Modeling the Spread of Disease, Science in New Mexico
Chapters on Sickness
Memory in Athens
A History of Epidemics
Colonization
Scientific Modeling
Dissapative Structure: A dissipative structure is an organized structure in open systems which are operating far-from-equilibrium exchanging energy and matter with outside environment. A dissipative system is characterized by the spontaneous appearance of symmetry breaking and the formation of complex, sometimes chaotic, structures. A whirlpool is a dissipative structure requiring a continuous flow of matter and energy to maintain the form. Photo: Complexity Explorer, Santa Fe Institute, glossary:
https://www.complexityexplorer.org/explore/glossary/410-dissipative-structure
New Mexico has a long tradition of self-reliance, problem-solving, and creativity. We are at our best when we take care of each other. As we confront the COVID-19 pandemic, important research is being done right here in our state on the science behind hygiene, social distancing, school closures, restricting travel, and the other changes we are being asked to make in our lives and our behaviors to slow down and end the spread of the COVID-19 virus.
Scientists at the Santa Fe Institute and Los Alamos National Laboratory are bringing together perspectives from biology, physics, and mathematics. They are at the cutting edge of advancing our understanding of how the human immune system works and the complex mechanisms and interactions that allow viruses to emerge and spread. This theoretical research and new knowledge are giving us exciting new tools in preventing and fighting epidemics and pandemics.
Are viruses even alive? It’s complicated. For most of us, viruses are the stuff of nightmares — mysterious micro-agents spreading diseases like Ebola, polio, HIV, and now, COVID-19. Most are so incredibly small that scientists questioned their status as living creatures. Yet in 1992, a group of scientists discovered the Mimivirus, a giant virus whose genome was so large and elaborate that there is no longer any question—they are alive.
A: AFM image of several surface fibers attached to a common central feature. B: AFM image of two detached surface fibers of Mimivirs. C: CryoEm image of a Mimivirus after partial digestion of fibrils with bromelain. D: AFM image of internal fibers of Mimivirus. Photo: cc By 2.5. Structural Studies of the Giant Mimivirus PLos Biol 7(4): e1000092. Doi:10.1371/journal.pbio.100092.
Computer viruses, which most of us would agree are not living, provide a neat analogy for biological viruses. There are remarkable parallels between biological viruses and computer viruses. Although man-made, computer viruses too operate through infection—in this case, of computer memory, not of cellular hosts—and evolve to combat antiviral software. As scientists continue to learn about viruses, they are looking for a mathematical model that will allow us to understand the spread of infections across both living and nonliving systems.
Author: Mimi Roberts
From the research page of the Santa Fe institute: https://www.santafe.edu/research/themes
To learn about some of the important research happening in New Mexico regarding modeling and studying the spread of disease, follow these Santa Fe Institute links:
Lauren Ancel Meyers on epidemiological modeling, “Preventing the Next Pandemic”:
Part 1 | Part 2
Papers by a team of SFI-affiliated researchers, Sam Scarpino & Laurent Hébert-Dufresnes, et al.:
They interact but we model them often in a vacuum:
Complex dynamics of synergistic coinfections
Macroscopic patterns of interacting contagions
Human behavior can have unexpected consequences:
The effect of a prudent adaptive behaviour on disease transmission
Regarding covid, heterogeneity of infections and social structure:
School closures, event cancellations
Beyond the basic reproductive number
Complexity Explorer, SFI’s online education platform, offers some great relevant learning resources. Here are links to three free courses that help people learn to model complex systems such as disease:
Intro to Complexity
Fundamentals of NetLogo
Agent-Based Modeling
SFI’s friend, professor Dirk Brockmann has made these two interactive “explorables” to understand disease transmission and herd immunity:
Transmission
Herd immunity
SFI External Professor Scott E. Page has launched a free online prediction market for various second-order effects of COVID-19 that he is using as a teaching tool to help people learn about complex systems:
Pandemic Impacts
Friends of SFI worth following on Twitter as premiere reliable resources for real-time information:
Marc Lipsitch
Carl T. Bergstrom
Samuel V. Scarpino
Laurent Hébert-Dufresne
