The Mathematical Sciences' Role in Homeland Security Proceedings of a Workshop (2004) / Chapter Skim
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Detection and Epidemiology of Bioterrorist Attacks
Detection and Epidemiology of Bioterrorist Attacks
Pages 135-260
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From page 135... ...
Dr. Broome has received many professional awards, including the PHS Distinguished Service Medal, the Surgeon General's Medallion, the Infectious Disease Society of America's Squibb Award for Excellence of Achievement in Infectious Diseases, and the John Snow Award from the American Public Health Association.
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From page 136... ...
Let me just go ahead and get started with the afternoon's first session. I am Claire Broome, medical epidemiologist at the Centers for Disease Control and Prevention where I have been involved in actually getting the data that you all would like to have as part of the targets for your modeling and simulations, and I have worked closely with a lot of the folks working on bioterrorism preparedness, and I will be moderating this session and what we will do is go through the first presentations and then try to pull some of this together and have a more interactive session during the discussant time period.
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From page 137... ...
137 Introduction by Session Chair Claire Broome Dr. Broome introclucect herself as a mectica]
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From page 138... ...
138 Kenneth Kleinman "Ambulatory Anthrax Surveillance: An implemented System, with Comments on Current Outstanding Needs" Transcript of Presentation Summary of Presentation Power Point Slides Video Presentation Kenneth Kleinman is assistant professor in the Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care. He serves as the main biostatistician on three CDC-funded projects to implement surveillance of health care system utilization in the Boston area and nationally, and he works with the national BioSense project.
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From page 139... ...
After the generality of this morning's talk I feel like this subtitle here is kind of grandiose, but I am a biostatistician and I am going to actually going to show you real data and describe a system that is running now in Boston, and there are a lot of people involved with getting the system running. It is actually a collaboration between the academic department, an HMO care provider and the State Department of Public Health.
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From page 140... ...
So, there is not a whole lot known about it but it is supposed that most people have symptoms within a couple of days and then a day or two after you have those symptoms you start having really severe symptoms like severe sweating and breathing problems and eventually shock, and if you are not treated then there is death in 98 percent of cases and there is even death in some cases where there is treatment. So, what are you going to do if you have anthrax?
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From page 141... ...
So, our data, our study, as I mentioned we are trying to do this. Our position is located between a health maintenance organization and a provider group and also we have, we are in an academic department.
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From page 142... ...
So, it is relatively easy for us to take our system which is in Eastern Massachusetts and transport it to some other locale where they happen to use the same medical records system and there are a bunch of them. PARTICIPANT: Does this system store all the medical record?
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From page 143... ...
Now, I am going to start talking about the problems we encountered when trying to set up the surveillance, and the first one is that it actually uses adult standard test for anthrax, and you have to get a chest x-ray, and I don't know enough about medicine to know what about this x-ray says that there is anthrax here, but if we actually waited for chests x-rays we wouldn't do any better than hospital surveillance because the physicians don't order chest x-rays for people who come in with cold symptoms. So, we can't actually do surveillance for diagnosis of anthrax, and so what we do instead is we define symptom clusters or syndromes, and what we do is we say that anything that your doctor might say if you came in with the first phase of anthrax problems we are going to try to collect that, and we call that lower respiratory illness or I might say lower respiratory infection later 143
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From page 144... ...
It was probably the same illness, and so we throw those away, and what is left we call episodes of lower respiratory infection. PARTICIPANT: How many don't visit with the same illness?
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From page 145... ...
So, here is actual data and each dot here represents the count of visits for their respiratory infection on a given day in between January I, 1996 and December al, 1999 or January I, 2000, and I just want to point out a couple of interesting features here that will come into play later, and the first is that you can see that during the winter there are big peaks. People tend to go to their doctors for respiratory complaints more in the winter than they do in the summer presumably because they are more likely to have those symptoms and the other interesting feature is that you can see there are two trends here, and our clinics are actually open on the weekends.
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From page 146... ...
So, there are 130 visits among our 250,000 numbers for lower respiratory illness on I don't know what day this is, probably like May I, 1999.
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From page 147... ...
So, what we do to solve the problem is we actually geo code everyone, and geo coding just means that we take their address and we find out where on the map it lies, and it is actually remarkably easy to do, and accurate and cheap. We outsource it, and it costs us, I don't know 4 or 5 thousand dollars to do 250,000 addresses, and it comes back within a week.
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From page 148... ...
So, it is an arbitrary grid on space but these actually, if you were to look at this latitude and longitude point you would be able to find it in the middle of Massachusetts Bay. PARTICIPANT: Is it adjusted for population?
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From page 149... ...
So, they wouldn't be able to fit a covariate saying that this count happened during the winter; this count happened on Monday; this count happened on Christmas and be able to adjust for that, and they are, also, both designed for smaller data sets although I think that is probably not a big problem.
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From page 150... ...
150 Now, the really big problem with these things though is that they are looking for clusters now and if you recall the problem that we have we are trying to say that we know there are clusters of flu because flu is contagious and flu symptoms are what we count. So, we know there is going to be a cluster on any given day especially during winter, but we know that there is going to be a cluster and we want to know whether the cluster we are seeing is bigger than the cluster we expect as opposed to whether there is a cluster, not whether there is a bump but is the bump bigger than the bump we expect based on the clustering there has been in the past.
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From page 151... ...
We have a denominator and numerator for every census tract in our area over time, and what you do is use the generalized linear mixed model approach, logistic regression, and of course I could use a Poisson(?
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From page 152... ...
So, what we are doing makes sense and the random effect might be features of each tract. So, if there are tracts where there are more people or there is more people that are prone to sickness or fewer people who are prone to sickness we are going to find that through these random effects and when we test for variance of those random effects we find out it is not zero.
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From page 153... ...
Now, there is a problem with that. The big problem is that we have 520 census tracts in our area and the estimated P value for each one each day and that means we have IS0, 000 tests each year.
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From page 154... ...
We report the name of the town and the census tract number and I didn't mention earlier that those things are actually not determinants. Census tracts can bridge more than one town and of course multiple census tracts would be included entirely in one census tract.
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From page 155... ...
So, I am close to the end, and what I think is a really big unsolved problem for us and I have a very easy solution to it, but an event can take place over more than one census tract, and when it does our models aren't going 155
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From page 156... ...
Logistically it is hard to do that for various reasons, but I am not a cryptographer so I am sure that it is a great idea. We are using census tracts as our neighborhoods.
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From page 157... ...
157 arbitrary grid on space that wouldn't take into account anything special about the boundaries and this is something that definitely should be assessed and I think that it would be good if we could figure out how to incorporate individual level covariates because when a 20-year-old person goes to their doctor complaining of respiratory infection it means something a lot different than when an BO-year-old person does that. Finally, I want to disclaim any collusion between me and the next speaker but I think that the biggest problem is figuring out how to simulate data because there is really no way to test the model sensitivity right now and we need to be, what we really need to be able to do is simulate the background noise which is flu and see whether we can detect and kind of solve the simulated data with anthrax and see whether we can detect additional cases.
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From page 158... ...
158 (Applause.) PARTICIPANT: I just want to follow up on an earlier question about anthrax is not contagious.
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From page 159... ...
DR. BROOME: The real question is have you notified alerts to the health department and has anything been found that had any public health significance.
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From page 160... ...
DR. KLEINMAN: And that is, also, why we don't send for the false alarm model, but I understand your question, but the answer to your question is there have been several times when a relatively unusual kind of event happened and that once every 55 days may have been the most extreme that has happened since we started running this in late October.
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From page 161... ...
So, I mean we definitely want to hear about true signals, but in fact the critical need is to say does this have any potential real relevance. I mean just because you have got a whole bunch of flu patients who show up in a census tract, that happens a lot.
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From page 162... ...
We are trying to detect a non-specific febrile illness which might be misdiagnosed as flu. So, you are trying to separate out an anthrax, a febrile smallpox rash from the background noise of a normal influenza season and there is a whole lot more background noise than there is anthrax.
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From page 163... ...
163 mathematics of planning . epidemiologic simulation for response He is at Los Alamos National Laboratory.
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From page 164... ...
One improvement wouIct be to ctetermine whether results from several census tracts are really just manifestations of the same overall exposure event. Another wouIct be to finct the optimal type of basic geographical unit census block groups, for example, or even an arbitrary grid and compare it to the census-tract groupings that are currently usecl.
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From page 165... ...
165 cases of flu anct the like anct see whether the mocle! detects any simulatect anthrax data embecictect in that noise.
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From page 166... ...
His current interests include developing advanced technology for the study of large sociotechnical systems and understanding the dynamics and structure of social networks.
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From page 167... ...
I will describe the simulation that I am building. I will talk a little bit about why we use simulation in the first place and then I am going to try to give some mathematical questions that arise not just from epidemiological simulation but from any simulations of social technical systems we do, and then I would like to give an existence proof for a math program that has a very definite role in homeland defense in particular.
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From page 168... ...
168 the process of simulation because once you understand what the components are it is pretty obvious how you can use it to build an epidemiologic simulation. The reason we have gone in this direction of individual based simulation for response planning is that we have been asked to detect anomalous patterns which means looking at geographic distributions of disease by time for demographic distributions.
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From page 169... ...
Let me go ahead and explain the rest of the simulation models first. We have a very simple disease progression model, all we really need to know about the disease or what the effects on the individual who is sick are.
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From page 170... ...
170 You already have the thresholds around. It is very important for the actual dynamics of the epidemic and someone can either die or recover.
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From page 171... ...
The traditional models for epidemiology require something called a reproductive number. I will talk about this a little bit more in a minute but it is basically what happens if you introduce an infected person into a susceptible population.
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From page 172... ...
Then you compare a little bit more from these two approaches. Traditional epidemiological models, the next speaker may correct me on this but I class them all as basically coupled rate equations.
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From page 173... ...
So, in contrast to this approach what we are doing is to represent individuals each of whom carries some set of demographics which is much more finely resolved than in the other models. We are estimating contact rates between the individuals and the whole population and what may or may not be fairly important here is that these contact rates are estimated independently from the disease spreading problem.
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From page 174... ...
The next few slides are actually fairly apropos of the previous session's data mining, I think because they 174
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From page 175... ...
We take census data down to the block group level and we build a synthetic population. The property of this population that is important is that if you were to do a census on the synthetic population you would match the results of the actual census in an actual city.
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From page 176... ...
Everybody in the simulation is trying to minimize their travel time to fulfill all the constraints that their activity structure imposes on them, but they don't know what everyone else is doing except that everyone else is trying to minimize their travel time. So, we play this game on the computer and we simulate the traffic and results which updates the travel times which can update the activities and certainly update the routes that people choose.
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From page 177... ...
177 When all this settles down we have an estimate for the contact panels. So, we put all that together and take the census data activity surveys and network the infrastructure data and we produce epidemic curves.
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From page 178... ...
178 infected during a specific week after an incident occurs, and this doesn't tell you as much as you might think. It is saying that in the first week the age distribution depends directly on exactly what the release scenario was.
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From page 179... ...
People move around and the resources often move with them and moreover defensive actions can change the way people move. So, what you really need to know of social networks is where the resources and people are and the function of time, possibly in hypothetical circumstances.
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From page 180... ...
The only reason for them being the way t hey are is some, it is contingent on some completely unknown past history. As an example I use the development of the social network that I went through briefly before.
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From page 181... ...
So, in addition to that kind of philosophical question about what simulation means there are very specific problems arising in our simulations of sociotechnical systems that I would to just very briefly mention. The first is we get questions in the form of well, here is what, you guys know what the social network looks like.
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From page 182... ...
On the theoretical side if you think computer science is too much to worry about but I would like to know about results about very structured random graphs, we have a long history of theory on random graphs that have say a Poisson degree distribution where you pick links at random to turn on and off, and recently there has been a lot of work on small world methods that have power law degree distributions and these arise in places where first order clustering statistics are very important. The graphs that I am working with have a very different degree distribution, number of neighbors of each.
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From page 183... ...
I am just trying to give you the flavor of a math program that has a very direct influence on homeland security. The kinds of research that go on in this program are characterization of dynamical systems, deriving morphisms between different dynamical systems, between different objects, inductions from one to another, algorithm development, specification simulations and extensions to other things as required by the applications that we are developing.
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From page 184... ...
The mathematical underpinnings let us know when it is even reasonable to suspect that we can build a simulation to do some of the things we want to do. A lot of our sociotechnical development depends on composing different simulations like the traffic simulation with an epidemiology simulation.
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From page 185... ...
SDS papers but I would like to mention on the computer science side and the math side we have papers come back from a journal saying,"That is a wonderful paper, great results. Please remove all reference to applications." And if you want my opinion as to what mathematics can do for participating i homeland security change the culture a little bit.
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From page 186... ...
The reproductive number involves two different things person-to-person transmission characteristics of the disease and sociaI-mixing patterns and the latter can't be cteterminect in isolation. So in contrast to the traditional approach, researchers are estimating contact rates between inctivicluais and the whole population, and what may or may not be fairly important is that these contact rates are estimated inclepenclently from the ctisease-spreacting problem.
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From page 187... ...
. So if you want my opinion as to what mathematics can do for homeland security," he saint, "change the culture a little bit so that it's not bact to have applications.
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From page 188... ...
She uses these models as health policy tools: to design epidemic control strategies for a variety of infectious diseases, to understand and predict the emergence of antibiotic and antiviral drug resistance, and to develop vaccination strategies. The main focus of her research is to develop the study of infectious diseases into a predictive science.
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From page 189... ...
So, I have been told to stand rigidly behind here and not move an inch. Okay, so in overview the material I want to cover then is to say a little bit about transmission models and their uses and to spend most of the time talking about uncertainty and sensitivity analysis to explain to you what it is, what it can be used for, some examples from work that we published on HIV and then to talk about the problem with risky vaccines, again, some work that we have done on HIV identifying vaccine perversity points, and you will have to wait to find out what those are and then talk a little bit about how that is related to smallpox, as we have a somewhat similar problem as we have currently a risky vaccine to deal with smallpox, and then I will go through as far as I know the complete literature of mathematical bioterrorism which is four publications at the moment.
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From page 190... ...
Second use of them is to define perversity thresholds based upon drug resistance. When you treat individuals you get drug resistance.
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From page 191... ...
So, how we can deal with this is by using uncertainty and sensitivity analysis based upon something called Latin hypercube sampling and this allows us to predict the future with a degree of uncertainty, and I will show you some examples, but essentially all you need to know about this is the parameter -- can we go back? The parameter estimation uncertainty is being translated into prediction estimation uncertainty, okay?
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From page 192... ...
Again, this is another paper I published with Angele McLean in 1994, in Science and a paper we published in 2000 in Science, both looking at HIV and trade-offs between if risk behavior increases and you have got treatment or vaccine how you can actually end up making the epidemic worse. So, you need to have your epidemic interventions coordinated.
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From page 193... ...
You can vary everything at once and Latin hypercube sampling was first proposed by McKay, Conover and Beckman in 1979, to aid in the analysis of nuclear reactor safety. So, they were concerned with a problem of nuclear reactor meltdown, obviously a very important problem and they had very large models and the parameters were uncertain, so, a somewhat similar problem to what we are thinking about today.
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From page 194... ...
DR. CHAYES: Can we ask you why would you be using a Latin hypercube because in a Latin hypercube you don't want to have the same color occur in -DR.
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From page 195... ...
You then use Latin hypercube sampling and then calculate 1000 values for R zero and therefore you then have a measure for R zero as an uncertainty estimate.
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From page 196... ...
So, again the Y axis is R zero, the value of it and on the X axis this shows part of the sensitivity analysis. The parameter here is the change in risk behavior and you can see as that increases and decreases the value of R zero changes and that this is again uncertainty analysis.
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From page 197... ...
So, we predicted a variety of things, the number of HIV infections prevented over time, the number of new cases of drug-resistant HIV arising over time, the prevalence of drug-resistant cases over time, overall prevalence and then the number of infections prevented per drug-resistant case that arose. So, this is sort of a biological cost/benefit analysis, how many things that you have done that are good, the number of infections prevented versus sort of the number of things you have done bad which is generate drug resistance.
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From page 198... ...
The blue predicted data are after 1 year. The yellow are after 5, and the red are after 10 years, and here you can see the more you treat, if you go along the X axis, the more HIV infections you prevent, and since it is an uncertainty analysis you get again the predicted clouds of data.
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From page 199... ...
Again, the treatment rate is an uncertain parameter varying between 50 and 90 and this is what would happen if you treated an HIV epidemic after one year of combination antiretrovial therapy. The drug sensitive strains come down, the white data at the top.
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From page 200... ...
So, these are our predictions from 1996 to 2005. So, then the other part of this was to do the sensitivity analysis and this uses the results of the uncertainty analysis that we generate and then we calculate partial correlation coefficients and this basically shows that one of the key factors in increasing the amount of drug resistance was the treatment rate which is not surprising.
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From page 201... ...
They are low cost and they are simple immunization schedules. So, live attenuated vaccines are very nice and are used a lot, but let us just think about some of the 201 are can the has the to
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From page 202... ...
We looked at this in terms of HIV vaccine and this is a paper we published in PEAS last year looking at live attenuated HIV vaccines. Basically this is an ordinary differential equation model and allows us to look at the effect of a vaccine that would be very effective and protect against infection but in some people because they are vaccinated will actually cause AIDS though at a much slower rate than if they had gotten infected with the wild type.
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From page 203... ...
What we did is predict what would happen in Zimbabwe where there is a very severe HIV epidemic; 25 percent of the population are currently infected and in Thailand where very much fewer, much less severe epidemic and compare and contrast between these two countries using exactly the same hypothetical HIV vaccines to see what would happen. So, again, we used time-dependent uncertainty analysis and we specified the parameters such as efficacy, such as coverage levels by probability distribution function and then we made some predictions.
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From page 204... ...
So, it would be the same thing if you were looking at a smallpox vaccine. At the vaccine perversity point then the annual AIDS death rate with a live attenuated HIV vaccine in place is equivalent to the annual AIDS death rate without a live attenuated HIV vaccine and this shows our predicted results for what would happen if you put an HIV vaccine out in Thailand.
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From page 205... ...
If you had live attenuated vaccines that were 5 percent or less they would actually reduce the death rate and be a good idea. The same vaccines in Zimbabwe as you see there is no vaccine perversity point.
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From page 206... ...
In Thailand vaccine strains that caused more than 5 percent of vaccinated individuals to progress to AIDS in 25 years led to perversity and if you just want to think about testing these vaccines, HIV vaccines in clinical trials that is an enormous problem. So, whether or not a vaccine will cause a perverse effect will be situation specific and depend upon the risk of becoming infected and this really then is the big problem with small pox.
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From page 207... ...
It should only be used basically if there has been a major release of small pox and we are convinced that the number of death, therefore, are going to be greater than the number of deaths that would occur without using the vaccine. So, to go through the mathematical bioterrorism literature, actually the first paper is back in 1760 by Daniel Bernoulli.
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From page 208... ...
208 - is in 2001 by the CDC, Modeling Potential Responses to Small Pox as a Bioterrorism Weapon. Then there are two more papers.
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From page 209... ...
MR. LEVIN: I have a question, Sally, which is when you are looking at these cost benefit tradeoffs in terms of -- is there any notion of discounting them in terms of how long in the future you push the -- or how late in one's life?
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From page 210... ...
BLOWER: We have looked at that, that basically that you avert because, yes, you don't prevent basically in the Science 2000 paper for HIV, you can show that you avert AIDS deaths and that that is a significant effect and, therefore, very worthwhile, as well as the number of infections prevented.
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From page 211... ...
Analysts clear with this situation by using uncertainty analysis and sensitivity analysis basest upon something caI1ect Latin hypercube sampling, which is a type of stratified Monte CarIo sampling. Essentially all you need to know about this technique is that parameter-estimation uncertainty is being translated into prediction-estimation uncertainty.
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From page 212... ...
Dr. Levin has also served as president of the Ecological Society of America and has won its MacArthur Award and Distinguished Service Citation.
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From page 213... ...
What I would like to do, if we can get the slides on, is to first of all touch on some of the points we heard, review them and put them into context, maybe try to identify some challenges, including some topics that haven't been hit and finishing up with sort of a pet hobby horse of mine, which has to do with system level aspects, indeed, the notion of developing a system level immune system. As we have heard, especially in the last two lectures, there is a large classical literature in epidemiology and, indeed, in much of mathematical modeling and infectious diseases, the focus has been on the sorts of things that Sally just talked about and we have talked about before that; namely, developing predictive models that will help us to understand what the spread of an infection will be once introduced into the population.
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From page 214... ...
Indeed, they don't even have to all be infectious disease agents. It could be different kinds of terrorist attacks coupled with bioterrorism.
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From page 215... ...
~_, ~ ___ at least four different categories dealing with infectious disease modeling and I am sure there are others, most of which we have heard about, but they relate to how do you detect the surveillance systems about which we heard this morning, prediction. The response systems once a disease appears in the population and tracing, that is, how do you trace back to identify where the source is, something which we have seen doesn't work very well in the case of the anthrax attacks, but has been used, for example, in the foot and mouth disease in the U.K.
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From page 216... ...
So, models not only are going to be useful when there has actually been an attack, but they can be extremely useful in training people or helping you to identify where you ought to be putting the resources and what is the best way to set up response systems. There have been a few exercises of that sort, but not a lot and typically the models that have been used have been fairly unsophisticated in driving the epidemics in those systems.
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From page 217... ...
) would be with death rate and gamma would be the recovery rate and, therefore, understand that there are various ways to control the disease by focusing either on improving the recovery rate -- you could also increase the death rate, 217
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From page 218... ...
Secondly, to reduce the mean infectious transfer per individual. For example, we do that with sexually transmitted diseases by the use of condoms and other ways by isolating individuals who are infectious and in itself is important, that is, the population size is important and one way we get at that is through vaccination to reduce the size of potential infectious individuals.
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From page 219... ...
219 about, is a challenge. Another challenge in the individual-based models, which relates to this question is how do you reduce the dimensionality of the system?
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From page 220... ...
So, rO, certainly can be temporarily -Now, in addition to the spread of infection over time, there is also the problem of spatial spread and there are two dimensions to that. One is the spread of the agent.
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From page 221... ...
So, understanding spatial spread is crucial. That has multiple scales to it and the same explanations may not be true on all scales.
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From page 222... ...
We are first of all dealing with a game theoretic problem in which 222
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From page 223... ...
So, it is really a game theoretic situation in which you are dealing potentially with multiple agents about which -- whose introduction may be unpredictable and, therefore, it is crucial to develop responses to have systems that are adaptive, that have the capability to respond to unpredictable attacks. In other words, to develop essentially an immune system for the whole system.
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From page 224... ...
224 MS. BROOME: Thank you.
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From page 225... ...
Most mocteiing of spatial spread involves mocleling the spread of the agent, although analyses and actions relating to the mobility of inctivicluais have proven effective in such epidemics as foot and mouth disease Outbreaks related to terrorist attacks as opposed to acciclental introductions. These are game-theoretic problems, in which the terrorists are trying to outsmart us.
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From page 226... ...
. He has devoted the past 20-plus years to the study and prevention of infectious diseases in the United States and in various countries in Africa, Asia, and Latin America, initially at the Centers for Disease Control and Prevention (CDC)
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From page 227... ...
We are going to go from power point to slides, back to overheads. I am going to actually focus my comments primarily around the context in which Ken is doing the work he is doing about detection of bioterrorist events and outbreaks.
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From page 228... ...
The implication here fundamentally in terms of bioterrorism is we would like to have a system in place that would permit us to detect illnesses quickly and then be in a position to respond rapidly to keep morbidity and mortality to a minimum. Now, in terms of surveillance needs for bioterrorism, there really are two phases, I think, one can look at.
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From page 229... ...
Similarly, we learned a lot of outbreaks from an astute clinicians, who recognize the one or more cases of an illness are more than they should be seeing and they are smart enough to let the health department know about that. If you could say, there is an intrinsic comparison of what the expected is, but it is primarily because that individual or that individual and someone they talked to on the elevator come to the conclusion that they 229
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From page 230... ...
What I would like to point out is a couple of things about this actual bioterrorist event that we now have experience with. The first is that these cases were primarily brought to our attention by astute clinicians; that is to say, a doctor was able to look at a patients and say I wonder if this person has anthrax based on the 230
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From page 231... ...
This particular event obviously had different features, which would not have been readily detectible by the systems that many people are building. So, what are the various approaches people are taking to improving surveillance to detect bioterrorist events?
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From page 232... ...
Some people are even considering direct monitoring of samples of the population through Nielson rating type setups, in which people are routinely answering questionnaires over the Internet, a whole host of different, creative approaches. I think we need to give some attention to the question of how likely is it that these kinds of systems will actually improve our early detection of bioterrorist events.
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From page 233... ...
This is also just to point out that, in fact, we currently do have surveillance systems in place and have had for a long time for influenza, not just on what proportion of deaths are due to pneumonia, but an outpatient visits to sentinel physicians and to a number of other indicators that all pretty much tell us that influenza is a seasonal disease and that all tend to peak at approximately the same time. I would really like to point out and you may not be able to read this very well is people in France a number of years ago were interested in the question of how well do it is not just the are many things can monitor, but to detect something stage or small pox 233
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From page 234... ...
They were looking at everything from emergency visits to sick leave reported to the National Health Service, sick leave reported by companies, visits to general practitioners, hospital fatalities, a whole host of drug consumption, many of the things that we are considering looking at now and measuring how sensitive, specific or the positive predicted value. By sensitivity we mean of all the outbreaks that occur, what proportion will be predicted by this indicator.
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From page 235... ...
What I would point out to you is if you set up these systems in many counties or many parts of the country, in any given county, in any given week, there will be zero bioterrorist attacks. Therefore, every positive -everything above the baseline that stimulates a response, if all you are looking for is bioterrorist events, a hundred percent of the events you detect will be false positives in most counties most of the time.
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From page 236... ...
So, let me just end -- I think this is the last one -- there are a lot of things we need to think about in figuring out how to affect bioterrorist events. Ken has referred to monitoring people who have a febrile respiratory illness and that is how things like anthrax and small pox will present initially.
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From page 237... ...
I would like to just remind folks that the overall session was on detection and epidemiology of bioterrorist attacks. So, even though Ken and Art have focused on the detection issue and I think there is a number of threads there that we could pursue, I do hope that we also pay attention to the epidemiology; that is, what is the distribution of an outbreak once it occurs and what is the strategy and effectiveness of the response to that outbreak.
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From page 238... ...
DR. BLOWER: For the HIV vaccine models, all we can do is make sure that they fit the current data because there are no vaccines out there and nothing has been done.
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PARTICIPANT: Also a question for Sally. In your sensitivity analysis and uncertainty analysis, how large are your systems and how many parameters do -DR.
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One slide I was going to show, but didn't was showing the results of the traffic simulation, which estimates traffic counts you would observe on different -on particular streets in the city. We can verify those against collected counts or just do simple hypothesis testing.
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PARTICIPANT: I have a question both to you and to the panel in general. When you had your contact graph, you compared it to the random graph and to the social network graphs.
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242 turn the mathematicians and figure out to generate those kind of graphs. For instance, for the small world graphs, Strogatz and Watts decided to look at triangles, numbers of triangles in a graph compared to what you might expect in a random graph.
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I was interested -you know, you are applying your aberration detection tool to influenza-like illness and there is an obvious reason for that and you also do have a lot of historical comparable data. But another approach that is taken for early detection is to try to pick markers that might be more specific.
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We also actually run a very similar system for upper respiratory complaints and upper and lower gastrointestinal complaints and we get a lot more visits for upper respiratory complaints than for the lower respiratory and a lot fewer for either of the gastrointestinal things. My sense is from looking at the way the models worked in the past six months when we have been running it, that it doesn't work as well for the rarer events.
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From page 245... ...
245 fingerprint of the particular outbreak organism and we digitize it and we can look across a national database to say there is an excess of that particular organism. That is sort of the opposite, where you are taking a highly specific signal, even though you are trying to pick it out from a huge background.
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246 PARTICIPANT: I wanted to comment that the social networks graphs and the kind of distribution of connectivity that you show in your graphs is very closely related to the kind of linkage you see in the worldwide web pages and there is a heuristic that motivates that that applies to the same kind of situation you are trying to model. So, it is something to go on line to look at, I think.
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It is a very similar problem that is also based in probably homeland security. But, of course, the rate of infection spread is -MS.
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Obviously, you don't want to do that once small pox is actually happening.
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MS. CHAYES: But there are some structures for that on a small scale, like the new Bampf Research Center has focused research groups, where people, you know -something on the order of five or six people can come together for a couple of weeks and work together away from their institutions, if you can manage to get away from your labs and your students and your families, but, you know -which is obviously a difficult thing, but there are structures in the research community now, I mean, there is the infrastructure to respond to that in a way that there wasn't a few years ago.
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MS. BROOME: I would like to suggest that the way the research -- the workshop is set up has the potential in terms of you brought in folks like me, who are not mathematicians, but I actually spend a lot of time thinking about what do we need to have an effective surveillance and response infrastructure.
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On the other hand, I have heard some -- you know, there is clearly a whole area around detection that Ken is addressing, but indicate a much broader range laid out, which are going to alone as was alluded to in the data mining session, aberration, detection issues there is, as I was trying to of possible syndromes, as Art have different challenges, let you know, you have got to have the data to apply these to. So, there is some highly applied questions in having data available electronically so that these wonderful tools can be used.
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What I have seen happening in network research is that for awhile people were just looking at the structure of networks like the Internet or the worldwide web and now 252
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MR . TONDEUR: When you say games theory, I sort of -- if I were a terrorist, I would do the following game theoretic approach.
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Do I assume that -- or how do I, if I am interested in response system, create a response system based on the fact that the terrorists are going to respond to my response system. So, those are the -- what makes it a game theoretic problem.
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There are more automated systems that are looking at more pathogenic agents. We can feed into the data mining thing.
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MR. MC CURLEY: -- way of merging the first session on data mining -- get rid of these delays.
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For traditional public health surveillance because it includes individual identities, it doesn't lend itself to wide open, although certainly the project that I am managing actually 257
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Then there is some fairly substantial data sets that are put together, for example, of pharmacy data that is de-identified. But most of these are -- you know, they rely on a number of collaborators.
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259 MS. CHAYES is giving a Also, one other thing, everyone who presentation, please give us a transparencies or your power point presentations 259 copy of your .
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One approach is to monitor visits to health-care providers, particularly outpatient visits, emergency-ctepartment visits, ciinicaI-microbio~ogy laboratories, and indicators such as 91~ calls, over-the-counter drug sales, and absenteeism at work and at school. Some people are even considering direct monitoring of samples of the population through Nielsen rating-type setups, in which a large group of inclivicluais is routinely answering questionnaires over the Internet.
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Key Terms
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