Julien, Ryan

Ryan Julien's research focus has been pathogen risks arising from in-building plumbing. This includes quantitative microbial risk assessment (QMRA) for pathogens such as Legionella spp., identifying variables associated with elevated pathogen risks, and modeling in-building plumbing to assess hydraulic retention time. After receiving his PhD, Ryan has continued his work at MSU on a different project; managing the logistics and data analysis of a wastewater sampling effort to monitor the prevalence of SARS-CoV-2 on campus.

Titles from this speaker

Building-Level Wastewater Surveillance Modeling for SARS-CoV-2

Abstract

The COVID-19 pandemic has resulted in widespread illness, taken the lives of nearly five million people worldwide, and caused many other disruptions to daily life. The pandemic has also presented several challenges to disease surveillance and epidemiological risk mitigation. Addressing these challenges requires novel decision support methods to satisfy multiple and sometimes competing goals of risk reduction, securing private data, and preserving personal liberties. In this presentation, we will describe our contributions to the development of a SARS-CoV-2 wastewater surveillance monitoring program, subsequent data analyses to interpret results, and modeling to evaluate the predictability of this novel method that emerged during the pandemic. Weekly grab samples of wastewater were initiated in May 2020 for SARS-CoV-2 analysis at four locations. Three of these were on-campus building-level locations, with one off-campus catchment-level location. Preliminary results indicated elevated concentrations of SARS-CoV-2 co-occurring with new outbreaks in the community. As a result, sampling was continued through the Fall semester, expanding the program to monitor four specific residence halls at the building level. In January 2021, sampling was expanded to a total of six residence halls and one off-campus catchment-level location, sampling frequency was increased to twice weekly, and the temporal composition of these samples was modified with the installation of automatic composite samplers. The sampling protocol was again expanded in August 2021 to include a total of 18 composite samples at twice-weekly resolution. This included 15 on-campus locations yielding building-level samples and three off-campus catchment-level locations. Methods to model this type of data to establish public health implications are rapidly developing and have required ongoing research. Some preliminary approaches have been published to correlate wastewater concentrations with COVID-19 cases at the community level from samples taken at wastewater utility plants. These methods allow for a larger population (i.e. those contributing to wastewater) to be analyzed using a single test. Further, this style of testing captures results from communities without differentiating between symptomatic or asymptomatic cases. However, these methods have not been well-established at the building level where factors such as fluid mixing, transit time, sewer geometry, dilution with wastewater streams largely free of viral RNA (e.g. laundry), and more transient populations are assumed to negatively impact the interpretation of results. Additionally, fecal shedding rates SARS-CoV-2 variants are not well-established, potentially calling into question the application of preliminary models based on the original strain of the virus. To support decision-making on campus, we have created a data analysis plan using monitored wastewater concentrations and positive or presumptive cases identified through clinical sampling, screening-based saliva sampling, and contact tracing. Building-level data such as occupancy counts, the percentage of vaccinated residents, and building water use volume are being collected to better support modeling and interpretation of results. Wastewater samples are collected from manholes corresponding to building wastewater discharges, and analyzed for a variety of gene targets from known variants. We will present results of these analyses for data collected during the 2021 calendar year. Several analyses will be presented including (i) cross-correlation between wastewater signal and the number of known or presumptive cases contributing to samples; (ii) a Poisson regression to determine the predictability of the number of infections from wastewater concentrations; and (iii) variable selection to determine factors driving the relationship between case counts and wastewater signal which will best inform deterministic modeling. These results will provide a unique perspective into the challenges and benefits of conducting a wastewater surveillance program at the building-level, and will support future efforts to model case counts from building-level wastewater concentrations of the SARS-CoV-2 virus.

The following conference paper was presented at the Public Health and Water Conference & Wastewater Disease Surveillance Summit in Cincinnati, OH, March 21-24, 2022.

SpeakerJulien, Ryan

Presentation time

13:45:00

14:00:00

Session time

13:30:00

15:00:00

SessionExploring the Role of Various Models in Wastewater-Based Surveillance to Evaluate Epidemiological Control Strategies

Session number4

Session locationDuke Energy Convention Center, Cincinnati, Ohio

TopicModeling, Pathogens, Risk Management

Author(s)