Santa Fe Institute Collaboration Platform

COMPLEX TIME: Adaptation, Aging, & Arrow of Time

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Contact: Caitlin Lorraine McShea, Program Manager, cmcshea@santafe.edu

Difference between revisions of "Aging and Adaptation in Infectious Diseases"

From Complex Time
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|End date/time=July 28, 2018
 
|End date/time=July 28, 2018
 
|Organizers=Mercedes Pascual;Jean Carlson
 
|Organizers=Mercedes Pascual;Jean Carlson
|Summary=This working group explores the role of aging and adaptation in infectious diseases operating over multiple organizational and temporal scales. General areas include immune system dynamics and age, host-pathogen co-adaptation in chronic vs. acute infections, pathogen antigenic diversity and endemism, effects of age on infectious diseases in human and nonhuman hosts. Overarching themes include memory, (co)adaptation, diversity, feedback, robustness and fragility. We are interested in aging and biological time as reflecting a loss of robustness in the face of infection at the level of individuals but also populations. We are also interested in aging of the pathogen in relation to its ability to persist and withstand intervention efforts. This meeting brings together a select group of scientists from a range of backgrounds to define novel questions, facilitate potential collaborations, and catalyze new and transformative research in this area. Development of methods that combine big data, experiments, theory, and computation with predictive and therapeutic applications across disciplines is of particular interest.
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|Meeting summary=This working group explores the role of aging and adaptation in infectious diseases operating over multiple organizational and temporal scales. General areas include immune system dynamics and age, host-pathogen co-adaptation in chronic vs. acute infections, pathogen antigenic diversity and endemism, effects of age on infectious diseases in human and nonhuman hosts. Overarching themes include memory, (co)adaptation, diversity, feedback, robustness and fragility. We are interested in aging and biological time as reflecting a loss of robustness in the face of infection at the level of individuals but also populations. We are also interested in aging of the pathogen in relation to its ability to persist and withstand intervention efforts. This meeting brings together a select group of scientists from a range of backgrounds to define novel questions, facilitate potential collaborations, and catalyze new and transformative research in this area. Development of methods that combine big data, experiments, theory, and computation with predictive and therapeutic applications across disciplines is of particular interest.
 
|Additional info=== Overview and rationale ==
 
|Additional info=== Overview and rationale ==
 
Time and age in standard dynamical systems for infectious diseases are treated as simple clocks that run at a constant rate. Thus, standard epidemiological models that incorporate host age consider structured populations and rely on partial differential equations in which the derivative of age relative to time is simply a constant. By contrast, ‘complex’ time in infectious disease dynamics is intimately related to the different trajectories that either individuals or populations can follow and which ultimately determine the outcome of infection, its susceptibility to intervention, and the likelihood of critical failure. Pieces of what determines these trajectories have been investigated, in relation to the immune system, pathogens’ evolution and their escape from the host’s acquired memory, as well as the coadaptation of both. A synthesis of these efforts and a general theory that places aging at its center is still missing.
 
Time and age in standard dynamical systems for infectious diseases are treated as simple clocks that run at a constant rate. Thus, standard epidemiological models that incorporate host age consider structured populations and rely on partial differential equations in which the derivative of age relative to time is simply a constant. By contrast, ‘complex’ time in infectious disease dynamics is intimately related to the different trajectories that either individuals or populations can follow and which ultimately determine the outcome of infection, its susceptibility to intervention, and the likelihood of critical failure. Pieces of what determines these trajectories have been investigated, in relation to the immune system, pathogens’ evolution and their escape from the host’s acquired memory, as well as the coadaptation of both. A synthesis of these efforts and a general theory that places aging at its center is still missing.

Revision as of 15:52, July 17, 2018