Session P01: Physicists Responding to COVID-19 and Beyond: Science and Trajectories

Live

Science Responds was established early during the COVID-19 pandemic as a collaborative hub for computational scientists to contribute their skills and experience managing large distributed datasets and research teams to projects focused on combatting the pandemic. Through this effort we organized a series of seminars from different researchers spanning the fields of public health, biomedical, drug discovery, and more and provided a central resource for interested researchers to connect with projects, resources, and information around best practices. This talk will describe the development and activities of Science Responds and in the final portion will provide a deep dive into the COVID Community Vulnerability Index project that was started within Science Responds and has since grown to an international quantitative research project.   

Live

Early during the current coronavirus disease 19(COVID-19) pandemic, hydroxychloroquine (HCQ) received a significant amount of attention as a potential antiviral treatment, and became one of the most commonly prescribed medications for COVID-19 patients. However, not only its effectiveness was questionable, but there were serious potential arrhythmogenic effects, especially as the concentrations used were higher than when commonly prescribed for malaria or and autoimmune conditions.
We show how we can use optical mapping and methods from nonlinear dynamics to quantify the arrhythmic effects of drugs in the heart with a combined approach of theory, experiments and computer simulations. We will identify a period doubling bifurcation that develops on the cell voltage (action potential) due to HCQ blocking certain potassium ion channels. We describe numerically and then experimentally the complex, disorganized patterns of electrical activation that develop due to this bifurcation in space. We demonstrate the arrhythmic substrate that develops due to HCQ and its combination with AZM and identify the physical mechanism.   

Live

The COVID-19 pandemic has make clear the need of more fast and reliable methods for testing .The golden standard on testing is the rT-PCR method which uses expensive chemicals .Even though in the last year the speed in which test results are produced do not allow instant tracing of infected people .We have propose the use of Raman Spectroscopy to detect the virus .However the Raman signal is very weak and we need to use Surface enhanced Raman Spectroscopy .This implies the use of plasmonic nanoparticles which are tuned to the main absorption wavelengths of the virus .Raman is based on Physics and Materials Science methods and produces instant results .
In this work we will report the advances in our lab on developing SARS-CoVi-2 testing and will show that can become the golden standard for testing.   

Live

COVID-19 spread across the world with a speed and intensity that laid bare the limits in our understanding of the transmission pathways of such respiratory diseases. There is, however, an emerging consensus that airborne transmission constitutes an important mode for the spread of COVID-19. Each stage in this transmission pathway is mediated by complex flow phenomena, ranging from air-mucous interaction inside the respiratory tract, turbulence in the exhaled jet/ambient flow, to inhalation and deposition of these aerosols in the lungs. Inspired by the Drake Equation that provides a framework to estimate the seemingly inestimable probability of advanced extraterrestrial life, I propose a phenomenological model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19. The model incorporates simple ideas from fluid dynamics with the factors implicated in airborne transmission and is designed to serve not only as a common basis for scientific inquiry across disciplinary boundaries, but to also be understandable by a broad audience outside science and academia. Given the continuously evolving nature of the pandemic and the resurgence of infections in many communities, the importance of communicating infection risk across scientific disciplines, as well as to policy/decision makers, is more important than ever.   

Live

Epidemiological modeling of infectious disease transmission informs public health decision-making by providing a way to synthesize data from multiple data sources, adjust for potential biases, forecast the trajectory, evaluate the impact of interventions, and conduct sensitivity analyses. We often adapt methods from the physical sciences, with compartmental models comprised of ordinary differential equations serving a central role in modeling of emerging infectious diseases. Network models also provide important insights about optimizing public health prevention strategies (e.g., including evaluation of targeted prevention strategies focused on influential nodes) for infectious diseases, including Coronavirus Disease 2019 (COVID-19). Using a variety of analytic approaches, we have modeled transmissions among individuals within healthcare facilities, (e.g., nursing homes) to assess the relative value of different testing and mitigation strategies, including comparing the impact of testing strategies focused on either nursing home residents or healthcare providers. Careers in public health can allow physical scientists to apply their strong analytic skillsets distilling the essence of a complex system into a model that informs translation of data into action.   

Panel Discussion: Career trajectories and perspectives

This final hour of the session will begin with each panelist briefly summarizing their career path and highlighting how it facilitated their ability to contribute to the science around COVID-19. Then the remaining time (roughy 40 minutes) will be devoted to the panel discussing questions of how to respond to important and timely social needs as a professional physicist. Live audience members will be encouraged to submit questions to the panel.

Panel Speakers: Flavio Fenton, Miguel Jose Yacaman, Savannah Thais, Rajat Mittal, Rachel Slayton