Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

Frequency Measures Used in Epidemiology

No description
by

Katrina Dielman

on 18 May 2016

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of Frequency Measures Used in Epidemiology

Estimating Risk:
Is there an Association?

Not everything that can be counted counts,
and not everything that counts can be counted.
—William Bruce Cameron, 1963

Frequency Measures Used in Epidemiology
NRS 411 - Epidemiology
CDC. (2006). Applied epidemiology for public health nurses. Module 2: Frequency measures used in epidemiology. From
Principles of epidemiology: An introduction to applied epidemiology and biostatistics
(2nd ed.).
Gordis, L. (2014).
Epidemiology
(5th ed.). St. Louis, MO: Elsevier Saunders.
Powell, T. (2008).
Confidence intervals.
Retreived from http://www.in.gov/isdh/24228.htm
Powell, T. (2008).
The p-value.
Retrieved from http://www.in.gov/isdh/24207.htm
References
Measures
of Morbidity

http://www.oregonlive.com/education/index.ssf/2016/04/norovirus_outbreak_confirmed_o.html
Using
rates
and
proportions
to express
the extent of morbidity resulting from a disease
Incidence rate
- New cases/population at risk~time period
Attack rate
- Sick exposed folks/Well exposed folks
Prevalence
- Affected folks/Total population~spot in time
Identify New Cases to Calculate Incidence
1. Spot in time
2. Period of time
Point & Period Prevalence
and
Cumulative Incidence
Interview Question

“Do you currently have asthma?”
“Have you had asthma during the last [n] years?"
“Have you ever had asthma?”
Type of Measure

Point prevalence
Period prevalence
Cumulative incidence
What is the numerator for
incidence
in 2012?
What is the numerator for
point prevalence
in 2012?
May
July
September
November
Relationship Between Incidence & Prevalence
Prevalence in the population
Increased incidence = increased prevalence
Decreased prevalence from death or cure
Trends in Data
&
Quality of Data
Trends in prevalence of obesity, by state, United States, 1990, 1995, 2000, 2005, and 2010,
based on self-reported height and weight
. Obesity was defined by BMI (body mass index) ≥30, or ~30 lbs overweight for a 5′4″ person. (Adapted from Centers for Disease Control and Prevention, based in part on data from the Behavioral Risk Factor Surveillance System.)
Measures
of Mortality

Expressing mortality in quantitative terms:
Can pinpoint
differences in the risk of dying
from a disease between people in different geographic areas and subgroups in the population
Can serve as measures of
disease severity
Can help determine whether
treatment
for a disease has become more effective over time
May serve as
surrogate for incidence rate
when the disease being studied is a severe and lethal one -
but not if the disease is mild and non-fatal
Mortality Rate
vs
Proportion
Proportion
of deaths
from heart disease
Rate
of deaths from
heart disease and cancer
3 Basic Study Designs in Epidemiology
Randomized clinical trial
Cohort study
Case-control study
Relative Risk
Relative risk
=
Risk in the exposed
Risk in the nonexposed
=
Incidence in the exposed
Incidence in the nonexposed
Negative association or a protective effect
Positive association, may be causal
Odds Ratio
(Relative Odds)

- The ratio of
the odds that the disease will develop in an
exposed person

to the odds it will develop in a
nonexposed person
Cohort Study
Case-Control Study
Odds ratio in both a cohort and a case-control study
The
odds ratio
is also known as the
cross-products ratio
, because it can be obtained by multiplying both diagonal cells in a 2 × 2 table and then dividing ad/bc:
Confidence Intervals
p-Value
When testing a hypothesis, the
p-Value
helps determine the significance of your results/validity of your claim/strength of the evidence
Your statement about what is currently believed about a population is the
"null hypothesis"
Versus the
"alternative hypothesis"
if the null hypothesis is untrue
This is your proposed hypothesis, or that which you wish to test
The p-value is a number between 0-1 comparing your
observed findings
to your
expected findings
, and lets you determine if there is a significant correlation
Interpreting the p-value:
A
small p-value (< 0.05
or 5%
)
is statistically significant (not likely attributable to chance), so you
reject the null hypothesis
Successfully shown a possible correlation related to your alternate hypothesis
A
large p-value (> 0.05)
indicates the events occur more commonly and are considered insignificant, so you
fail to reject the null hypothesis
p-Values very close to the cutoff (0.05) are considered to be marginal (could go either way)

All who drink of this treatment recover in a short time,
Except those whom it does not help, who all die,
It is obvious, therefore, that it fails only in incurable cases.


—Galen1 (129–c. 199 ce)
The Importance
of
Randomized Trials
and
Case Controls

One day when I was a junior medical student, a very important Boston surgeon visited the school and delivered a great treatise on a large number of patients who had undergone successful operations for vascular reconstruction. At the end of the lecture, a young student at the back of the room timidly asked, “Do you have any controls?” Well, the great surgeon drew himself up to his full height, hit the desk, and said, “Do you mean did I not operate on half of the patients?” The hall grew very quiet then. The voice at the back of the room very hesitantly replied, “Yes, that’s what I had in mind.” Then the visitor’s fist really came down as he thundered, “Of course not. That would have doomed half of them to their death.” God, it was quiet then, and one could scarcely hear the small voice ask, “Which half?” - E. Peacock
Studies Without Comparison
"Results can always be improved by the omission of controls."
- Professor Hugo Muensch's Second Law,
Harvard University
Experimental
Study
Observational
Study
Comparison
is an essential component of epidemiologic investigation and is well exemplified by the case-control study design
Calculating Relative Risk
Example - The Framingham (Cohort) Study
Only the
odds ratio
can be calculated as a measure of association; but we can estimate the relative risk in a case-control study from the odds ratio
Either the
relative risk
or the
odds ratio
is a valid measure of association
CDC Case Study -

Norovirus in Vermont

Interpreting the Odds Ratio
It is the same as interpretation of the relative risk:

If the exposure is
not related
to the disease
The odds ratio will be
= 1

If the exposure is
positively related
to the disease
The odds ratio will be
> 1

If the exposure is
negatively related
to the disease
The odds ratio will be
< 1
Full transcript