What is VirusWatch?

VirusWatch is creating a web application that can host and compare any type of viral surveillance data so that we can determine how far in advance wastewater surveillance can “alert” stakeholders of an upcoming outbreak. Our project is to create a web application for Dr. Crystal Hepp (Assistant Professor at the School of Informatics, Computing, and Cyber Systems). The goal of this project is to create a space that allows for data that is taken from the analysis of wastewater and convert it to a digestable format for agencies to use. This application would be useful as the current processing of information involves the manual delivery of data to respective agencies that can be expidited through a common host site for this information.

Who is our client?

Crystal Hepp is an infectious disease expert and currently works at the Institute of Pathogenic Microbiology at Northern Arizona University. A key challenge for her is being able to take the wastewater test data and translate it onto a streamlined and easily accessible platform. Currently, The data is distributed as manually formatted excel sheets to various agencies which is time consuming and slower to get the information to said agencies. The conclusion of the current experiment is that there is no risk of coronavirus in wastewater. Dr. Chrystal believes that total wastewater may be a powerful tool for public health testing.

What can we do to help?

Presently, we are collaborating with the City of Flagstaff, City of Sedona, Village of Oak Creek, Munds Park, Kachina Village, and Northern Arizona University to test their wastewater at various geographic scales to monitor the SARS-CoV-2 outbreak magnitude. However, the reports we submit to them are simple excel spreadsheets and charts that we recreate each week and submit. We would like to host a secure website, and possibly a mobile application, that would allow the different agencies we work with to login to see their own results as well as a few basic analyses that would allow them to compare (for example) case counts or percent seropositivity to a quantitative wastewater signal.

We envision a website (secure web app) that can host and compare any type of surveillance data (e.g. case counts, % positive, wastewater signal, viral copies per sample) so that we can determine how far in advance wastewater surveillance can “alert” stakeholders of an upcoming outbreak. We would additionally generate an automated basic caption that would tell stakeholders what the data means overall and for the most recent epidemiological week. Finally, we would like policy-makers to have the ability to provide date-labelled annotations to describe interventions they are implementing, which would help explain the wastewater signal over time.