Lectures

Measurements of Morbidity – Descriptive Epidemiology

by Raywat Deonandan, PhD
(1)

Questions about the lecture
My Notes
  • Required.
Save Cancel
    Learning Material 2
    • PDF
      Slides 09 DescriptiveEpidemiology Epidemiology.pdf
    • PDF
      Download Lecture Overview
    Report mistake
    Transcript

    00:00 One of the first concepts I want to talk about though is rates versus ratios and commonly we conflate these two ideas, that's okay that we do, but I want you to get straight in your mind that they are distinct ideas. A rate is a measure of the frequency of something divided by some measurement of time. For example, a car moving along a highway moves at a rate of speed which is measured as a function of time. A ratio on the other hand, is what we get when we divide one quantity by another; we're getting a pure number. Sometimes expressed as a percentage, sometimes as a fraction.

    00:36 So let's talk about incidence. Incidence is the number of new instances of a disease in a fixed period of time expressed as a proportion of people at risk. It's a genuine rate, because we express it as a function of time, time is an important characteristic here.

    00:53 There are two kinds of incidence measurements, the first is incidence density. Incidence density is characterized by an appreciation that everyone in our population may not be exposed to the disease at the same amount of time, so people are at risk for different amounts of time.

    01:12 In cumulative incidence however, we're assuming that everyone's at risk at the same amount of time. Usually incidence density is done in clinical populations, we compute it for small numbers of people who are being observed in the clinical context and cumulative incidence typically, we use it for large populations like cities or towns, though not exclusively.

    01:34 Whereas prevalence which is our other measure of morbidity is again, the number of people who have the disease at a particular point in time expressed as a proportion of the total population. It's a ratio. It doesn't necessarily have a function of time involved.

    01:46 There are two kinds of prevalence as well. The first is point prevalence. This is when we care about the number of people that have the disease right now or at a particular date or time, whereas period prevalence is a number of people who have the disease or proportion that have the disease over a particular period of time. Now let's talk about incidence density some more. It's expressed as again a fraction, the numerator is the number of new cases and the denominator is the population at risk multiplied by duration of time that we care about. However the important consideration with incidence density is that we're expressing it as a rate per population time. What can be a confusing concept, sometimes it's man hours, woman years, population weeks, whatever it might be, but there has to be a consideration of population and time as a unit in the denominator. Let's do an example. Consider that you have a population of six clinical patients, A, B, C, D, E and F and you're examining these patients to see if disease X manifests incidentally, you're going to observe them for about eight years, again in their clinical context. Now patient A develops disease X on the second year and dies on the seventh year. Patient B disappears on the second year, maybe they get bored and move away. Patient C develops the disease on the third year and then disappears on the fifth year, we don't know if patient C died or went away or survived. Patient D we observe for seven years and again disappears. Patient E, we observe for two years but we don't know what happens after that and patient F we observe for six years. So again we have different patients being observed for different lengths of time, only two of them develop the disease and one of them died, so the incidence of the disease, we know the numerator is going to be two, because two of them developed the disease. Now let's compute the incidence density.

    03:45 To do so we have to consider how long each individual was observed. So for patients A, B, and E, we observed them a total of two years each, now patient A at the two year mark, developed the disease, so after that no longer count, we only care about those who are at risk. So after patient A developed the disease, here she is no longer at risk, so again patient A was observed for two years, patient B for two years, patient E for two years, patient C for three years and so forth. We add up all those years at risk and that gives us our denominator. So we had two incidence cases over 22 years total at risk, so our incidence density is 2 divided by 22 or 0.09 cases per person year. If we wanted to express that as a rate per a hundred person-years, I just multiply my number by a hundred, 0.09×100 gives me nine cases per 100 person-years, it's straightforward like that. Cumulative incidence rate on the other hand, doesn't involve computing different exposure times per population at risk. It's simply the number of new cases divided by the total population at risk over a time period that we've defined. Let's say we have 50 new cases in a population of a thousand people in one year, then my cumulative incidence rate is quite straightforward, it's just 50/1000, so 50 cases per 1000 person-years over one year. Let's try a different example.

    05:17 Cityville has 1000 people, over a two-year period, 28 people in Cityville developed disease X, so what's the incidence of disease X in Cityville over this period? Well our numerator is 28, our denominator is 1000, that's over two years, so we divide 28 x 2 times a thousand and we get 14 cases per 1000 persons per year or 1000 person year, it's the same thing.


    About the Lecture

    The lecture Measurements of Morbidity – Descriptive Epidemiology by Raywat Deonandan, PhD is from the course Descriptive Epidemiology.


    Included Quiz Questions

    1. 5 cases per 100 people per year
    2. 200 cases per 1000 people per year
    3. 150 cases per 1000 people a year
    1. 200/1000 or 20%
    2. 150/1000 or 15%
    3. 50/1000 or 5%
    1. The study population is experiencing a higher than expected death rate or excess morbidity/mortality
    2. Reduced morbidity/mortality
    3. The study population is experiencing a lower than expected death rate
    4. No change in morbidity/mortality rate
    5. Death rate has reduced from past year
    1. 5.49 x 10-4
    2. 6.49 x 10-4
    3. 2.49 x 10-4
    4. 3.49 x 10-4
    5. 4.49 x 10-4

    Author of lecture Measurements of Morbidity – Descriptive Epidemiology

     Raywat Deonandan, PhD

    Raywat Deonandan, PhD


    Customer reviews

    (1)
    5,0 of 5 stars
    5 Stars
    5
    4 Stars
    0
    3 Stars
    0
    2 Stars
    0
    1  Star
    0