Phil, I did read your question, repeated below:
Cool, do you include any comparative natural system component? Perhaps working with better ways to identify system structures in natural systems and early signs of when they are inventing new ones would be helpful in developing tests for models that approximate the complexity of nature. However, I found it to be sufficiently ambiguous that I had absolutely no idea what was being asked, and thus found myself at a complete loss for a response. -- Doug Roberts, RTI International [EMAIL PROTECTED] [EMAIL PROTECTED] 505-455-7333 - Office 505-670-8195 - Cell On 3/31/07, Phil Henshaw <[EMAIL PROTECTED]> wrote:
Doug, Did you not answer my question just because it seemed obvious or something? The other questions and your other answers all seemed very thoughtful, but didn't address mine. I'm thinking the use of the tool would include helping people in the learning process of finding what is actually working during the experience of an epidemic. Every pathogen and every public health initiative will have different growth dynamic characteristics, and sometimes very small differences will have large effects, especially because of relative lag times of divergence and response. I was commenting, I guess, on the difference between a universal general model of epidemic spread and response and the particular event process of an individual epidemic and the creative adaptation an effective response requires. Phil Henshaw ¸¸¸¸.·´ ¯ `·.¸¸¸¸ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 680 Ft. Washington Ave NY NY 10040 tel: 212-795-4844 e-mail: [EMAIL PROTECTED] explorations: www.synapse9.com -----Original Message----- *From:* [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] *On Behalf Of *Douglas Roberts *Sent:* Friday, March 30, 2007 5:45 PM *To:* The Friday Morning Applied Complexity Coffee Group *Subject:* Re: [FRIAM] One of my projects A few of you have asked questions about the the EpiSims-Grid project, so I'll try to answer them here, in roughly inverse order that they were received: From: Paul Paryski: For someone like me who rarely works with such complex models this is a > very interesting discussion. Out of my ignorance a couple of questions have > popped into my aging synapses: > -does the model include mutation and other adaptations by diseases? > No, we have only simulated one pathogen at a time, to date, and it does not mutate. -are you going to study past massive epidemics to see what patterns are > applicable (bio mimicry and incidence of natural immunity, cultural > practices) > Yes, we have done this fairly extensively. Lots of data exists from the 1918 pandemic flu outbreak, for example. -who will make the political choice to use the info/models when the time > comes? > Good question. See my response to Laura Mac's questions bleow. From Laura MacNamara: Being someone who studies people who use models, I'm curious about how you guys are relating to your user community. Who are the intended analysts (the ones that you hope know what you're doing)? At what point do you guys start engaging them? Do they treat your simulation as black box? Our last study was commissioned by a high-level consortium of Department-level representatives -- Dept. of State, Dept. of Treasury, Dept. of Homeland Security, Dept. of HHS, and the office of the White House. The purpose of the study was to help them identify relative measures of effectiveness regarding what intervention strategies would provide the most benefit in the event of a pandemic flu outbreak. Examples of intervention strategies that were modeled included 1. Self-isolation (staying home when symptomatic) 2. Social distancing (telecommuting, scheduled trips to the store with minimal contact to other shoppers, in general minimizing physical proximity to other people) during an outbreak 3. Closing down schools and non-critical workplaces 4. Treating critical infrastructure workers with anti-viral treatments (remember -- it was a pandemic being simulated, there were no vaccines) 5. etc. The intent was to help government officials develop a response plan in the event of an outbreak. I was quite impressed with the expertise with which the leader of the study, the White House representative, directed the study. He was one of the most knowledgeable and intelligent of any of the customers that I have aver worked with. The simulations used in the study were most definitely not treated as black boxes. Rather, the strengths and weaknesses of each of the three models were thoroughly explored. The consortium of users approached the leader of the MIDAS project and requested our participation on the project last summer, at which point we immediately engaged with them to develop an experimental design. From Robert Holmes: Fair enough: big simulation answers some questions, small simulation answers others. So what are the specific questions that a big epidemiological simulation can answer? It can't be anything too predictive ("ohmigod, New York has just fallen to small pox. Which city is next?") because that depends (I'd guess) on something that is unsimulatable ("errr.... dunno. Kinda depends which flight the guy with small pox got onto"). What are the questions that can only be answered with a big model? EpiSims was by far the most detailed of the three models used. It is an individual-based ABM in which the second-to-second movements of every individual in the 8.6-million population city were modeled for 60 consecutive 24-hour days. Further, each individual was fairly completely characterized demographically -- race, inccome, marital status, number of children, etc. Also, family household structures are created by EpiSims, in which the same adults and children come back to the same household every day. This level of detail allowed us to run experiments on specific demographic subsets of the population that were not possible with the other models. For example, we ran a series of experiments for which social distancing was less effective among lower income people, because they could not afford to stay home -- they had to work. These runs were compared to runs where all working members of the population had the same compliance when social distancing measures were imposed. Another example of experiments that were conducted with EpiSims that could not be achieved with the other models: we ran several experiments in which the imuno-response of lower economic segments of the population was less effective in resisting the pandemic virus then for those more affluent members of the population. The reasoning being that poorer people have less access to health care. Remember, the intent of these studies was to establish a relative effectiveness ranking determination of various intervention strategies for future use establishing a response strategy in the event of a pandemic outbreak. The intent was *not* to model "ohmigod, New York has just fallen to small pox. Which city is next?" types of human behavior in response to an outbreak. I hope this addresses some of your questions. Thanks for your interest! --Doug -- Doug Roberts, RTI International [EMAIL PROTECTED] [EMAIL PROTECTED] 505-455-7333 - Office 505-670-8195 - Cell ============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
============================================================ FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
