public health midterm lec 5

Cohort study

• large numbers of people are questioned concerning their exposures

• all subjects are “healthy” at the time the study begins 

Case-control study

• start with People who are already ill and look back to determine their exposures 

Problems and limits of Epidemiology 

ultimate goal of many epidemiological studies is to determine the causes of disease

• first Observe a possible association between an exposure and an illness,

• Second: Develop a hypothesis about a cause and effect relationship

Random error

• when a value of the sample measurement diverges from the true population value, due to chance alone

Three main sources of random error

1. Individual biological variation

2. Sampling error 

3. Measurement error

Systematic error

• sampling error is caused by the fact that a small sample is not representative of all the population variables 

What is meant by bias?

any systematic error in the design, conduct or analysis of a study that results in a mistaken estimate of an exposure’s effect on the risk of disease.

Selection bias

individuals or groups in a study differ systematically from the population of interest leading to a systematic error in an association or outcome.

Ex. Only sampling males from Ontario when the question is the average height of everyone in Ontario 

Measurement (information bias)

the individual measurements or classifications of disease or exposure are inaccurate Ex. Measurements do not measure correctly what they are supposed to measure

confounding bias

the distortion of the association between an exposure and health outcome by an extraneous, third variable called a confounder

• can cause over or under estimate of exposure and health outcome

When is a third variable a confounder

in a study of whether factor A is a cause of disease B, we say that a third factor X is a confounder if the following is true:

1. Factor x is a known risk factor for disease b 

2. Factor x is associated with factor A, but is not a result of factor

Hill’s Causal criteria 

1. Strength of association (effect size)

2. Consistency of data (reproducibility)

3. Specificity

4. Temporality

5. Dose-response (biological gradient)

6. Biological plausibility

7. Coherence

8. Experimental evidence

9. Analogy

1. Strength of association

• Between the exposure of interest and outcome is most commonly measured via risk ratios, rate ratios, or odds ratios 

Consistency of data

• refers to the reproducibility of results in various populations and situations 

Temporarity

if smoking causes lung cancer then the smoking needs to come first

Experimental Evidence 

• These types of studies can support causality by demonstrating that "altering the cause alters the effect".

Other considerations 

critically important to have a thorough understanding of the literature to determine if any other plausible explanations have been considered and tested previously.

Background

• public health workers monitor the health of a community by collecting and analyzing health data

Surveillance

• systematic collection, analysis and timely dissemination of information in population health to those who need to know so that action can be taken.

Roles of Clinicians in surveillance 

primary care physicians are typically the ones who see the initial cases in what may become an epidemic

Passive surveillance 

• The “passive” in passive surveillance refers to the role of the surveillance agency: they wait for reports to come to them.

Hospital and billing data for passive surveillance

• hospital discharge summaries can provide useful info on patterns of disease and on the therapies being used 

Vital statistics 

Births and deaths are the most basic, reliable, and complete data collected. 

● Birth certificates contain information supplied by the mother about the child’s 

Death certificates 

• information on death certificates is subject to a 

number of uncertainties, depending on how well the 

informant knew the deceased and the circumstances of 

death.

Active surveillance 

• Active surveillance means that those responsible for 

it play an active role in collecting data 

Census data 

• data collected through the vital statistics system and other methods must be converted into rates or proportions if they are to be useful for many public health purposes.

Census in Canada

• The first national Canadian decennial census was carried out in 1871 and there has been a census every 10 years since then, in the years ending in 1.

Sentinel surveillance 

• When clinicians are keeping watch for potential diseases of interest 

• Useful for rare diseases 

Health surveys

• surveys, such as the Canadian community health survey (CCHS) and the national census can also be viewed as active surveillance 

Data accuracy 

process of data collection is always imperfect

PII - personal identifiable information 

• any representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.

PHI - personal health information

• Personal information includes oral or written information about the individual 

surveillance data - Epidemic curves

• spoof resulting epidemic curve can suggest the nature of the disease and its modes of transportation 

Surveillance data - Source outbreak 

• in common source outbreak people are exposed to single noxious influence 

Surveillance data - Continuous source

• exposure to a common source can be prolonged, as with contamination water supply  

Propagated spread

• Begins like infection, secondary cases of disease act as sources to infect new people