This is an article written by EpiRen. Since his blog has gone offline, I am republishing these articles since I find that they contain some good descriptive information. Here is “Epidemiology Night School: Descriptive Epidemiology”:
Let’s say that you have been told by several of your neighbors that they became ill after the neighborhood mixer over at the fire hall the other day. You’ve heard from enough people to make you a little worried that the food at the mixer (some of which you made yourself) may be involved. Descriptive epidemiology helps us form theories about what, if anything, is going on. What is descriptive epidemiology? Simply stated, it’s looking at the location and characteristics of the cases (and non-cases) and letting the evidence guide your decisions.
Let’s discuss descriptive epidemiology and see if something is going on in the neighborhood, all after the jump…
From that information we can take a quick look for clues. Are they all males or females? If not, what is the breakdown? What are their ages? Are they all young, old, in between? You might think that this information is trivial, but it isn’t. Suppose you’re investigating cervical cancer. Gender and age surely play a role in the distribution of the disease based on biology alone. (Very few men, if any, have uterine cervices.) I seem to remember a food outbreak where the men in the party were far more likely to be ill than the females. We would later find out that the party attendees were of an ethnic background where men and women celebrated and ate separately.
One of the classic examples of the use of “place” in a public health investigation is John Snow’s mapping of cholera cases in London . John Snow was a physician who was in London during a huge outbreak of cholera. He went from house to house, asking for the characteristics of people in the household who were ill. When he plotted the number and location of those who were ill, he came to the conclusion that one water pump was causing the great majority of cases. He removed the pump handle from the pump in question, and the number of cholera cases dropped precipitously.
Person and place gave Dr. Snow a lot of clues
Your symptoms lasted how long?
Time is also important in knowing because it may give us a clue as to what kind of exposure is going on. That part is for our section on outbreaks later in the “course,” so maybe just keep this in mind.
HOW TO GET THE DATA
We’ll discuss poor survey techniques later.
Actively going to your neighbors and asking about disease is a form of active surveillance. Waiting for them to tell you, or for someone to tell you, is a form of passive surveillance. We’ll discuss surveillance in a later “lesson,” so make a note of this too.
PRESENTING THE DATA
Totally random, I swear.
Because I used a random number generator, the distribution of ages should be a bell curve (called a “normal distribution”). That is, there will be about an equal number of people in each age group, more or less. Your results will vary. Tip: When averages and medians are about the same, as is the case here, there is a good chance that the data are normally distributed.
With regards to age, I would describe this group in the following way: “The group consisted of 157 people, ages 2 to 100, with an average age of 54 and a median age of 53.” There is a common mistake that a lot of member of the media make, and I think it has more to do with lack of time to present findings than to be malicious. They will usually say or write, “The average person is 54 years old,” or “Most people were 54 years old,” or “Middle-aged people were more likely to get the diease.” Well, no, because you have half of your group older than that, and half of your group will be younger than that. This leads us to describing gender.
He’s mostly male, 54% or so.
I could bore you to death even more by showing all the other mistakes done when presenting data gained from descriptive epidemiology. But I won’t. You’re all bright “students,” and you know how all these things can be mixed up to confuse you.
SUMMARY FOR TONIGHT
LAST BUT NOT LEAST
If your interest is epidemiology, the study of everything and anything that comes upon the people, then you’ll impress the admissions department if you have a good background in biology, mathematics, or any of the sciences that require serious research skills. The biology will come in handy when you have to understand why and how vaccines work, or why and how coffee can’t possibly cause pancreatic cancer. (The former will be discussed in our future “lesson” on clinical trials, and the latter will be discussed in our future “lesson” on confounding and bias.) The math, as you can see, will be handy with biostatistics.
Of course, there are other factors that go into getting admitted to any master’s degree program. I didn’t get admitted when I first submitted an application because my undergrad GPA was awful. I had to talk to the dean of admissions and explain to her that years had passed since I was “just a kid” in college, that I was incredibly interested in understanding how and why things like outbreaks happen, and that my background in the lab would boost my critical thinking skills (not to mention biology). I had to take some courses under “probation,” but even those courses helped me decide that the MPH was the degree for me before diving in completely. I suggest the same… Taking a couple of courses to see if being an epidemiologist (or an MPH in other disciplines) is your cup of tea.
Thank you for your time.