# Epidemiology - Block 3 and Final

version from 2015-07-27 03:36

## Biostatistics

The midpoints of the top of each bar of the histogram are plotted and connected with straight linesFrequency Polygon
Skewed curve with the tail to the rightPositively Skewed
Skewed curve with the tail to the leftNegatively Skewed
Average of the squared differences from the meanVariance
Square root of the variance; summary of dispersion around the meanStandard Deviation
Observations are widely spread outLarge SD
Observations are closely centered around meanSmall SD
68% values are within1 SD
95% values are within2 SD
99.7% values are within3 SD
Mean + - 2SDNormal Range
One standard deviation from the mean in each direction34%
One standard deviation from the first deviation13.5%
One standard deviation from the second deviation2.35%
One standard deviation from the third deviation0.15%
Standard deviation percentages cannot be apply to a study that has this type of distributionMulti-Modal Distribution
SD / square root (n)Standard Error of the Mean
Specifies how close our sample based value lies to the population value and it gives the range of these valuesConfidence Interval
Mean(x) +- confidence coeff x Standard Error MeanConfidence Interval
Is a score for normal distribution = confidence coefficient = standard scoreZ Score
(x – mean) / SDZ Score
Shows variability of observationsStandard Deviation
Shows variability of sample means about the true population meanStandard Error of the Mean
Is the range of values for the population mean in which you are 95% sure the true population mean falls95% Confidence Interval
Whole number countDiscrete
Includes fractional numbersContinuous
Characteristics of groups can be compared by comparing proportionsChi-Square
Characteristics of groups can be compared by comparing meanT-Test
States there is no difference between characteristics of groups or outcomesNull Hypothesis (H0)
States that there is a difference between characteristics of groups or outcomesAlternative Hypothesis (Ha)
When the data is interval/ratio, or if samples are different (when you are comparing “Means (averages)” between groups). If you only have 2 groupsT-Test
When the data is interval/ratio, or if samples are different (when you are comparing “Means (averages)” between groups). If you have more than 2 groupsANOVA
Two groups of subjects are sampled on one occasionIndependent (non paired) T- Test
The sample people are sampled on two occasionsDependent (paired) T-Test
Rejecting null hypothesis when the null hypothesis is trueType I Error (α error)
Accepting null hypothesis when the null hypothesis is falseType II Error (β error)
Calculated by 1 - βPower of the Test
A way to increase the power of a test is to do thisIncrease Sample Size

## Outbreak Investigation

The occurrence of cases of an illness in excess of expectancyOutbreak/Epidemic
Spike in the number of cases over a period of time that eventually decrease and stopPoint Source Outbreak
Increase in the number of cases that continue to increase over timePerson-Person Outbreak
Number of cases continue to rise and fall over time until the source is removedContinuous Source Outbreak
Confirm the diagnosis
Data collection
Generate hypothesis about pathogen, route of transmission, Vector/vehicle
Analytical epidemiology
Environmental inspection
Control Measures - Remove source and protect persons at risk
Is further investigation necessary
Preventive Measures
Communication
During the outbreak
Information for the public and the media
Information for professionals
After the end of the investigation
Produce a report for officials, parties involved, general public, media
Write up for scientific publication
Maintain surveillance