, reducing open defecation (OD) and increasing decentralized secondary wastewater treatment, with condominial sewers, will probably have the greatest impact on reducing AR, for the least expense. However, the best option for a given country depends on the existing sewerage infrastructure. Using Southeast Asia as a case study and World Bank/WHO/UNICEF data, the approach suggests that Cambodia and East Timor should target reducing OD as a national priority. In contrast, increasing decentralized secondary treatment is well suited to Thailand, Vietnam and rural Malaysia. Our approach provides a science-informed starting point for decision-makers, for prioritising AR mitigation interventions; an approach that will evolve and refine as more data become available.

The treatment performance of small wastewater treatment plants (WWTPs) is not well understood, and their ecological impact may be underestimated. Growing evidence suggests they play a critical role in ensuring sustainable wastewater management, meaning they can no longer be neglected. The aim of this study was to provide new data, understanding, and analytical approaches to improve the management of existing small WWTPs. A one-year sampling campaign was performed in the rural UK, and we found the effluent quality from twelve small versus three larger WWTPs was significantly poorer (p < 0.05) across a range of performance parameters. Specifically, mean removal rates at the small plants were 67.3 ± 20.4%, 80 ± 33.9%, and 55.5 ± 30.4% for soluble chemical oxygen demand (sCOD), total suspended solids (TSS), and NH₄-N (± standard deviation), respectively, whereas equivalent rates for larger plants were 73.3 ± 17.6%, 91.7 ± 4.6%, and 92.9 ± 3.7%. A random forest classification model was found to accurately predict the likelihood of smaller WWTPs becoming unreliable. Importantly, when condensed to the three most ‘important’ predictors, the classifier retained accuracy, which may reduce the data requirements for effective WWTP management. Among the important predictors was population equivalence, suggesting the smallest WWTPs may require particularly stringent management. Growing awareness of the need for sustainable wastewater and water resources management makes this new approach both timely and widely relevant.