TAMU Epi 305 Exam 1 Mac Shaltout summer semester

Epidemic

More cases of a disease than expected

Pandemic

Epidemic that is all over the world

Endemic

A disease where a disease is consistently present in a particular region

What are the key characteristics of epidemiology?

Population focus

Quantification

Distribution

Variation in the occurrence of disease and other health outcomes in populations relates most closely to

Distribution

Which of the following is NOT descriptive epidemiology

A specific country where diseases may occur

tracking time trends of a disease

Sex, age, race/ethnicity

Seeing whether a suspected factor may be behind a certain disease

Seeing whether a suspected factor may be behind a certain disease

Distribution

Occurrence of disease and health outcomes vary in populations

Some are more affected than others

Determinant

A risk factor causally related to a disease/illness

Biological agents, chemical agents, lifestyle

3 goals of epidemiologists

Measure: Disease or some aspect of health

Identify: Causes/factors

Intervene: To improve health

Descriptive epi

Person, place, time

Analytic epi

Analyses correlation and causation between things

Hippocrates

First to argue that a non-supernatural cause for disease

Father of epi

Diseases are caused by imbalances of humours(blood, phlegm, yellow bile and black bile

Ibn al Nafis

Disease caused by humidity

Different age and sex have different factors that contribute to disease

Minor uncovered wounds pose risk of death or infection

How many people did black death kill

Claimed 1/3 of europes population

Kills 60% of its victims

What is the Black Death caused by

Bubonic plague

Bacteria called bubonic pestis

Symptoms of Black Death

Swelling of lymph nodes in groin and everywhere else in the body, fever, splotches

Paracelsus

Toxicology

Dose response relationship- more poison=more effects

Girolamo Fracastoro

Disease seeds cause each different disease

Germ theory of disease

Thomas Sydenham

Used empirical approach to medicine

Went against hippocratic approach to smallpox

John Grant

Bills of mortality- summarized diseases and casualties of each

Anton Van Leeuwenhoek

Developed sufficiently powerful microscope

First visual evidence of living particles consistent with germ theory of disease

Animalcules

Bernardino Ramazzini

Disease of workers

Occupational health/medicine

James Lind

Scurvy- lack of vitamin c

Citrus fruits

Percival Pott

First person to describe environmental cause of cancer

Chimney sweeps

Bathe once a week to lower risk

William Farr

Built on graunts work

Systematically collected and analyzed britains mortality

Reported to health authorities and public

Edward jenner

Vacccines

John snow

Argued Cholera was waterborne

Pasteur

Germ theory- Germs were living and caused disease

boiled things to kill the germs= pasteurization

Koch

Stated disease was caused by a microorganism

Postulates demonstrate assosciation between microorganism and disease

Came up with 4 postulates

Koch’s postulates

1. Organism must be observed in every case

2. Isolated and grown in pure culture

3. Must reproduce the disease in a susceptible animal

4. Observed in and recovered in the experimental animal

Florence nightingale

Hospital hygiene

Shattuck

Importance of setting up state and local boards

Jonas Salk

Made the Polio vaccine

Disease in the 1850s

Typhus and cholera

Smallpox

Virus

Fever, vomiting, sores

30% risk of death

Edward Jenner made vaccine

Polio

Viral

Muscle weakness, fecal oral route transmitted

Jonas Salk made vaccine

Epidemiological transition

Phase of development, increase population, medical advances

Leveling population, decline in fertility rate

Replacement of infectious disease by chronic disease

Population

All of the people who share a characteristic

Everyone who lives in college station

No error, true representation

Mean: mew

Sample

Some people of a population, not whole group

People who live in traditions

Margin of error and confidence interval

Mean: xbar

Probability sampling

Every member in a population has a probability of being sampled

Measure sampling error

Simple random, stratified, systematic, cluster

Simple random sampling

Everyone has same chance of being included

Stratified sampling

Population divided into non overlapping subgroups, then the same amount of people are selected from each

Systematic sampling

Numbers people and uses a certain interval to select them

Every 3 people

Cluster sampling

Clusters people into groups

Ex. State, block, county, school, grades, area code

Non probability sampling

Biased, so can’t calculate sampling error

Convenience sampling

Data

Quantitative

• Discrete- whole numbers, can’t be broken down

  • Number of people

• Continuous- numbers that can be broken down- height, weight

  • Interval- known differences between variables-time

  • Ratio- measurable increments- height

Qualitative

• nominal- naming variables- hair color

• Ordinal- describes order of values- pain on a scale of 1-10

Frequencies

Bar chart

Histogram

Line graph

Pie chart

Location of data

Mode- most occurring number

Median- numbers ordered, then # in the middle

Mean- average

Spread of data

Range

Variance

?

Distribution

Percentiles

Quartiles

Normal (Gaussian) distribution

Bell shaped curve

+-1SD= 68.3%

+-2SD= 95.5%

+-3SD=99.7%

A positively skewed graph means that the _____ is less than the ______ which is less than the _____.

Mode, Median, mean

Skewed

Negatively- bigger curve on right

Positively- Bigger curve on left

Epidemic curve

Graphs distribution of cases by time of onset

Bivariate assosciation

Relationship between two variables

Correlation, not causation

Pearson correlation coefficient

Strength of assosciation

R-: inverse relationship

R+: positive relationship

Scatterplots

Know correlation and what they look like

Dose response curve

Correlative assosciation between exposure and effect

X axis: dose

Y axis: Response

Beginning flat: low dosage, no effect

Middle rising: more dosage, increased effect

End flat: maximum effect

Contingency tables

Parameter estimation

Point estimate: single value estimates parameter- sample mean to estimate mew

Interval estimate: range of values that with a certain level of confidence contains the parameter

95% confidence level: 95% certain the confidence interval contains the parameter

Ratio

X/Y

Proportion

A/A+B

Proportion of deaths that occurred among ______/ number of male deaths+female deaths

Percentage

A/A+B x100

Why are proportions and percentages important

Tell you how important a health outcome is in comparison to the size of the group

Rate

Numerator: # of events such as health outcomes

Denominator: measure of time(delta t)

Count

number of disease or other health phenomenon being studied

Incidence

Number of new cases of an illness during a period of time

What do measures of incidence do

Measure risk of getting disease, rate at which new cases develop, health outcomes

Incidence rate

Number of new cases during a period of time/ average number of individuals at risk x multiplier

Calculate the incidence rate:

Number of new cases- 28639

Average US population- 316,128,839

9.1 per 100,000

Cumulative incidence

Incidence rate, but ALL individuals in the population are at risk

Calculate the cumulative incidence rate

CVD of 23502 male middle aged alumni of an Ivy League university

During the 1st year, 111 alums have heart attacks

111/23502= .005 (0.5%)

Incidence density

Incidence rate but when the time periods of observation of the members of a population vary from person to person

Person-time= total period of time that each individual at risk has been observed

One person-year= one subject has been observed for one year

Number of new cases during the time period/ total person-time of observation

Attack rate

Incident rate when the occurence of disease among a population at risk increases greatly over a short period of time

Ill/ Ill+ well

Calculate the attack rate

59 people ate roast beef suspected of causing a salmonella outbreak

34 people got ill

25 remained well

34/34+25 × 100

=57.6%

Prevalence

Number of existing cases of a disease or health condition, or deaths in a population at some designated time/ number of people in that population

Point prevalence

Number of people ill/total number in the group at a point in time

Period prevalence

Whether a respondent answered yes to the question/ The time period for this measure is the past year

Lifetime prevalence= cases of disease diagnosed at any time during the persons lifetime

Relationship between incidence and prevalence

Prevalence= incidence rate x duration

Factors that increase prevalence

• longer duration

• Medications help them live longer

• Increases in new cases(incidence)

• Cases migrate in

• Healthy people leave

• Susceptible people migrate in

• Diagnostic things increase

Factors that decrease prevalence

• shorter duration of disease

• High case-fatality rate from disease

• Decrease in new cases

• In migration of healthy people

• Out migration of cases

• Improved cure rate of cases

Life expectancy

Number of years that a person is expected to live at any particular year

Life expectancy at birth

Average number of years a group of infants would live if the group experienced throughout life the age-specific death rates present in the year of birth

Crude death rate

Number of deaths in a given year/ population during middle of the year

Case fatality rate

Number of deaths due to disease x/ number of cases of disease x X100 during a time period

Crude fertility rate

Proportional mortality ratio

Mortality due to a specific cause during a period of time/ mortality due to all causes during the same time period x100

Cause specific rate

Mortality(or frequency of a given disease)/ population(at midpoint) x100,000

Age specific rate

Number of deaths among people 15-24/number of people age 15-24 ×100,000

Sex specific rate

Number of deaths in a sex group/total number of people in the sex group

Adjusted rates

Remove the effect of differences in composition of the population

Age and direct

Age adjusted rate

Uses age structure for population for which the rates are being age adjusted

Direct method

Multiplying the age specific rate for each subgroup to be standardized by the number in a comparable subgroup of a standard population

Maternal mortality rate

Number of deaths assigned to causes related to childbirth/number of live births x100,000 live births

Infant mortality rate

Number of infant deaths among infants age 0-365 days/number of live births during the year x1000 live births

Fetal mortality rate

Fetal death rate: number of fetal deaths after 20 weeks or more gestation/number live births + number of fetal deaths after 20 wks or more gestation

Late fetal death rate: number of fetal deaths after 28 weeks or more gestation/live births and fetal deaths after 28 weeks