Research Area
We use wastewater-based epidemiology to detect pathogen signals, understand disease burden, and support public health decision-making across scales.
Wastewater-based epidemiological surveillance provides a community-level tool for monitoring infectious agents shed into the sewer system by both symptomatic and asymptomatic individuals. Because wastewater combines inputs from residential areas, healthcare facilities, schools, workplaces, travel hubs, and other community settings, it can provide an integrated picture of infection trends across a defined catchment population.
As wastewater moves through the sewer network, the signal can be influenced by factors such as stormwater dilution, industrial flow, travel time, temperature, and solids content. Samples may be collected at different scales, including buildings, neighborhoods, pump stations, manholes, or wastewater treatment plant influent, depending on the surveillance question.
In the laboratory, samples are concentrated and analyzed using molecular methods such as qPCR, digital PCR, sequencing, or metagenomics. These data can support early warning, trend tracking, variant detection, outbreak response, and evaluation of public health interventions.
Overall, wastewater surveillance connects environmental sampling, laboratory analysis, and public health action to help detect infectious disease threats and protect communities.
Completed studies to (1) examine possible WWTP worker exposure to SARS-CoV-2, (2) determine viral presence across the treatment process from influent to effluent and in WWTP-generated bioaerosols, and (3) optimize the procedures and methods for state-wide surveillance across multiple WWTPs.
Learn more →Performed wastewater surveillance of SARS-CoV-2 at 12 locations across the USC campus to enhance the campus pandemic mitigation response.
Learn more →As Co-PI of the DMA-PRIME CDC Center, the lab serves as the wastewater core and provides routine wastewater surveillance of a number of respiratory viruses, STIs, measles, mpox, and TB. Data are used in the development of disease forecasting and transmission models.
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