Sept. 28, 2020
Environmental engineer and team monitor community health in Detroit
Associate Professor Irene Xagoraraki and her students (Brijen Miyani, Liang Zhao and Maddie Spooner) in the Department of Civil and Environmental Engineering at Michigan State University are working with collaborators John Norton - Director of Energy - Research and Innovation of the Great Lakes Water Authority, Anna Mehrotra - Senior Process Engineer with CDM Smith, and Anil Gosine - Program Manager - Office of Deputy Director, City of Detroit Water and Sewerage Dept., to identify upcoming viral outbreaks and predict temporal and spatial fluctuations of COVID-19 in Detroit and Wayne Macomb and Oakland Counties.
Testing in her laboratory gave early warnings of temporal fluctuations of COVID-19 in April and May, described in published paper (Miyani B., Fonoll X., Norton J., Mehrotra A., Xagoraraki I. (2020) SARS-CoV-2 in Detroit Wastewater. Journal of Environmental Engineering, 146(11): 06020004). Recently, the team predicted the second wave of COVID-19 that took place in July in the Detroit area two weeks in advance (data submitted for publication).
“Wastewater surveillance is getting a lot of attention recently, but this approach needs to go beyond simple testing of wastewater if prediction and issuing of early warnings is the goal,” she explained.
Learn more about how Xagoraraki and her students conduct community composite samples work in this video.
Effective sample collection is critical. Beyond that, effective sample pretreatment, concentration, and genetic testing of environmental samples – which are more complex than clinical samples – are important.
The methods need to be able to detect viruses at very low concentrations, before the outbreak is at its peak and before the samples are full of viral particles, if prediction of upcoming disease is required. The process includes a series of steps for viral-selective sampling, elution, concentration, DNA/RNA extraction, inhibition control, and final detection that all need to be optimized to provide signals at very low concentrations – as low as few viral particles in gallons of water, she continued.
When the virus of concern is known, such as SARS-CoV-2, primers and probes are designed to target that particular virus. Positive and negative standards are used to produce standard curves for QA/QC purposes. Sequencing and bioinformatics tools can be used to identify virus-related genes and viral diversity, that will give indications of upcoming novel diseases.
In the newly published editorial (Xagoraraki I., (2020) Can we predict viral outbreaks using wastewater surveillance? Journal of Environmental Engineering, 146(11): 01820003) and a book chapter (Xagoraraki I., O’Brien E. (2020) Wastewater-Based Epidemiology for Early Detection of Viral Outbreaks. In: Women in Water Quality (O’Bannon D., Editor): Women in Engineering and Science, Springer Nature, Switzerland, Xagoraraki writes that:
“A critical step in this research and management approach is the determination of the relationship between measured viral concentrations in wastewater and viral disease incidence in the community. To determine this relationship and forecast/predict viral disease fluctuations in the community over space and time, multiple measurements and data need to be taken into account.”
For example, she said it is critical to estimate the dilution, fate and detention times of viruses in the collection network using hydrological and other network data. It is also important to estimate the contributing population. The models also need to include disease characteristics, such as incubation times, shedding duration, and shedding rates, in addition to anthropometric data of the serviced population.
Xagoraraki said that the team is building and testing mechanistic/deterministic and statistical models to relate all of these parameters and processes. The team is working with City and County epidemiologists to select appropriate clinical data for validation of their models.
Their models describe patterns of endemic disease, identify potential novel viruses, and forecast hot spots and critical moments for the onset or spread of outbreaks prior to the full-blown demonstration of disease in clinical settings.
Funded by the National Science Foundation, Xagoraraki began working in Detroit in 2017.
Since 2017, the team (including recently graduated students Camille McCall, Huiyun Wu and Evan O’Brien) has detected viruses that go beyond SARS-CoV-2 – a finding that is advancing the early-warning health monitoring in the Detroit area based on wastewater surveillance. The team was able to identify a number of enteric, respiratory, bloodborne and vector-borne viruses ranging from norovirus to hepatitis and HIV-AIDS. The latter two related to outbreaks in Detroit that occurred during their sampling period. The results can be found in a published paper (McCall C., Wu H., Miyani B., Xagoraraki I. (2020) Identification of Multiple Potential Viral Diseases in a Large Urban Center using Wastewater Surveillance. Water Research, 184: 116160).
The research team learned they can identify multiple viral infections by using multiple confirming methods and by cross checking public health records reported by the State of Michigan against signals of genetic sequences found in wastewater in Detroit, Wayne, Macomb and Oakland counties. They have even been able to distinguish between strains of coronaviruses that cause the common cold HKU1, or strains such SARs-CoV-2 that cause COVID-19.
In collaboration with local department epidemiologists, Xagoraraki and her team are now expanding monitoring to target specific districts (within Wayne, Macomb and Oakland Counties) with different demographics and patterns of disease.
“Our united effort includes engineers, hydrologists, GIS specialists, molecular microbiologists, epidemiologists and data science specialists,” she added. “It is worth the collaboration and scientific exploration.”
