Socioeconomic indicators are more strongly associated with the global wastewater core microbiome than geography

Municipal wastewater harbors microbial communities that are essential for treatment performance and increasingly valuable for population-level public health surveillance. However, the globally persistent bacterial and archaeal taxa in raw wastewater influents and the large-scale factors associated with their distribution remain poorly resolved. Here, we analyzed publicly available shotgun metagenomic sequencing reads from 662 raw influent wastewater samples, representing 220 city-level sampling locations across 97 countries between 2017 and 2019, to characterize the global bacterial and archaeal core microbiome. Taxonomic profiles were generated using a standardized bioinformatics workflow, and core taxa were identified using prevalence, mean relative abundance, and contribution to the dominant fraction of community abundance. We identified a compact core representing only 2.4% of detected genera yet accounting for 69% of total microbial abundance. The 55 core genera were exclusively bacterial and were dominated by Comamonadaceae, Moraxellaceae, and Pseudomonadaceae, with Pseudomonas , Acidovorax , and Acinetobacter among the most abundant genera. Biogeographical analyses showed that North America and Europe had highly similar core microbiome compositions, whereas South America and Oceania were more distinct. Altitude showed the strongest and most consistent association among the examined geographic variables (R 2 = 0.121–0.193), whereas latitude showed no significant association with alpha diversity. Core microbiome composition was also associated with country-level socioeconomic indicators, providing statistical support for the socioeconomic filtering hypothesis. Structural equation modeling suggested that socioeconomic indicators explained genus-level abundance variation more strongly than geographic variables for over half of all core taxa (56%) and for 75% of taxa with substantial model explanatory power (R 2 > 0.200). These findings provide a global baseline for interpreting large-scale variation in wastewater influent microbial communities and highlight the value of integrating microbiome profiling with geographic and socioeconomic context.