Tyrone Burke, July 8, 2020
Carleton University Rapid Response Grants: Epidemiology, Testing, Tracing and Security
The COVID-19 pandemic has created new challenges and emphasized the urgency of grappling with social issues like inequality. The complexity of this crisis demands the mobilization of experts in many disciplines, and the academic community has answered the call. In April 2020, Carleton launched the Rapid Response Research Grants program to help build our understanding of COVID-19 and the ways in which the pandemic is impacting our lives. This funding initiative is providing $250,000 to 59 research projects being undertaken by researchers from all five of Carleton’s line faculties: Arts and Social Sciences, Engineering and Design, Public Affairs, Science, and the Sprott School of Business. This is the second of five stories covering these projects.
COVID-19 Research: Epidemiology, Testing, Tracing and Security
Dry cough. Persistent fever. A loss of taste and smell. Skin lesions. Heart palpitations.
COVID-19 is caused by a respiratory virus, but it has proven to be a medical chameleon that impacts much more than our lungs. Ever since the disease was first identified in late 2019, the list of the symptoms associated with it has continued to grow. When COVID-19 arrived in Canada, we knew little about the disease, but researchers are learning more every day. They are developing ways that COVID-19 can be detected, treated, and prevented.
There has been plenty of buzz about a possible vaccine for COVID-19, but it is entirely possible that researchers will develop effective treatments before a vaccine is ready. Dr. Ashkan Golshani of the Department of Biology is developing peptides — chains of amino acids — intended to interfere with the reproduction of SARS-CoV-2, the virus that causes COVID-19. Golshani is working with researchers at the Ottawa Hospital Research Institute and University of California San Francisco to design peptides that bind to a protein tied to the reproduction of the virus. This would prevent the virus from replicating and causing the heavy viral loads that are often present in most severe forms of COVID-19.
Dr. Kyle Biggar of the Department of Biology and Dr. James Green of the Department of Systems and Computer Engineering are also working on peptide treatment. They’re seeking to prevent the virus from interacting with humans. Green’s lab is using algorithms to model how the virus interacts with its host, while Biggar’s lab will be testing potential treatments identified by the algorithms — with the aim of developing peptides that prevent these interactions from occurring at all.
Even if potential treatments are identified, they won’t be available until they’ve been tested and safety is assured. In the meantime, we’ll need to build our understanding of COVID-19. The sudden deterioration experienced by some patients is a hallmark of the disease. Sometimes, patients who experience this show few outward signs of their rapidly deteriorating health. Dr. Sreeraman Rajan and Dr. Yuu Ono of the Department of Systems and Computer Engineering are developing a non-invasive ultrasound sensing technology that monitors vital signs. They’re seeking to provide a low-cost tool that uses a machine-learning algorithm to automatically monitor blood pressure, and help doctors make decisions about patient care.
As many as half of patients who develop COVID-19 pneumonia also develop secondary infections, which might increase the disease’s severity and mortality rate. Dr. Edana Cassol and Dr. Joerg Overhage of the Department of Health Sciences are studying how SARS-CoV-2 impacts a patient’s immune response to bacteria, and whether these responses contribute to tissue inflammation and lung damage. They are seeking to identify whether the virus affects a patient’s immune responses to co-infections, which might afford opportunities to prevent secondary pneumonia from occurring.
Exactly how lung damage progresses in patients with severe COVID-19 symptoms remains one of the disease’s unknowns. Dr. Jeff Dawson of the Department of Biology and Dr. Andy Adler of the Department of Systems and Computer Engineering are using a novel, non-invasive medical imaging technology to observe the progression of acute respiratory distress syndrome (ARDS) — a type of acute respiratory failure associated with inflammation and fluid in the lungs. Patients with this condition often deteriorate quickly, and they hope to develop tools to understand how lung function the function of the lung is impacted as the disease progresses.
The SARS-CoV-2 virus has been shown to linger on some surfaces for days, contributing to a fear of contagion that has made many of us reluctant to touch surfaces outside our homes. In higher risk areas such as hospitals, those concerns are amplified. Dr. Alex Wong of the Department of Biology is seeking to develop and validate protocols for detecting the virus in health care settings. Dr. Maria DeRosa of the Department of Chemistry is developing testing methods that could help identify the presence of the virus on a wide variety of surfaces, without consuming valuable resources that are necessary for diagnosis of COVID-19. DNA aptamers are molecules engineered to bind to other molecules, and DeRosa is seeking to identify aptamers that bond to SARS-CoV-2. These could obtain results quickly, and be used to create a test strip that would change colour to indicate the presence of the virus.
But while many are concerned about contaminated surfaces, it is liquid droplets and aerosols that are the most likely source of infection. These are mainly transmitted through coughs, sneezes, and conversations in close proximity. Dr. Edgar Matida of the Department of Mechanical and Aerospace Engineering is studying the effectiveness of homemade masks in blocking droplets and aerosols. He’s using an aerosol generator to test popular mask designs at different distances and velocities, with the aim of identifying which designs are best, so the public can make informed decisions about safety.
During the pandemic, long-term care homes have proven to be especially vulnerable to contagion. Most COVID-19 deaths in Canada have occurred in long-term care homes, with 82.5% occurring in for-profit facilities and 17.5% in non-profit homes. These homes house seniors and persons with disabilities, and require ongoing care. Yet current infection prevention and control protocols in long-term care homes have not been developed to the same extent as in acute care hospitals. The protocols that are in place do not reflect the unique psychosocial and physical needs of residents, their families and healthcare providers. Prof. Chantal Trudel is researching how the design of homes and associated protocols can be improved, so that similar issues can be avoided as new facilities are built, and existing ones redeveloped.
For seniors living at home, COVID-19 presented a different challenge. Some services they rely on were not deemed essential, and delivery was restricted by the lockdown. Home care, day programs, and meal programs can all be necessary for seniors living at home, and Dr. Susan Braedley of the School of Social Work and Dr. Renate Ysseldyk of the Department of Health Sciences are exploring how Ottawa seniors have been impacted by restrictions on these programs during the crisis. Their research builds on their 2019 study, which explored these services before the pandemic.
As it became clear that COVID-19 would become a global pandemic, it brought the capacity of our hospitals and intensive care units into sharp focus. Italy’s hospitals had been overwhelmed. China had mobilized massive resources to build a 1,000-bed emergency hospital in Wuhan, and the United States sent Navy hospital ships to New York and Los Angeles. There could be a way to approach problems like this one that is systematic and more effective. When crisis strikes, prefabricated, modular hospitals could enable the rapid construction of temporary, purpose-built facilities. Dr. Vahid Sadeghian and Dr. Jeffrey Erochko of the Department of Civil and Environmental Engineering are developing and evaluating designs for modular hospitals that are applicable to Canada, suitable for a pandemic response, and could be deployed where they are needed most, including to remote rural and northern communities with limited access to medical resources.
Early projections suggested that to treat COVID-19 patients, we would need thousands more ventilators than we had. In Milan, then being hit hard by the virus, physicians were forced to make difficult choices about who would have access to these machines. Governments scrambled to obtain them, and even entered into bidding wars. This accentuated the need for a low-cost ventilator that can be produced at scale. The Mechanical Ventilator Milano project has sought to provide exactly that. An international team of physicists and engineers with experience in gas systems for astroparticle physics experiments worked in close collaboration with medical doctors on the COVID-19 front line to develop a ventilator that is simple to build and easy to use. It needs only medical oxygen and electricity to operate. Dr. Simon Viel of Carleton’s Department of Physics is leading the project’s data analysis in Canada, with the eventual aim of certification by Health Canada.
During the pandemic, change has been the only constant. Because COVID-19 was entirely unknown, our knowledge of it has evolved quickly. That uncertainty has made it more difficult to make health care recommendations. Test kit availability has impacted testing recommendations. Asymptomatic carriers and a long incubation period have made it difficult to know how widely SARS-CoV-2 has spread, and to make the right physical distancing recommendations at the right moment. Dr. Tom Sherratt of the Department of Biology is working to apply sequential signal detection theory (SDT) to the problem. In clinical settings, doctors need to make multiple decisions quickly, and choices about testing and quarantine can have impacts that ripple far beyond the patient in front of them. Sherratt is seeking to combine sequential SDT with existing epidemiological tools like the symptomatic-exposed-infected-recovered (SEIR) model to give physicians a mathematical toolkit to assess the risks and rewards associated with their decisions.
A population’s age and general health have proven significant in its ability to weather an outbreak. But there are other factors too. Physical distancing, quarantine practices, testing, and contact tracing can all limit the extent of an outbreak, while high population density can accelerate it. The factors that shape COVID-19 outbreaks are numerous and dynamic, and the apparent irregularity of data can make it difficult to draw clear conclusions about what is happening — at least for the human brain. Dr. Emmanuel Lorin of the School of Mathematics and Statistics is using machine learning to develop a hierarchy of mathematical models. The work will use the results of various scenarios and practices to simulate the outcomes of future public health decisions, so that officials can have a more precise understanding of the implications of their recommendations that they are making.
Share: Twitter, Facebook