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Epidemiology

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study of the DISTRIBUTION and DETERMINANTS of health-related states or events in SPECIFIED POPULATIONS and the application of this study to the control of health problems

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Epidemiology's goal

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is prevention.

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Epidemiology is a_____________science.

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population-based

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Five objectives of Epidemiology

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1. Identify etiology (causes) of disease and relevant risk factors 2. Determine the burden (extent) of the disease in the community 3. Study natural history of disease and prognosis of disease 4. Evaluate existing and new preventive and therapeutic measures and modes of healthcare delivery 5. Provide the foundation for developing public policy related to disease prevention and health promotion

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Epidemiology differs from clinical medicine. How?

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Epidemiology informs the clinical practice of medicine Example: Diagnosis and prognosis are based on population data. • Preventive medicine -We are concerned with how we can prevent disease from occurring, not curing it once it has occurred • Population science - Our unit of study are groups of people, not individuals -We advocate for the allocation of effort ; resources at the community level

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Epidemiology informs medicine

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Example: Prognosis A patient asks a doctor, "How long do I have to live?'' The doctor usually answers on the basis of : Experience with large groups of patients who had the same disease were observed at the same stage of disease received the same treatment

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Three types of prevention and examples of each PRIMARY SECONDARY TERTIARY

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1. Primary: Preventing the initial development of a disease; eg., immunization 2. Secondary: Early detection of existing disease to reduce severity and complications; eg., cancer screening 3. Tertiary: Reducing the impact of disease; eg., rehabilitation

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Successes in Epidemiology, examples

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1. Sanitation 2. Vaccination 3. Water quality 4. Disease screening 5. Health promotion/disease prevention campaigns

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Epidemiology utilizes both _______ and ________ approaches for study

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descriptive AND analytical

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Descriptive Epidemiology

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Characterizes disease in populations - Who? When? Where?

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Analytical Epidemiology:

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is there an association between risk factor and disease?

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Diseases result from an interaction of the Epidemiologic Triad HOST AGENT ENVIRONMENT

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1. Host: The organism harboring the disease 2. Agent: The microbe that causes disease 3. Environment: The external factors that allow transmission

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Vector

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Person, animal or microorganism that carries and transmits the infectious pathogen

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Factors that may be associated with an increased/decreased risk of human disease (examples of each)

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1. Host characteristics 2. Agents 3. Environmental factors

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Natural history of disease, Stages, severity of disease A. Pre-Clinical vs. Clinical PRECLINICAL? SUBCLINICAL ? PERSISTENT? LATENT?

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Clinical vs. Nonclinical Disease • Clinical Disease - Characterized by signs and symptoms • Nonclinical Disease (i.e., not apparent) - Preclinical: not apparent but will progress - Subclinical: not apparent and won't progress - Persistent, i.e., chronic: a person filos to "shake-off" the infection, and it persist for years, at times for life. - Latent: silent, not active; an infection with no active multiplication of the agent, as the viral nucleic acid is incorporated into the nucleus of a cell as a provirus. 1. Biological onset 2. Detectable by screening 3. Symptom onset 4. Seek medical care, diagnosis 5. Treatment 6. Outcome: cure, death Stages, severity of disease: VIEW SLIDE PICTURE BELOW

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Disease carrier - Carrier Status

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an individual who harbors the infectious organism but does not have any evidence of clinical illness. the person can still infect other people.

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Disease transmission

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Direct: Person-to-person contact • Indirect - occurs through Common vehicle such as contaminated air or water supply, or a vector (1) Single exposure (2) Multiple exposures (3) Continuous exposure (4) Vector

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Incubation period

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The interval from receipt of infection to the time of onset of clinical illness

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Endemic

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he habitual or "background" presence of disease that is normal for a given geographic area

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Epidemic:

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the occurrence of a disease at a level that is higher than normal background or expected for a specific community or geographic area

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Pandemic:

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an epidemic that spans more than one country

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Herd immunity

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the resistance of a group of people to a disease to which a large proportion of the members of the group are immune - Basis likelihood of encountering susceptible or infected person - eg. measles ~94% immune/vaccinated before herd immunity of population

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Disease outbreaks

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an occurrence of disease greater than would otherwise be expected at a particular time and place, Types (for example): 1. Foodborne 2. Waterborne 3. Healthcare facility What is an outbreak? - an occurrence of disease greater than would otherwise be expected at a particular time and place - Could be small and localized or widespread and impact thousands of people - Could be two epidemiologically linked cases of a rare disease

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"Epi curve"

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Common-vehicle, single exposure a graphical presentation of number of cases over time

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Attack rate

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= Number of people at risk in who get ill/ Total number of people at risk

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Common measures of disease

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1. Proportions: the fraction of the population that is affected by disease, death 2. Rates: how fast disease, death is occurring in the population

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Morbidity measures

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incidence rate and prevalence rate

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Incidence rate

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i. The number of new cases of a disease that occur during a specified period of time in a population at risk for developing the disease ii. calculation of - numerator and denominator (persons, person-time) iii. measure of disease risk

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incidence rate

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• Choice of multiplier is arbitrary (1,000, 10,000, 100,000) • NEW onset cases (assumed population at risk is comprised of persons who did not have the disease previously) • Serves as a measure of risk • Can be calculated in any group, subgroup, population, subpopulation • Denominator must contain only those who have the potential to become part of the numerator (eg., cervical cancer & men) • Units of denominator consist of - persons (when followed for entire period) ("cumulative incidence") or - person-time (when followed for portion of time period)

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person-years

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number of new cases during a specified period of time ________________________________________ total person time X1000

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Prevalence rate

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i. The number of existing cases a disease in the population at a specific time divided by the number of persons in the population at that time ii. calculation of iii. measure of disease burden iv. point and period prevalence v. survival is an important factor c. Interrelationship between incidence and prevalence d. Disease surveillance is used to identify/count incident cases

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Point prevalence

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- Prevalence of disease at a certain point in time - "Do you currently have x disease?"

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• Period prevalence

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- Prevalence of disease during a certain time period - "Have you had x disease during the last # years?"

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Mortality (death) rate

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i. Number of deaths overall/due to a certain cause/disease that occur during a specified time divided by the number in the population (midyear) ii. calculation of iii. all-cause, cause-specific

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Case-fatality rate (percent)

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Percentage of people with a specific disease who die from the disease

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Proportionate mortality (proportion)

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Proportion of all deaths due to a specific cause

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Years of potential life lost

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Measure of premature mortality (early death)

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Age-adjustment

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age-adjusted rates: age is arguably the most important known factor related to death; when comparing rates of disease, mortality in populations it is important to adjust for age is it important know indirect and direct age adjustments?

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Problems with mortality data

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• DC coded for underlying cause of death, not multiple cause/contributing cause • Reflect medical opinion • Varying quality, completeness • Changes in ICD coding • Changes in definition of disease • Not published promptly, multi-year delay

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Measuring Prognosis (survival): standardized from time of diagnosis

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1. Case-fatality rate - Best for short-term, acute conditions 2. Five-year survival rate - percentage of patients alive 5 years after diagnosis or treatment 3. Median survival time 4. Observed survival (life table) approach 5. Kaplan-Meier method Did not go over 4 and 5

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Lead time:

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made earlier because of screening for disease artificially lengthens survival time

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Screening test

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1. Laboratory tests that help to identify people at increased risk for a condition or disease before they have symptoms 2. Help detect disease in its earliest and most treatable stages 3. Contrast with a diagnostic test which confirms a diagnosis in person who already has signs/symptoms of a disease 4. Oftentimes, continuous test value must be dichotomized into positive/negative, yes/no result for interpretation

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Validity

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ability of a test to distinguish between who has a disease and who does not includes: sensitivity and specificity

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Sensitivity

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i. level at which test correctly identifies those who have the disease ii. calculation of iii. interpretation of

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Specificity

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i. level at which test correctly identifies those who do not have the disease ii. calculation of iii. interpretation of

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example of screening

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```

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Predictive Value (precision) -

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probability the patient has/does not have the disease if he/she tests positive/negative

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Positive Predictive Value (PPV)

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i. the proportion of patients who test positive that actually have the disease (eg., correct diagnosis) ii. calculation of iii. interpretation of

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Negative Predictive Value (NPV)

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i. the proportion of patients who test negative that don't actually have the disease ii. calculation of Interpretation: • Of the individuals testing positive by this test, 44% will be correctly diagnosed as having cancer • Of the individuals testing negative by this test, 98% will be correctly diagnosed as not having cancer

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Reliability (reproduceability)

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a. Intra-subject (within the same subject) b. Intra-observer (within the same observer) c. Inter-observer (between observers)

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Experimental

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The researcher intervenes to change conditions, then observes what happens a. Randomized Trials

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Observational

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The researcher studies/observes but does not intervene a. Case-Control b. Cohort

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