>
> 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: pfh at synapse9.com
> explorations: www.synapse9.com
>
> -----Original Message-----
> *From:* friam-bounces at redfish.com [mailto:friam-bounces at redfish.com] *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
> droberts at rti.org
> doug at parrot-farm.net
> 505-455-7333 - Office
> 505-670-8195 - Cell
>
>
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