The number of people diagnosed with Legionnaires disease has risen to 108 as America’s largest city suffers from a record outbreak of the form of pneumonia, authorities said Saturday. No new deaths have been reported on top of the 10 announced earlier in the week and officials say the outbreak is now on the decline. To date, 94 people have been admitted to the hospital with the infection since the outbreak began on July 10 in the south Bronx, the poorest section of New York state.
Sourced through Scoop.it from: news.yahoo.com
Working in the heart of New York City right now, some thoughts about the nature of what is happening with Legionnaires makes me wonder how the press and people are going to deal with this.
It is worth mentioning that I am perhaps two steps shy of feeling much concern for my developing this disease. First and foremost, I use my "sense" of health and especially immune health (mostly subjective assumptions) to keep these concerns at a minimum. Legionnaire’s erupted in my medical school during my first year there, in 1982; I did not catch it then why might I catch it now? May I add, this reasoning is identical to what I used to perform my field surveillance work around known houses with cases of West Nile inside; the purpose of being there was to map out the ecology of that setting and evaluate the species of vectors and determine if they were carriers. The second reason I had was even more pinpoint–all of the cases I investigated then involved people who were much older than me . . . and therefore textbook cases.
Everyday, I take a train past on of the hot spots for the most recent New York City Legionnaires outbreak, and may have even traveled to one or two of these sites as part of my work.
But seeing the big picture of what’s happening in the immediate one to two block area, around a potential outbreak nidus, and seeing how many people travel those streets and enter those buildings each and every hour, I find it amazing to think that anyone could actually design a model to accurate predict the diffusion activity down to the small area spatial level. That’s what makes spatial epidemiology as exciting as it is and formula writing the big brainteaser that it is.
Taking a break at lunch, I counted about ten thousand people coming in and leaving a less than one block area in lower Manhattan per hour. Therefore, it makes sense to guess that this is a place where an infectious disease could very easily come in.
But exactly where the infectious person goes once he lands on Water Street is a different story. He or she could head to a hospital in the Bronx by taxi or subway, the many local tourist sites, the 911 monument, to times square, or to a small clinic north of Harlem by bus or company transit because that is where he or she works. How and where a disease will actually diffuse away from the Old Slip is anyone’s guess.
What’s also important here is to realize that is how Valentine Seaman thought when he was trying to map yellow fever out in 1799 or 1800, following its repeated return in early October. Seaman thought his disease had to be either locally airborne or came in by crew and passenger and/or by rotten foodstuffs and stinky ballast water.
So, based upon Seaman’s observations, applying this same logic to Legionnaire’s makes no sense–or does it?
The large air conditioning facility is the suspected culprit in this case–aerosolized water particles being spread about a facility. But how can such an event commence almost simultaneously in multiple facilities? Is there another commonality to these places and their people, be it environmentally or ecologically (human ecology that is)?
Once again, that question has to be asked by modern New York epidemiologists–is the disease being spread by people or air-water effects. The locations point to people. The pattern suggests an aerosol nature. The nature of the facilities point to the role or human transportation in all of this.
Relating all of this back to GIS–with GIS, we cannot make as accurate prediction for the cause and spread of Legionnaire’s as we would like. We would have a hard time predicting this outbreak, had we the foresight to think about looking this up months ago. But once it is there, we have a place to begin our spatial prediction modelling routine.
Fortunately, we can develop a very accurate model on how a disease can behave once it has erupted, and in retrospect why it is where it is.