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Covid-19 Research

Baskin Engineering Covid-19 Research Projects
Two researchers in a lab at UCSC are working on developing testing for COVID-19

When the COVID-19 pandemic hit, engineers at the University of California, Santa Cruz were eager to do their part to help. Over the past few months, they have made remarkable strides in rapidly shifting their resources and research expertise to address some of the most pressing problems of the current global crisis. Below are their current and developing projects.

Current Projects

The UCSC SARS-CoV-2 Genome Browser

Led by Maximilian Haeussler and Jim Kent at the UC Santa Cruz Genomics Institute, the coronavirus genome browser project will accelerate successful COVID-19 research by integrating into the UCSC Genome Browser all genetic information from existing resources related to SARS-CoV-2, the novel coronavirus that causes COVID-19. The Browser is an important resource for genomic researsch as it allows scientists to look at the virus’ structure so they can find ways to attack it. Read more.

  The UCSC Genome Browser for Covid-19

Creating rapid, low-cost serology tests

Nader Pourmand, professor of biomolecular engineering, is evaluating a serology testing platform derived from nanopipette technology developed in his lab. The new nanosensor technology could detect and quantify antibodies to the coronavirus in a finger-prick blood sample in less than a minute. He has received a $75,000 grant from the COVID Catalyst Fund established at UC Berkeley to further fund this research. Read more.


Video-assisted clinical care for remote management of COVID-19

Narges Norouzi, professor of computer science and engineering at UC Santa Cruz has partnered with Ian Julie at UC Davis on a project to demonstrate real-time analysis of video and the ability to identify clinically useful information from a live video stream to assist clinicians in the management of COVID-19 patients. Read more.


Genome Sequencing 

Mark Akeson, professor of biomolecular engineering, is working on rapid sequencing of coronavirus samples using the nanopore sequencing technology he helped pioneer. By sequencing virus samples taken at different times and places, researchers can track genetic changes and trace the spread of different strains of the virus. Read more.


Producing Coronavirus Antigens

Immunologic testing to determine if someone has already been exposed to the coronavirus requires coronavirus antigens. After learning that these antigens were in short supply, bioengineering professor Rebecca DuBois began production of them in her lab and will provide them for use by other researchers through a national repository maintained by the National Institutes of Health. Read more. 


Open-source 3D browser with virtual reality option for crowdsourcing COVID-19 data analysis

Electrical and computer engineering professor Mircea Teodorescu and computational media professor Sri Kurniawan are developing a web-based platform that enables crowdsourced analysis of COVID-19 data through browser-based 3D rendering with and without virtual reality. Read more.


Vine Robot for Automated Nasopharyngeal Swabbing

Electrical and computer engineering professor Gabriel Elkaim is collaborating with Dr. Lin Zhang of UC Davis Health to create a “vine” robot to collect nasal swabs, the perfered method of testing for Covid-19, without endangering healthcare workers. The tests are also being designed to be more comfortable for patients. Read more


 Developing Projects

Real-time learning network models of COVID-19 for prediction

Electrical and computer engineering professor Ricardo Sanfelice is working on creating mathematical models to describe the evolution of COVID-19 in various populations around the world and under different environmental conditions. The models will be capable of learning the dynamics and parameters of transmission of COVID-19 using real-time information about COVID-19 cases and their evolution. The models will describe the infection status of the members of the population, the policies imposed by governments (social distancing, travel restrictions, etc.), and the status of the infrastructure (workplaces, travel, etc.) They will use these parameters to create probabilistic mechanisms to determine how COVID-19 is transmitted within populations, using online machine learning techniques. 

Rapid coronavirus detection

Holger Schmidt, professor of electrical and computer engineering, has developed novel optical sensing technology for biomedical diagnostics and is now adapting his optofluidic chip technology for rapid detection of SARS-CoV-2. Schmidt's optofluid chips can detect single molecules, including biomolecules such as DNA, RNA, proteins, whole viruses, and ribosomes. His team demonstrated the technology's capabilities by detecting Ebola RNAs.

Counting SARS-CoV-2

Assessing the distribution and quantity of viral pathogens in a community has become essential in providing a view of viral prevalence in a community. This data provides the base to understand how far a disease has spread and to assign rates to active disease. Today, that data comes from testing of individual disease sufferers. Asymptomatic carriers can easily remain uncounted. We need a way to gain a more complete understanding of viral spread across an entire community and to do so in a way that is both non-invasive and fully anonymous.

Community wastewater (sewage) provides a near ideal source for gaining a community-wide view of viral prevalence. David Bernick and team are aiming to sample waste streams from our local community to count virus. This viral signature not only counts viral excretions from individuals who are suffering, it also provides viral counts of those who are symptom-free and actively shedding virus.

The team is currently developing protocols to do this work safely and cost-effectively. Someday, these sewage counters may provide an early warning to communities around the world. This data could guide the reopening of communities, monitor hospitals, inform universities, and bring understanding to a world in chaos.

A generous donor in our community provided seed funding for this project. 

Determining the credibility of claims about coronavirus

Yang Liu, assistant professor in computer science and engineering, is working with the Defense Advanced Research Projects Agency (DARPA) to train an algorithm to index whether or not the results of a scientific paper on the coronavirus are likely to be replicable. This will help increase confidence in the research that is coming out on the virus.

Quantifying the coronavirus in solution

Detection and quantitation of a virus can be accomplished by detecting the proteins that make up its outer shell or by detecting the nucleic acid sequence that is encased in that outer shell. Biomolecular engineering professor David Bernick is proposing an apparatus that can detect RNA and partially sequence it using a single-molecule detector. This approach avoids use of fluorescent tags and engineered probe molecules, and under certain conditions can establish the quantity of a viral sequence that is present. The device itself already exists and is in production, and the analytical protocol and software could create a diagnostic platform completely enabled by internet-deployable software.

Evaluating mobile apps for virtual psychiatric services

The COVID-19 pandemic has led to the virtualization of psychiatric services such as diagnosis and therapy that were previously conducted in person. There are many apps that offer virtual therapy experiences, and computational media professor Steve Whittaker is evaluating how these apps are being modified to respond to the crisis, as well as how organizations are moving therapy online.