By Jacob G Scott
COVID-19 has affected us all in myriad ways, from our work and travel patterns, down to our daily routines and interactions with friends and family. One small silver lining is that our field has come front and center to many who never knew of its existence. I have even seen some ODEs on the television news! Another side-effect is that many in our field are now involved in COVID-related research when that was not previously a focus. Here we highlight two of our members, Dr Joseph H Tien, Associate Professor of Mathematics at The Ohio State University, and Dr. Philip Gerlee, Associate Professor of Mathematics at Chalmers University, and the recent projects they have been asked to lead for their local governments.
twitter: @pgerlee
web: bit.ly/2XTvNYM
During late February many Swedes returning from skiing holidays in northern Italy were unaware that they were bringing home the novel corona virus. The first confirmed case in Gothenburg was reported on the 26th February at which point the disease was already circulating in the community. In mid-March me and Torbjörn Lundh were contacted by the logistics group at Sahlgrenska University Hospital who were in desperate need for predictions of hospital resource utilization. Both with respect to what the peak demand would be, but also when normal hospital care would be able to resume. Since the focus was on resource utilisation and not the dynamics of the disease we opted for a statistical model that predicted the expected number of new COVID admission per day. An unusual challenge for me as an academic was that this model had to connect directly existing modelling tools the logistic group used. We built a preliminary model within a week or two, and since then the model has been used by the hospital (alongside nationwide models) to plan the future ICU-capacity. But as the pandemic progressed it became clear that one model will not be sufficient, and we have therefore, in dialogue with the logistics group, tested a range of different modelling approaches. I entered into this project with a mindset of providing my services to those in need of them. This has meant putting some of my regular research projects on hold, but me and Torbjörn were lucky to get internal funding from our university to dedicate more time on this project. So far this has been an exciting and informative experience, and putting my knowledge of modelling at the service of the community has felt both humbling and rewarding.
I’ve been working with an interdisciplinary team at the Infectious Diseases Institute at Ohio State U. to model COVID-19, in collaboration with the Ohio Department of Health (ODH) and the Ohio Hospital Association (OHA). This began in early March, when we were tasked with estimating hospital burden in the coming weeks and months. Our approach has relied upon knowledge developed by amazing postdocs past and present at the Mathematical Biosciences Institute — we use a law of large numbers proved by former MBI postdoc Karly Jacobsen (with G. Rempala, M. Burch and I) for a stochastic disease process on a dynamic network to get a differential equation that provides the base of our model, and then use an estimation technique combining dynamical systems and survival analysis developed by current MBI postdoc Wasiur KhudaBukhsh (with G. Rempala, E. Kenah, and B. Choi) to estimate parameters and quantify uncertainty. It’s been an intense, rewarding experience, and I’ve been humbled to be part of this dedicated team. (I also have a lot more gray hair because of it!)
Interview with Dr. Reginald L. McGee II, Assistant Professor at College of the Holy Cross in the Department of Mathematics and Computer Science, and new member of SMB newsletter editorial board, about his research as a mathematical biologist.
Jacob talks to Reginald about his research in the field of mathematical biology. Read the interview here.