Each year when students and staff return from summer vacation, the year's new versions of colds and the flu are introduced and reintroduced into the school population. Many of us may enjoy the novelty of visits to exciting and sometimes far off exotic places or come into contact with those who have. Inconspicuously, along with our friends and associates we are confronted with new viruses, ones that are not recognizable to our immune system's memory.

Early in the Fall, windows remain open and ventilation is adequate enough to reduce airborne transmission yet, it is difficult to avoid sipping a drink, touching a doorknob or touching a pen or calculator that has come into direct contact with someone harboring a virus. Perhaps they do not even show the slightest symptoms of infection. As the season changes and the air begins to chill, windows are kept closed and the dusty building becomes a breeding vessel for viruses, bacteria, fungus and other infectious agents. The spread of infection quickens. The effects of transmission are compounded as our immune systems begin to bare the stress of too little sleep, light deprivation, the burden of grades, expectations and increasing demands on our time. By December as much as 70% of the school population may have been exposed and suffered the effects of the season's first cold epidemic, Later we will continue to see periodic eruptions of infection and of course, the flu. Relatively few individuals will have escaped the fate of at least one illness.


The above account is anecdotal yet, most would agree that it bares some resemblance to what occurs year after year in our school. The variables suggested above are plausible and raise interesting questions about what is really happening and why. Can we identify any cause and effect here? How can we collect enough data to adequately tell the story? Who can we consult that may help us to become competent researchers? How can it be assured that our data and conclusions are trustworthy or at least reasonable?

To begin we must collect some data that will help us to see clearly what is going on and to think far enough in advance about correlation and possible causation to ask the right questions and pay attention to important details while the window of opportunity is still open. It is also important to consider how much data must be collected to be able make valid generalizations later. What are the best methodologies that will enable us to acquire the kind of data that we will need to figure out just what is going on here?

Please explore our website as we attempt to gather answers to these and other questions.