what's def on the test

don’t need to write out the def of epi

• studying pop not people

• studying determinants

• natural only

• observational

descriptive epidemiology: who, where, when

analytic: how and why/cause

endemic, epidemic, pandemic

• need to know some of the diseases we’ve talked about in class and categorize what those diseases fall under

matching question with description of covid, ebola, zika, influenza, cholora, scrotal cancer, plague, smallpox,

difference between pop and sample

• what is sampling frame - group of people you take the sample from, set of units where you draw the sample, like a list

sampling vs coverage bias

• sample isn’t representative

• coverage is when the sampling frame doesn’t include members representative of the population (like only choosing a sample from the DMV)

types of random sampling

• simple random sampling

• stratified random sampling - divided into groups to get a representative sample like males vs females

non random sampling

• convenience - easy sample like a class

• systematic - an interval, choosing a person off of a list

• snow ball - MLM but for sampling, passing a study to someone you know

• cluster - breaking the sample down into groups but taking a group or two whole groups as your sample but doing nothing with the rest

qualitative and quantitative

discrete and continuous

• continuous can be on a spectrum like weight or height

• discrete variables are whole numbers or are a category like where you live

Stevens measurement scale - need to know which is which in multiple choice

• nominal - categorical data, non ordered categories

• ordinal - categorical data, can be ordered categories

• ratio - continuous data with a true zero point like kelvin or how many children you have

• interval - continuous data with no true data

bivariate association

• linear

• inverse

• no association

• nonlinear

• dose response curve

how would you write a proportion, percent, ratio, rate - how to write them

• proportion: part over whole

• percent - part over whole multiplied by 100.

• ratio - x/y

• rate - x/time elapsed

count vs incidence, prevelance,

• count - raw number

• incidence - new cases

• prevelance - existing cases

what factors might increase or decrease prevelance

• deaths of a disease will decrease

• immigration/migration increasease

• improved healthcare can decrease

• better reporting increase

• new cure decrease

big data - vast electronic storehouses of information

• 4 Vs - volume, velocity,

decennial survey

• every 10 years by census

other reliable sources for information

• cdc, cencuc, nih, who

notifiable and reportable diseases

• diseases required to be required to report to the government

vaguely need to know data mining, data usage, data linkage

4 vital life events

• deaths

• births

• marriages/divorces

• not all death and birth data might be reliable or standardized, different criteria, inconsistent practices, some dr might want to report on a death more vavorably, death or birth at death isn’t necessarily a huge problem

who maintains the registries - the states

deterministic and probabilitic causality

• deterministic - nec and suf, not nec not suf, nec not suf, nec not suf

  • suffiecient componant pie model

• probabalitic (don’t rlly need to know) - if you have a greater expsure ur more likely to get the diease

types of association - be able to indentify them in a fact pattern

• no association vs association

  • association can be non causal and causal

    • causal can be direct or indirect

person and place variables

• sex, age, where born, where live, race, urban rural,

time variables - need to be able to point out which is which

• secular,

• cyclic,

• cluser, clustering of same disease in roughly same time and place due to same factor

• point - exposed at that one specific point in time and place

case reports, case series, cross sectional

• case report is individual or a handful

• case series are several dozen or hundered

• cross sectional relationship between disease and certain variables where a pattern has been dectected

miasma

• theory of the bad air causing illness bleieved in middle ages

• associated with john snow sorta and chollera

epidemiologic triangle

• host

• agent

• environmrnt

• vector

null hypothesis

• no association between the 2 variables

• reject the null

• fail to reject the null

know measurments of central tendency

• check midrange

most of the math questions are multiple choice

there will be a few fill in the blanks like for a specific birth rate

put the multiplyier in both the numerical and sentence answer

point prevelance - period prevelance

double check on infant mortality, fetal mortality, late fetal death, perinatal death rates