By Hans Kaper
During the fourth week of the summer school on “Dynamics and Data in the COVID-19 Pandemic,” organized by the American Institute of Mathematics (AIM) and the Mathematics and Climate Research Network (MCRN), the rubber met the road, so to speak. Having established five “umbrella groups” (each of which focused on a particular theme) and categorized 15 projects under the various umbrellas, it was time for participants to apply mathematics, simulations, and data assimilation to better understand COVID-19.
The daily schedule had a few fixed points: “all-hands” meetings at 11 a.m. and 5 p.m., optional tai-chi sessions at 3 p.m., and tutorials during the lunch breaks. Students spent most of their time engaging in individual and group discussions, reading, developing mathematical models, programming these models in MATLAB or Python, and narrowing the scope of the projects.
Five Umbrella Groups and their Subgroups
Diseases and the Environment
- Climate
- Air Quality
- Zoonotics
Impacts of Human Behavior
- Modeling human behavior using game theory
- Adaptive network structures for social interactions
Incorporation of Data
- Multi-scale domain adaptation
- Blood types and COVID-19
- Topological epidemiology
Resource Allocation
- Optimal control and testing
- Network topologies for testing strategies
- Optimization of pop-up testing sites
Social Justice
- Uninsured/insured populations
- Economics and disease interactions
- Multi-population models
- Age-structured multi-population models
Special Lectures
The learning process, which occupied most of the school’s first three weeks, continued on a smaller scale with two special lectures. On Wednesday, Steffen Eikenberry (Arizona State University) gave a talk entitled “To Mask or Not to Mask,” and Linda Allen (Texas Tech University) returned on Thursday with a tutorial talk about “Branching Processes.”
Eikenberry addressed the effectiveness of facemasks to curtail a pandemic’s spread. He based his presentation on a recent paper published online in Infectious Disease Modeling. An early paper by A.J. Jessup, which published in Scientific American Supplement in 1878, previously addressed this topic but remains controversial. Eikenberry’s talk included details about the Manchurian pneumonic plague (1910-1911), the Spanish influenza pandemic (1918-1919), the severe acute respiratory syndrome (SARS) epidemic (2002-2004), and the current COVID-19 pandemic. He emphasized that one can efficiently study the effectiveness of mask-wearing with an extended version of the susceptible-exposed-infected-recovered (SEIR) model. The bottom line was clear: universal mask use is critical to curtail a pandemic’s spread.
Allen’s talk served as a follow-up to her presentation during the school’s second week. This time, she focused on estimating the probability of an epidemic’s outbreak using branching processes, a new topic for most students.
Tutorials
This week’s program featured three tutorials, which mentors presented during lunch breaks. Topics included GitHub (for code sharing), Zotero (for reference material), and fundamentals of data assimilation.
Hans Kaper, founding chair of the SIAM Activity Group on Mathematics of Planet Earth and editor-in-chief of SIAM News, is affiliate faculty in the Department of Mathematics and Statistics at Georgetown University.