https://centre.santafe.edu/complextime/w/index.php?title=Hallmarks_of_Biological_Failure/Measuring_the_resilience_of_hosts_to_infections_by_mapping_disease_space&feed=atom&action=historyHallmarks of Biological Failure/Measuring the resilience of hosts to infections by mapping disease space - Revision history2024-03-29T14:02:11ZRevision history for this page on the wikiMediaWiki 1.35.6https://centre.santafe.edu/complextime/w/index.php?title=Hallmarks_of_Biological_Failure/Measuring_the_resilience_of_hosts_to_infections_by_mapping_disease_space&diff=4141&oldid=prevAmyPChen: Created page with "{{Agenda item |Start time=April 9, 2019 09:45:00 AM |End time=April 9, 2019 10:15:00 AM |Is presentation=No |Presenter=DavidSchneider |Pre-meeting notes=My group has been tryi..."2019-04-05T16:23:03Z<p>Created page with "{{Agenda item |Start time=April 9, 2019 09:45:00 AM |End time=April 9, 2019 10:15:00 AM |Is presentation=No |Presenter=DavidSchneider |Pre-meeting notes=My group has been tryi..."</p>
<p><b>New page</b></p><div>{{Agenda item<br />
|Start time=April 9, 2019 09:45:00 AM<br />
|End time=April 9, 2019 10:15:00 AM<br />
|Is presentation=No<br />
|Presenter=DavidSchneider<br />
|Pre-meeting notes=My group has been trying to find relatively simple multidimensional ways of measuring the response to infections. Our idea is to measure how far a host will be pushed from its normal physiology when it sickens and what route it will take coming back from sickness. We do this by drawing the trajectory infected individuals take through phase space and try to produce maps that improve our understanding of the process. We want to understand how far the system can be pushed before it breaks, which is one sort of system failure. We then want to understand how this varies. For example, do hosts die because their physiology becomes more elastic? In this case they would be more likely to enter physiological states that are not survivable. Alternatively, physiological states that would be survivable when to one host might not be survivable to another. Our first project is to understand what variation looks like when we examine infections this way. As we proceed we would like to model this system more carefully.<br />
}}</div>AmyPChen