cc  >> Cathy Vrentas: Hi, everyone.  Welcome to Wednesday Nite at  the Lab here at the UW  Biotechnology Center.  Tonight we're welcoming  Dr. David Van Sickle who has an  extensive background studying  respiratory affects and  epidemiology.  So his background has included  studying asthma for a diversity  of populations including some  research in India.  He was an officer in the  Epidemic Intelligence Service at  the CDC, Centers for Disease  Control and Prevention, and he  investigated a variety of things  including some of the health  effects of hurricane Katrina and  some of the Effects of exposure  to mold in New Orleans and  exposure to gases in the air in  different sites across the  country.  In 2006 he left the CDC to  become a Robert Wood Johnson  Health and Society Scholar here  at UW Madison, and he's  continued his research on the  epidemiology of respiratory  disease including a function or  focus on asthma research.  So please join me in welcoming  him to Wednesday Nite at the Lab  today.  (applause)  >> David Van Sickle: Thank you,  very much.  It's a pleasure to be here, and  I appreciate you guys making  time tonight to hear me talk.  As Cathy mentioned I came here  from the Centers for Disease  Control where I worked in the  air pollution and respiratory  health branch. 

 And lot of this work grows out  of my experience doing field  work on respiratory diseases  like asthma, a chronic  obstructive pulmonary disease.  Tonight I'm going to talk about  what I've been working on for  the past couple years which is  the development of this device  that goes on asthma inhalers and  lets us track where and when  the inhaler is used.  I'm sorry I'm recovering from a  bit of a chest infection so  you're going to have to excuse  the coughing.  So I want to start tonight by  talking about some events that  happened more than 20 years ago  in Barcelona, Spain, which is,  for those of you what haven't  been there, a beautiful city on  the Mediterranean of about a  couple million people.  And there in 1981 physicians at  four large urban hospitals began  to report these fairly sizable  outbreaks of asthma.  On the days when they occurred  you'd see this dramatic spike in  visits.  So here's just a figure of the  typical January when one of  these days fell on the 21st, and  you can see a fairly stable rate  of visits across time and then  this real big surge and one day  and then it goes away.  These visits were also much more  likely to result in people being  admitted to the hospital or  dying from asthma.  So fairly severe effects.  So a group called the  Collaborative Group of Barcelona  was formed to investigate, try  to figure out what was causing  these. 

 And they really spent a long  time, I think around six or  seven years, investigating this,  collecting all kinds of various  meteorological data, climatic  data, environmental pollutants  and pollens, but over the course  of the next seven years a total  of about 26 outbreaks would be  recorded.  So they weren't really able to  ever identify what was causing  this.  The clue finally came when they  decided to actually find and  interview the people who had  shown up at the hospital.  There wasn't anything really  different about these folks in  terms of their clinical  characteristics or their  demographics, by that I mean  their sex or age distribution.  They asked them where they were  when their attack began they got  what ended being the key piece  of information.  This is just a figure reproduced  from one of their papers showing  sort of down in the bottom  middle you can see the dots on  the map.  They were able to pinpoint on  the map where the folks' asthma  symptoms started.  And this was really the turning  point in the investigation.  It drew their attention to the  waterfront and the activities  going on in the harbor area of  Barcelona.  Here you can see just a little  bit up more closely. 

 The group was then able to  narrow their focus to the  activities and the environment  in this area, and someone had  the idea to pull the records of  the cargos from the ships and  the barges that were calling  into port in Barcelona.  Does anyone have an idea or  anyone heard this story before  can help me think about what it  might be?  Well, it turned out that the  cause of the outbreaks was  soybean exposure.  What had happened is the people  who built the harbor silos  hadn't installed the proper  filters.  So when soybeans were unloaded  or loaded onto the barges and  ships they were releasing these  large clouds of soybean dust.  And this was what was causing  people in that area to develop  asthma symptoms and wind up in  the emergency room.  This was really the first time  that soybeans were implicated  as an important -- agent in  asthma outbreaks.  It actually occurred again in  New Orleans some years later.  So once they put the appropriate  filters on the harbor silos the  long series of asthma outbreaks  was brought to an end, and the  excess morbidity in terms of  hospitalizations, deaths and  emergency room visits came to a  stop.  So since then we've learned a  lot about asthma, but it's still  a significant problem.  And, in particular, we focused a  lot about learning more about  triggers of asthma like ragweed  pollen here or tobacco smoke. 

 Even workplace exposures, we  know a lot more about that since  the Barcelona outbreaks.  And air pollution, as well.  And in the last 20 years we've  made pretty substantial  improvements in asthma  medications.  Almost everybody now, this is  sort of the main line of  therapy, everyone uses  anti-inflammatory medications  that are designed to address the  underlying pathophysiology of  asthma, airway inflammation and  hyper responsiveness.  And really designed to prevent  people from having asthma  symptoms.  And almost everyone has one of  these things, an inhaler, a  bronchodilator inhaler or a  rescue inhaler that they carry  around as they go about their  daily life and use it when and  where they have exposures that  cause symptoms.  So it works really quickly to  open up the airways and to  relieve wheeze and cough.  But despite all these  improvements we really haven't  made much progress addressing  the sizable morbidity and  mortality from asthma.  Each year in the US asthma still  accounts for 27 million missed  days of school and work.  A total of 2 million emergency  room visits or about a quarter  of all the emergency room visits  in our country. 

 Half a million hospitalizations  and 5,000 deaths.  So we're really not making much  progress in reducing this  important and costly and  unfortunate morbidity and  mortality from asthma.  So I took a couple of papers  from the literature and looked  at what percentage of folks who  enrolled in these clinical  trials had controlled asthma or  uncontrolled asthma.  So I'm going to pose this  question to you guys.  These are two recent studies,  which parts of the pie do you  think are the controlled  asthmatics in these studies?  Any ideas?  >> (inaudible)  >> Van Sickle: Right,  it's incredibly low.  23% in a recent clinical trial  in -- and 41% in a larger view  of primary care cases from  Canada.  So we're not making great  progress.  The majority of patients with  asthma don't have adequate  control of the disease.  In fact, fewer than one in five,  sorry one in four.  Physicians, when patients come  into their offices, physicians  are able to assess how well  their patients are doing. 

 They can do spirometry, they can  take a history, do an  examination and really get a  good idea how well the patient  is under control.  But what happens is when the  patient is out in the community,  increasingly they're being asked  to take responsibility for  managing their disease over  time, deciding when they need to  adjust their medication or come  back to the clinic for  additional treatment or a  different type of medicine, and  this is a typical asthma diary.  It involves a lot of work on the  part of the patient recording  symptoms, peak flow, the use of  various medications over time,  and not surprisingly as a result  these things are very flawed.  They're burdened by people  forgetting to fill them out.  People deliberately sort of fill  them out right before their  appointment to please their  physician.  They forget to keep track of  various aspects of them.  There are just all kinds of  problems with these instruments.  Not to mention just the burden  of time it takes in your daily  life.  But assessing asthma control has  become really pivotal so people  have tried to simplify these  come with questionnaires, simple  five-item questionnaires that  people can take as they're going  about their daily life that  would give the physician a  good indication of how well  they're doing.  One of those questions, pretty  much on every one of those  instruments, they ask how often  have you used your inhaler in  the last four weeks. 

 And trying to remember that is a  pretty significant challenge for  a lot of folks.  The other problem with these is  that they sort of depend on the  patient having the same  perspective of the doctor.  And it turns out the majority of  the patients in a bunch of  studies, including the ones I  showed, those folks who don't  have good control of the disease  actually think they have it very  well managed.  So objectively, when you look at  how they're doing, you figure  out how often they're using  their medicine, they're doing  very poorly and we could do a  lot better.  There's a big gap between where  they are and what we're able to  accomplish if they were to be  appropriately controlled.  So almost 85% of those with poor  control regard their disease  as adequately controlled or very  well controlled.  It's pretty surprising.  The Lancet recently wrote an  editorial sort of taking  epidemiology to task and saying  that progress in understanding  the disease triggers in asthma  has been slow and confusing.  The harder one looks, the more  questions arise.  And I think part of the reason  is that epidemiology really  hasn't taken advantage of all  the information we've got  available about asthma. 

 By that I mean what we end up  with is maps that show where  people who were hospitalized  lived.  But it doesn't tell anything  about where the attack began  which was the important piece of  information in the Barcelona  epidemic.  So here's a typical  epidemiological analysis showing  rates of hospitalizations by  where the person lived.  So if the person's attack  started at work, at their school  or somewhere out in the  community they still end up on  this map, the point of data that  goes into this map is the  location where they live.  And here's another effort to  make sense of asthma sort  trigger points or exposures in  Manhattan also using the  residential location where the  person was hospitalized.  So public health has really  focused on the house.  Not surprisingly we have all  kinds of environmental  interventions designed to target  the home, clean up the home.  And I think we haven't really  taken advantage of all the  information we could have about  variations in where asthma  related exposures and symptoms  occur.  So I worked as an Epidemic  Intelligence Service Officer at  CDC and we were sent out to do  outbreak investigations.  The whole time we were there we  were never able to do outbreak  investigation of asthma. 

 So when I left CDC and came to  Madison I started thinking what  was the key piece of information  that was missing.  Why weren't we ever able to  investigate an usual outbreak or  a cluster of asthma in a  community.  It turns out it's just  incredibly rare.  So CDC and state public health  agencies have conducted a total  of almost 1400 joint  investigations into outbreaks of  diseases in the last 16 years.  A total of three or 0.2%  were focused on asthma and  one of them was basically a  program evaluation and there  were two death clusters that  were picked up, one in Georgia  and one in Maryland.  One of the most important  chronic diseases of childhood,  one of the most important  chronic disease in our country,  we're not able to investigate  changes in the disease  prevalence over time and space.  So I started thinking that the  piece that we were missing was  that people were carrying around  this inhaler, and they're using  it when and where they're  exposed to things that cause  them to develop symptoms.  And it occurred to me that if  you were able to see everyone in  the community carrying around  their inhaler and see the point  in space and time when they  actually use their inhaler and  then aggregate that information,  you might be able to learn  whether there was some kind of  exposure in the area that was  causing folks to develop asthma  symptoms.  In addition, you would have  instant and much better data  than what we currently collect  object the burden of asthma in  the community, how often people  are having symptoms in their  daily life rather than just this  tip of the iceberg that we've  been collecting in public  health, that is emergency room  visits, hospitalizations and  deaths.  Remember I said there's like 2  million emergency room visits  and half a million  hospitalizations but 27 million  missed days of work. 

 So there's this incredible  amount of significant asthma in  the community that we don't know  anything about.  And even CDC said, we need to  improve the timeliness and the  geographic specificity of asthma  surveillance data.  So that was my cue.  So a couple of years ago it  occurred to me that electronics  that would allow us to track  where these inhalers were used  and have them report that  information to us were getting  small and cheap, and it was  almost trivial to put on an  asthma inhaler and give them to  patients, let them carry them  around.  And patients, at the same time,  had started participating in  websites and in communities  where they're actually  volunteering a little bit of  information about their disease  in order that it could be  aggregated and perhaps we could  learn something new about  Parkinson's disease or the  treatment of some other chronic  condition.  So this is the first prototype  which I had built with a team of  four undergraduate students in  biomedical engineering two years  ago.  It was fairly big.  It looked a little bit like a  washing machine on the side of  an asthma inhaler.  And a little bit foreboding  especially to TSA when I took it  to conferences.  Here's a view of the inside of  it. 

 A large battery, the GPS at the  time was fairly power intensive,  but over time we've managed to  slim it down.  This is the second version of  the device that we ended up  using in a pilot study I'm going  to tell you a little bit more  about now.  So this is, I can pass it around  or you can come look at it  afterwards.  This is the size.  It just fastened on to the side  of the inhaler.  Folks carried it around.  And when they used the inhaler,  it recorded the time and place  of the device and sent us a  message over a cell phone  networks which we put into a  server and that's sort of the  end of the data transmission.  This is a typical day in our  lab.  A lot of soldering, trying to  keep the costs down, make the  thing as small as possible.  And the electronics ended up  being pretty small. 

 The part in the middle, the big  black part, is a SIM card  holder.  So this operates a lot like a  cell phone.  You just take the card out of  the phone, shove it in there and  it gets on the AT&T network.  This is our batch of batteries  waiting for us to solder them  into the device.  And that's sort of what it ended  up looking like.  Again, you're welcome to come  take it.  We also built a suite of online  tools including a bunch of maps  and charting software so that  patients and their physicians  could see where and when they  were using their inhaler during  the study.  And this is a report that was  sent to participants in the  study ever week showing them how  often they were using their  inhaler, whether their use was  exceeding national guidelines,  so thresholds of use that  National Institutes of Health  set that sort of define what's  in control and out of control  asthma or uncontrolled asthma.  As well as a little bit of  information about what their  peers were doing, other people  who were in the study.  That was something that we were  asked to add. 

 So we recruited adults with  asthma from primary and  specialty care here in  Wisconsin.  And we compared, the goal was A  just to see if people were  willing to carry around this  thing and use it routinely.  And then to compare the results  with these more conventional  forms of monitoring that I  showed you earlier, those asthma  controlled tests, the  questionnaires that people had  to fill out.  And then we wanted to see so if  we had all these people and we  started aggregating data could  we learn anything interesting  about the epidemiology of asthma  attacks in the community.  And then, as I mentioned, get  feedback from patients and docs  which we did in spades, of  course.  So this is a quick graph to show  who ended up in our study.  They were fairly young overall.  There's really nothing special  about the demographics of them.  But what is interesting is that  not many of them had controller  medications.  So remember in the beginning I  showed you there's two kinds of  medication. 

 One that people can take  everyday that keeps them from  having symptoms and then one,  the one I track, that's designed  to relieve symptoms when they  occur.  Pretty much every asthmatic  should be on some kind of  controller or preventive  medication, but only less than  60% were in our study.  And also people weren't in  possession of things we consider  key components of asthma  management like an action plan  or what they should do if their  asthma went out of control when  they're out in the community.  Or of influenza vaccinations,  peak flow diaries, peak flow  meters and asthma diaries.  We also had fairly high health  care utilization in the sample.  So during the past year a lot of  ED visits for asthma,  hospitalization, unscheduled  doctor visits.  So it was a fairly active sample  in terms of the asthma.  And I should mention the asthma  control tests up there.  So 19 is the score where we  consider it to be, 19 and above  is considered to be controlled  asthma.  But these folks, the mean was  actually under that threshold. 

 So quite a few uncontrolled  asthmatics as you'd expect  looking at the utilization and  you'll see the amount of  beta-agonist use.  Any questions about the study or  how we set it up?  Yeah?  >> How do you deal with people  who don't want to have that  diagnosis in their record?  >> Van Sickle: To enter in our  study they actually already  have to have a diagnosis.  So they come forward or their  physician refers them.  So they've already come to  terms, I think, with that.  They have to have the medication  also.  Yes?  >> So how many people  participate?  Is it currently ongoing?  >> Van Sickle: Nope.  So we wrapped up the study on  August 9th.  We ended enrolling a total of  35.  Four dropped out, actually they  went completely missing with my  device.  Mainly because, as you'll see,  there's a fairly significant  burden of surveys. 

 Once a month we asked people to  fill out surveys, and those four  people just decided they'd  rather not do that.  I haven't turned on the device  which I can do remotely to see  where they are and track them  down but I've thought about it  on days.  (laughter)  Have a dark suburban  pull up at their house.  Excuse me.  Anything else?  Should I go forward?  So I'll show you some results  now and then kind of talk about  what we're doing next.  So I analyzed the data for  tonight looking at all the use  that we captured through June  1st of 2009.  So we saw a total of 552 uses of  inhaler on 244 days.  And I think by August 9th, when  we shut it down, we had 1300  observations.  So I can also tell that the  device, since it's a cell phone  it's always kind of in  communication with a cell phone  tower.  So if somebody ran over it or  turned it off or just left it  and never charged it, I can see  that the device isn't on. 

 There's periods where people go  dark in the study and then they  come on.  It makes for a really  complicated analysis, but it  makes it more accurate because I  know whether the thing was  actually working or not.  So that's what I'm doing that by  way of introduction to this when  the devices were active.  So people used the devices on  31% of the days the devices were  active and then on 19% of the  days that they were enrolled in  the study overall.  So the columns are participants,  and you can see on the Y axis  it's the percent of days that  the device was active where we  detected a use of the inhaler.  So some folks it's a really  interesting distribution.  Some folks are using it  incredibly frequently.  Almost 90% of the days.  Other folks are not hardly using  it at all.  They went through the entire  study with one or two  inhalations or events. 

 And then there's these sort of  steps that occur in this  distribution.  We see this in the overall data  too all the way to the end.  So what's really great about it  is you can look at a graph, an  administrative panel on the  computer and you can really  quickly see who needs more  attention.  Who do we need to bring back  into the clinic to figure out  what's going on, why their  asthma isn't better under  control.  And looking at this, look at the  person down on the bottom.  They're obviously having a hard  time.  The national guidelines say they  should be using it on two or  fewer days per week.  And these are daily columns.  So that person needs to come  back and we need to figure out  what's going on with them.  Person number two, probably  doing okay. 

 They've had a couple days with  symptoms but overall doing all  right.  And look at the person on the  bottom.  We actually had sort of an  ethical quandary of what we do  with this person because there  was so much inhalation and so  much usage that we ended up sort  of intervening and trying to get  them to go back to their  physician and get more help.  Whereas the person at the top,  doing great.  So just with this real quick  glance you can see who's doing  well, who's not doing well.  And this ties into a lot of the  feedback we got from physicians  at the end and healthcare  providers.  They said I don't want to see  every inhalation of my patient I  just want you to notify me when  something's going wrong.  They called it alert by  exception.  Let me know when one of my  patients in my whole panel needs  more attention.  Does that make sense?  So the other thing that people  were real interested in having  us analyze is when were people  using these rescue inhalers. 

 So what we've started looking at  is the time of day when people  were using the beta-agonist, the  inhaler.  And you see these really  interesting bumps when people go  to work, when people leave work  and come home and then probably  before people are going to bed.  Excuse me.  So, of course, like the sexy  thing is the mapping and  figuring out where people were  using them in time and place.  And this is four maps of  different people who were in the  study, and I keep it zoomed out  so you can't actually see their  houses.  But what's interesting is look  what happens when you start  looking at a single person's  use.  This turns out, when we showed  them the participant it turns  out to be their commuting path.  So this is their commuting path  from a home in, I guess near  Lake Kegonsa to a workplace up  by the Dane County airport.  So it ends up tracing this  commuting path and showing  locations of use at multiple  areas in town.  Public health and  epidemiology have assumed this  person is also having asthma at  home. 

 In fact, what our study shows is  they're having asthma symptoms  all over the place.  At parks, at school, at the  workplace.  We have a couple of people who  became aware of workplace asthma  by participating in the study  and seeing for the first time  the amount, the burden of asthma  that occurred in their  workplace.  This is another person who  actually did have asthma  symptoms all the time at home.  You can see all of the points  piling up on top of her house in  the map.  So the bottom, the real dark one  there right above or below  Plover is the point blown up in  the inset there with I don't  know how many inhalations that  was in her home.  So it's fairly accurate.  You can see from the map that's  it within a really reasonable  degree of accuracy.  So as I mentioned one thing we  wanted to look at was how well  did the data we collect stack up  against these other measures of  asthma control, having people  fill out these questionnaires  all the time.  So we have, not surprisingly,  people who were controlled by  the questionnaire used the  inhaler on fewer days than  people who were uncontrolled by  the questionnaire. 

 So we see some validity on the  face of it.  We also found though that if you  take someone's ACT scores calls  them controlled and you look at  how often they're using their  inhaler, a lot of times the  label, the ACT score masks some  significant variability.  So you can have someone who  appears controlled by their ACT  score but is actually using the  inhaler all the time.  So this is sort of our first  analysis of this, but it seems  like there's some real  shortcomings there.  What we're exploring is what if  you take just the number of  events and feed that into the  ACT.  We could probably improve,  rather than asking someone to  remember how many times in the  last four weeks did you use your  inhaler, having them put it on a  five point scale, we just feed  the actual number of uses right  into that and we come up with a  much better score.  So the other thing that's  apparent so far is that it seems  like being in our study and  having these weekly email  reports saying, hey, your  asthma's on the increase you may  need to see your physician, you  may need to remember just to  take your preventative  medication more often, it seems  like being in our study actually  results in an improvement in  their ACT score over time.  There's a lot of confounders we  have to analyze and it's fairly  complicated time-dependent  analyses.  So I'm just giving sort of the  rough cut right now.  But it seems like the ACT score  goes up by two and a half points  by the end of month two when  they have to complete this  monthly survey I mentioned  earlier. 

 And that's actually a pretty  significant increase in ACT  score.  >> What did you say ACT meant?  >> Van Sickle: ACT is  a five question questionnaire  that patients complete  that gives the physician  an idea of how in control  or uncontrolled their asthma is.  >> What do the letters  stand for?  >> Van Sickle: Asthma  control test, sure.  Any other questions about the  results?  It was pretty fast.  Yeah?  >> Just one question, I don't  know much about asthma, is  stress a trigger?  >> Van Sickle: Stress is  a trigger for some people.  >> Okay, because I was just  looking at the commute coming  into work, maybe when they're at  home more stressful environment.  >> Van Sickle: Right.  It's possible.  So one thing...  >> Can you repeat the question?  >> Van Sickle: Oh, sure. 

 She asked if stress was a  trigger for asthma.  And was highlighting that  perhaps the fellow who had a lot  of inhalations along his commute  path perhaps stress had been a  factor in that.  And I don't actually know  whether stress was involved in  those events.  However, we did ask people quite  a lot of questions at the end of  every month.  Things like had anything changed  at their job or at home that  would impact potentially the  number of times they would have  asthma symptoms, as well as just  had you been to the hospital for  asthma or other changes in  asthma management.  And we haven't gotten a chance  to look at all that yet.  So it could be we learn some  things from there.  Other things that I forgot or  didn't cover in enough depth?  Yeah?  >> Did you find anything  correlating with the -- plants  in Madison?  >> Van Sickle: No,  that's something that we  just started looking at whether  there were air quality event  days and whether we see an  increase in the number of  inhalations.  No, but that's sort of at the  top of the white board right now  for things to do.  Thanks for the vote of  confidence in that. 

 So at the end of the study we  wanted to get feedback from  patients, physicians, even  public health folks about  whether this was useful, whether  this was something they would  do.  It turned out that just sort of  on the device level it was a  little too big for some people.  Actually mainly for men because  men tend to carry it in their  front pocket.  Women tend to carry it in a bag,  this is what we've heard anyway,  so the men were fairly  encouraging about trying to get  us to reduce the size.  The other thing that we learned  that was really interesting is  that this has a battery life of  about two weeks, and people  basically forget that they  needed to recharge it, it lasted  too long.  It wasn't sort of compatible  with the, oh, man, I need to  recharge my cell phone every  night.  So people have these consumer  electronics that need so much  power that ours made all these  efforts to make this have a long  battery life, and it was  actually the wrong thing to do.  You need to make something that  fails in about two days so  people develop the habit of  recharging it.  So what would happen is people  would just forget that it needed  to be charged and then suddenly  they would be calling me saying  it's not working.  I'd say when was the last time  you plugged it in?  About two weeks ago. 

 So that's what we learned about  the device.  The other interesting thing, I  don't know if you care about  these little anecdotes, but the  other interesting thing is it  used to beep and people told us  we don't want the thing to be  beep, we want it to flash a  light because if it beeps I  can't use my inhaler discreetly  in a movie theatre or at a  restaurant.  So you learn all these really  intriguing things about having a  chronic disease and how it's  managed and that you never think  about going into it.  Anyway, so we learned some great  things from the patients.  We asked them to fill out these  surveys at the end of their  participation and so far have  been really promising.  Some of the themes are people  are more aware of how often  they're using their rescue  inhaler which in my mind is kind  of key to changing the  management of asthma.  The other thing people were able  to see, they called it whether  it was under control or not.  And in a couple of cases people  were able to see that their  asthma was well controlled and  it realized a little anxiety in  that I've realized that my  asthma is well controlled, and I  don't need to worry about it so  much.  Like that last person.  A lot of indication that people  were learning about and  developing a better  understanding of triggers that  might be causing their asthma  symptoms. 

 Here's just some quotes that I  liked from the survey.  And then more awareness of  patterns of asthma over time on  a small scale or over time on a  bigger scale.  Times of day.  I mentioned the couple of folks  who learned about workplace  asthma.  And then I guess most hopefully  some better preventive practices  emerged.  We see people by the end of  their participation taking a  more active role in adhering to  their controller medication.  Trying to use it on a more  routine basis and also then  seeing this relationship between  when they start using their  preventive medication you see  the need for rescue medication  going down.  So seeing that relationship  hopefully reinforcing the  positive use of preventive  medications.  So I'm going to end just by  talking about what we have next.  Over the summer we  simultaneously worked on getting  the device a lot smaller and a  lot lighter and addressing all  of the feedback we were getting  from patients. 

 So now it's tiny.  It's this size.  It goes on the end of the  canister instead, and it doesn't  have the sound.  It has instead some fancy lights  that flash.  And so you're welcome to come  look at it.  But overall we think we've  addressed everything we learned   from that first round of  participants.  We're going to target our next  study to looking at differences  in asthma among rural farm  residents and rural non-farm  residents which is a really  intriguing question in asthma  epidemiology that's been looked  at a lot in Europe and  internationally but not at all  really in the United States.  So it's something we wanted to  tackle and we're doing that in  collaboration with the Centers  for Disease Control.  We're also currently about to  ship a bunch of devices to  various agencies and academic  centers for use in environmental  and exposure assessment studies  that are going to be starting  this fall.  One of them looking at exposure  to gases from volcanoes,  another looking at just more  routine traffic exposure. 

 So here's a picture, some  drawings of the new device.  I forgot I had these movies so  you can actually see it up  close.  So that's how it attaches to the  end of the inhaler.  And the top is just a floating  button that when the inhaler is  used it closes a switch and it  logs the event.  We also have been building some  mapping tools that allow us to  aggregate use and see sort of  quickly overall what's happening  in the community level.  This is just showing you how you  can animate the use over time.  You can also change the scale so  you can collapse a use across  just all the weekdays.  See it animated by Monday,  Tuesday, Wednesday, Thursday,  Friday or by hour of day.  You can highlight parts of the  histogram and see who is  actually experiencing symptoms  during that time.  And you can do some basic  filtering and searching. 

 So this is, the other thing  we've been working on is a  mobile diary.  Remember the big paper thing I  showed you before where people  would have to record all that  data over the week.  I would never do it even if it  was my kid or myself.  So since I carried around a  phone I thought we really ought  to make something for the phone  that would both allow people to  contribute data to the project  who don't have a device,  as well as just allow people to  do what they have to do on paper  now but much more conveniently  and with location because your  phone has all these cool sensors  in it that can contribute data  to the report.  So the mobile phone diary let's  people track their use of  preventive medications and sends  compliance reminders if you want  saying you didn't enter your  routine medication today.  You can map where you used your  inhaler, and then you can add  things like what kinds of  symptoms did I have.  What do I think might have  caused this.  There's a page for triggers.  And you can see the list, and  you can see the chart showing  you the same thing we deliver in  weekly email report but you see  it right there in realtime on  your phone.  So the last thing we're doing is  we're starting to look at  running sort of what I consider  the key piece, as someone with a  public health interest. 

 What happens if you start  analyzing the aggregated data.  The cool thing is you can start  doing all these great kinds of  statistical routines to see  whether there's an event that  significantly different from  baseline occurring.  And you can look at it across  space and time.  So we're building this nice heat  map platform where we can  actually see clusters and sort  of unexpected concentrations of  asthma occurring in the  community by aggregating data  from everyone using the device  or the mobile phone diary out in  the field.  Granted, we don't have enough  people to make it statistically  meaningful at this point.  We're really just show you what  can be done.  So I'm really intrigued by the  Lancet kind of keeps pushing, I  think, asthma epidemiology and  clinical research along, and  their latest editorials said we  need personalized treatment and  computer-based algorithms and  really focus monitoring at the  individual to make any progress  against asthma.  So that's kind of what gave me  the drive to build what I've  been working on.  So at a public health level  really hoping to provide a new  data stream for public health  studies.  It gives you information about  the burden of the disease; who's  having symptoms; where are they  having symptoms in realtime. 

 Hopefully then we can do a  better job of targeting and  evaluating public health  interventions.  Rather than just focusing on,  hey, you need to clean up your  home.  Maybe the bulk of things aren't  occurring in the home and we  need to focus our attention  elsewhere.  Or maybe they are in the home;  until now we just assumed that.  And then hopefully we'll  identify epidemiological  patterns and risk factors that  we haven't paid attention to  before because of our  assumptions, because we haven't  been collecting as much data  about asthma epidemiology as we  could.  And then we can do something  about the sort of endless  morbidity and mortality that  keeps me up at night.  As two sort of recent experts in  physician epidemiologists and  asthma said established risk  factors for asthma do not  explain the global time trends  and prevalence patterns.  So I think there's a tendency to  become a little bit complacent  about thinking that we  understand sort of what's  causing asthma and really we  should keep our eyes open, I  think, and pay attention to new  ways of gathering information,  expanding our asthma  surveillance a little bit to try  to make more progress.  And lastly, I think the project  is really a success to the  extent that people have become a  little bit more willing to share  something about health, about  their own health, with other  people and to the extent that we  give up a little bit of privacy  when we do that.  Of course we anonymize  everything but being willing to  contribute something to make  public health a little bit  better rather than relying the  government to analyze emergency  room visits months after they  occur. 

 I think there's really an  interesting trend occurring sort  of in the internet and sort of  the electronic health tools  where people are realizing that  by collaborating and pitching in  a little bit of information  while protecting their own  privacy we can actually assemble  a vast amount of data that sends  us in entirely new and really  productive directions for public  health.  So I would be happy to talk more  about some really intriguing  examples of that that I see  going on in the community right  now.  That does it for my talk.  Thanks, very much, for coming  tonight.  (applause)