Fecal contamination and water quality

The paper identifies a single capsid residue in Echovirus 11 that determines its susceptibility to proteolytic inactivation in freshwater.

This study examines how zooplankton affect virus inactivation under sunlight and darkness, finding species-specific impacts on virus removal rates.

This paper develops a method for detecting protozoa, bacteria, and viruses in water using membrane adsorption and direct nucleic acid extraction, showing improved sensitivity for several pathogens.

The paper uses microbial source tracking markers to identify human and animal fecal contamination in Ecuadorian households, finding that caregiver hand contamination is linked to child contamination.

MicrobiomePrime identifies primer pairs for microbial source tracking by analyzing amplicon sequences, achieving high specificity in laboratory validation.

This study evaluates two passive samplers for detecting fecal pollution markers in an urban river, showing they accumulate significantly more target genes than grab samples.

This paper optimizes triplex digital PCR assays for microbial source tracking in surface waters, showing comparable results to single-plex assays.

This study compares five viral concentration methods in wastewater to identify which best capture diverse viral taxa for metagenomic analysis.

This study evaluates E. coli survival and removal on traditional and sustainable cement-based surfaces under field conditions, finding similar performance between fly ash and traditional mixes.

This study shows lognormal distributions accurately model enteric virus concentrations in wastewater, outperforming other distributions, and suggests weekly monitoring for effective and cost-effective tracking.

The paper demonstrates that aggregate-bound fecal indicator bacteria are significantly undercounted by traditional methods, leading to underestimated waterborne disease risks.

The paper curates nine genomic databases for fecal source tracking, summarizes their source-specificity, and tests their utility with mock water samples.

This study evaluates the impact of a sanitation intervention on enteric pathogen detection in soils in Maputo, finding a 15% reduction in pathogen presence but persistent contamination.

This paper develops a model using limited qPCR data and beach correlations to improve E. coli prediction at Chicago beaches, increasing sensitivity by 230%.