Epidemiology

Epidemiology 12

  • The study of the distribution and determinants of a disease frequency in human populations



epidemic/outbreak

  • The occurrence of a disease in members of a defined population

  • More than the normal amount of cases in a population



Pandemic

  • Throughout the population of a country, people, or world



Epidemiologic methods purpose

  • Measure how common health problems are.

  • Find out what causes diseases.

  • Help decide how to best use public health resources.

  • Check if prevention strategies are working through ongoing monitoring.




History of epidemiology 

  • 5th century B.C Hippocrates 

    • suggested that the development of human disease may be related to the external and personal environment of individual

  • 1662 John Graunt 

    • analyzed weekly reports of births and deaths

    • First to quantify patterns of disease

    • # of men that were born/died

    • High infant mortality rate

    • Seasonal variations (more die in winter)

  • William farr 1839

    • System of routine complication of numbers and causes of death 

    • Compared mortality rates with several different characteristics

  • John snow (2 decades later) used williams data

    • Formulated and tested hypothesis’ concerning origin of cholera epidemic

      • Cholera: bacterial infection of the small intestine

      • Symptoms - severe diarrhoea and vomiting, muscle cramps, dehydration, and depletion of electrolytes

    • Suggested it came from contaminated water

    • Charted frequency and distribution of water

    • Found out cause of cholera



Components of epidemiology principles and methods 

Distribution: where, when who

  • Comparisons between different populations at a given time, or between subgroups, or different periods of observation

  • Describes disease patterns

  • Formulates hypotheses to cause and preventative factors



Disease frequency 

  • Quantification of occurrence of disease in human population 



Determinants of disease 

  • Distribution and disease frequency

  • Necessary to test epidemiologic hypotheses



Hypothesis

  • A statement derived from a theory that predicts the relationship among variables representing concepts, constructs, or events

  • What researcher expects to find



Key assumption of epidemiology

  • Majority of human disease doesn't occur at random

  • Casual and preventative factors of human disease can be identified through different populations or subgroups



Primary units of concern

  • Interested in groups of people - not individuals 

  • Groups must be studied to find the cause and prevention of a disease



Key concepts of epidemiology 

  • Quantitative science 



Count

  • # of people studied who have particular disease

    • Ex. 40 of 90 KP290 students have asthma



Ratio 

  • Relationship between 2 numbers

    • Ex. 100 males : 150 females



Proportion 

  • Special type of ratio

  • The numerator is part of the denominator and the resulting proportion is expressed as a percentage

    • Ex. 100 (males) / 250 (females + males) x100%



Rate 

  • Certain kind of proportion 

  • Frequency of how much an event occurs over a certain time



Prevalence rate (point prevalence rate)

  • Can only exist at one point in time

  • # of preexisting cases of a condition within a specific population and time per 100 of population at risk

  • Denominator includes everyone

  • = # of cases (specified time)/ population (everyone) x100

Incidence 

  • # of new cases



Incidence rate

  • # of new cases of a starting during a specific time/ population - pre existing cases x 100 = population at risk



Epidemiologic study designs

Descriptive study designs

  • Concerned with disease distribution 

  • Used for initial hypothesis about exposure disease relationships

  • Who, where, when (for hypotheses)

    • Who: what populations do not develop disease

    • Where: what location is more or least common

    • When: how does the frequency of the disease occurrence vary over time

  • Cross-sectional and ecological 



Cross-sectional design

  • Measures cause and effect at a certain point and look at relationships

  • Advantages

    • Looks at individuals rather than groups

    • Can control potentially confounding variables

  • Limitations

    • Outcome and exposure are measured at same point in time

    • Cannot make statement about cause and effect

    • Cannot examine continuous relationships



Ecological design 

  • Use existing data sources to understand the relationship between outcome and exposure at a population level



Analytic study designs 

  • Focus on disease causes by testing hypotheses, formulated from descriptive studies 

  • The goal is to determine if exposure to a certain factor prevents disease

  • Cohort studies and case-control studies



Cohort studies (prospective studies)

  • Begin with a small group of people and follow them over a period of time 

    • Amount of exposure to each will vary

  • Try to figure out cause and effect

  • Try to figure out the rate of X occurs in relation to the amount of exposure to Y

  • All cohort members have no health problems at the start of study 

  • Groups divided into 2 or more

  • Sample of cohort selected from population grouped into cases and non cases

  • Advantages

    • You know exactly the time between the exposure and outcome

    • Good for rare exposure

    • Good for understanding multiple effects of a single exposure 

  • Limitations

    • Difficult to do (large sample)

    • Costly 

    • Forget to follow up (can last years)

    • Some diseases are very rare, may be difficult to get a sufficient number of cases for analysis

  • How to select a cohort 

    • Accessibility (easy selection)

    • History of previous exposure (random sample)

    • Medical records



Case-control studies (retrospective studies)

  • Participants from a group with a disorder and compare cases without disorder

  • 1st group who already have X (aka cases)

  • 2nd group who doesn't have X (aka controls)

  • Need to determine how 2 groups differed in their exposure to Y

  • How to select cases

    • Physicians 

    • Employers

    • Healthcare providers

    • Medical records

    • Dental records

    • Subjects themselves

  • Advantages: 

    • Results can be seen in a short period of time

    • Efficient for studying rare diseases ( don't need large population or long follow up periods)

    • Enable hypothesis testing for multiple exposures for a single disease outcome

    • Can be used to get more detail about exposure

  • Limitations

    • Exposure information is obtained after disease has been diagnosed 

      • Could be recall bias

    • Can be challenging to recruit control group (can affect odds ratios)

      • Can be selection bias



Errors in data collection

  • Clinical observations (disease presence/ absence)

    • Physical examinations rounding of B.P

    • Medical history interview

  • Disease reporting

  • Clinical diagnosis

    • Different criteria for making same diagnosis

  • Death certificates + mortality statistics 

  • Medical chart review 

    • Missing info

    • Illegible 

  • Laboratory data

    • Ingestion of certain drugs affects blood constituents 

  • Responses to questionnaire 

    • Non response

    • Inconsistent response

    • Overreporting symptoms 

    • Understanding factors 



Establishing causation 

  • Temporal sequence 

    • The thing that causes disease came before disease

  • Consistency

  • Strength of association

  • Specificity of effect

  • Biological gradient 

  • Existing data and theory



Problems of error

  • Bias

    • Selection bias

    • Information bias

    • Confounding bias

  • Random variation 

    • Chance differences between groups

  • Random misclassification 

    • Subject could be in wrong group

    • Exposed person with non exposed (vice versa)



How to control errors?

  • Matching variables

  • Homogeneous grouping

  • Stratified sample (1:1 ratio)

  • Post-stratification 

    • Sample first, then strata