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Maria made a landfall in Puerto Rico on September 20, 2017 as a category 4 hurricane, causing severe flooding, widespread electricity outages, damage to infrastructure, and interruptions in water and wastewater treatment. Small rural community water systems face unique challenges in providing drinking water, which intensify after natural disasters. The purpose of this study was to evaluate the functionality of six very small rural public water systems and one large regulated system in Puerto Rico six months after Maria and survey a broad sweep of fecal, zoonotic, and opportunistic pathogens from the source to tap. Samples were collected from surface and groundwater sources, after water treatment and after distribution to households. Genes indicative of pathogenic Leptospira spp. were detected by polymerase chain reaction (PCR) in all systems reliant on surface water sources. Salmonella spp. was detected in surface and groundwater sources and some distribution system water both by culture and PCR. Legionella spp. and Mycobacteria spp. gene numbers measured by quantitative PCR were similar to nonoutbreak conditions in the continental U.S. Amplicon sequencing provided a nontarget screen for other potential pathogens of concern. This study aids in improving future preparedness, assessment, and recovery operations for small rural water systems after natural disasters.

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA genenormalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolidelincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.

Wastewater-based epidemiology (WBE) for disease monitoring is highly promising, but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. We demonstrate a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage, enabling assessment of: 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends including antibiotic concentrations in sewage. Across an internationally-sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Sales data were not predictive of antibiotics measured in sewage, emphasizing need for direct measurements. The WBE approach defined herein demonstrates multi-site comparability and sensitivity to local/regional factors.