Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g.

Identifying sources of antibiotic resistance genes in the environment using the microbial , and framework.

Introduction: Antimicrobial resistance (AMR) is an increasing public health concern for humans, animals, and the environment. However, the contributions of spatially distributed sources of AMR in the environment are not well defined.

Methods: To identify the sources of environmental AMR, the novel microbial Find, Inform, and Test (FIT) model was applied to a panel of five antibiotic resistance-associated genes (ARGs), namely, erm(B), tet(W), qnrA, sul1, and intI1, quantified from riverbed sediment and surface water from a mixed-use region.

Assessing Residential Exposure to Microbes from Industrial Hog Operations in Rural North Carolina: Methods and Lessons Learned.

Background: Recent advances in molecular source tracking make answering questions from residents regarding their exposure to microbial contaminants from industrial hog operations (IHOs) possible. Associations between residential distance to IHOs and exposure can be addressed by measuring livestock-associated (Staphylococcus aureus) and pig-specific bacteria in the air, on household surfaces, and in participants' nasal and saliva swabs.

Objectives: Here we assess the mechanics, feasibility, capacity-building, and lessons learned during a pilot study employing this novel technology in community-based participatory research of bacterial exposure and human health.

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework.

Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water.

Microbial Find, Inform, and Test Model for Identifying Spatially Distributed Contamination Sources: Framework Foundation and Demonstration of Ruminant Abundance in River Sediments.

Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) help to assess the microbial risks by linking hosts to contamination but do not identify the source locations. Land-use regression (LUR) models have been used to screen the source locations using spatial predictors but could be improved by characterizing transport (i.