Ph2

Front 1

Infection

Back 1

Possibility of causing disease

Presence of the microbe in a host to the benefit of the micro-organism.

Front 2

Colonization

Back 2

Presence of microbes in host but which does NOT result in clinical disease and may be needed for health.

Front 3

T/F Bacterial colonization in the body necessarily causes clinical disease

Back 3

False. there are good flora too! think about yogurt

Front 4

Latent infection

Back 4

involves persistence of microbe in host with possibility of disease in future without shedding of organism in the interval

Front 5

What is an example of a latent infection (this is related to chickenpox)?

Back 5

Example: Shingles from Varicella Zoster

Front 6

Some examples of acute disease are ______ Some examples of chronic disease are ______

Back 6

Infections may also be acute (cholera, influenza) or chronic (leprosy, hepatitis B)

Front 7

Nonclinical infections

Back 7

inapparent infections which can still cause transmission of a disease.

These can occur at the preclinical (prior to onset of disease)

subclinical levels (mild disease, so spreads without being aware of having the disease

Front 8

Mary Mallon was famous for what disease and how did people respond?

Back 8

She was known as Typhoid Mary. She was a cook who transmitted typhoid fever. She was eventually quarantined

Front 9

Describe the typhoid fever carrier state

Back 9

can occur with or without acute symptomatic infection 2-5% of infections More common in women Shed organism for years

Front 10

Infectivity

Back 10

The ability of the microbe to cause infection (enter, survive, multiply in host), but not necessarily cause symptoms

Front 11

attack rate (for infection) =

Back 11

# infected / # exposed This attack rate (usually based on clinical criteria) is used in epidemic investigation

Front 12

Pathogenicity

Back 12

the ability of the microbe to cause disease. …without regard for severity!

Front 13

attack rate (for pathogenicity) =

Back 13

# of clinical cases / # infected

Front 14

Virulence

Back 14

the degree of severity of disease produced.

Front 15

Virulence attack rate =

Back 15

Virulence attack rate = # of fatalities / # of diagnosed cases = to case fatality rate

Front 16

Epidemic:

Back 16

a sudden increase in the frequency of infection in a particular region.

Front 17

Pandemic:

Back 17

an epidemic on a global scale HIV infection is an example

Front 18

Endemic:

Back 18

an infection that occurs regularly at a stable rate in a particular region

Front 19

Modes of Transmission Direct

Back 19

Person-to-Person Contact

Front 20

Modes of Transmission Indirect

Back 20

Common Vehicle 1.) Single exposure 2.) Multiple exposure 3.) Continuous exposures Vector

Front 21

Infections are transmitted from a reservoir

What are 4 common reservoirs?

Back 21

Inanimate objects
asymptomatic human
symptomatic human
Another species

Front 22

Reservoirs

Two examples of inanimate objects being reservoirs

Back 22

Fomite
contaminated water

Front 23

Reservoirs

Two examples of another species being reservoirs

Back 23

Zoonosis
Vector-borne diseases (like mosquitos)

Front 24

Food borne illnesses.
Two major ones.

Back 24

Salmonella
Botulism

Front 25

Crytosporidiosis is an example of a _______ illness

Back 25

waterbourne

Front 26

Airborne illness
Different size aerosols

Back 26

Air borne Large particle aerosols

Small particle aerosols or droplet nuclei residual of droplets which have evaporated to < 5 microns
- May remain suspended in air for prolonged periods of time

Front 27

Airborne illnesses

Diseases caused by large particle aerosols

Back 27

Bacterial: Hemophilus influenzae, Meningococci Diphtheria, Pertussis, pneumonic plague, Mycoplasma pneumoniae

Viral: - Adenovirus, Mumps, Parvovirus, Rubella

Front 28

Airborne illnesses diseases caused by small particle aerosols (droplet nuclei)

Back 28

Tuberculosis
Measles
Varicella
Influenza

Front 29

Vector borne illnesses

Description

Back 29

Vectors are other living organisms which harbor microbe and transmit to susceptible host

Front 30

Vector borne illnesses disease examples are:

Back 30

Examples: malaria, dengue, yellow fever

Front 31

Fomites. Definition and examples:

Back 31

inanimate objects which are contaminated and spread infection.

Examples: the common cold, cold sores, conjunctivitis, coxsackievirus (hand-foot-mouth disease), croup, E. coli infection, fifth disease (“slap cheek”), Giardia infection, impetigo, influenza, lice, meningitis, pinworms, rotavirus diarrhea, RSV, and strep

Front 32

Zoönosis

Back 32

infection normally present in vertebrate animals but which can rarely spread and cause disease in humans. (Example: brucellosis)

Front 33

Zoonosis

Why aren't we too concerned about zoonoses?

Back 33

Person to person transmission is rare. Disease may be mild. Infection usually requires extensive exposure.

Front 34

Describe the shape of a point source infection curve.

Back 34

Increase to a peak and then decrease

Front 35

Describe the shape of a continuous infection curve

Back 35

Increases to a plateau

Front 36

Describe the shape of a propagation infection curve

Back 36

Wavelike appearance with each crest increasing. There is a maximal crest and then a series of decreasing crests

Front 37

Statistical inference:

Back 37

drawing conclusions for data using statistical methods to describe and arrange data and to test suitable hypotheses

Front 38

Most scientific problems address whether there are __________ or _________ between variables

Back 38

differences, associations


most scientific problems address whether there are differences or associations between variables

Front 39

"null" hypothesis = ?

"research" hypothesis = ?

What are we trying to accomplish in most research studies?

Back 39

no difference = “null” hypothesis

a statistically significant difference = “research” hypothesis (also called the alternative hypothesis)
- most research studies aim to reject the null hypothesis

Front 40

null hypothesis:

What does this mean in terms of the predicted effect and the means of the treatment to the placebo?

How do represent the association?

Back 40

predicted effect does not exist;

that is, the mean response to treatment being tested is equal to the mean response to the placebo in the control group;

both responses have a normal distribution with an unknown mean and standard deviation

For difference: mean 1 = mean 2

For association: r^2 = 0

Front 41

Null hypothesis:

What is the equation in terms of means? Describe what the equation means in words.

Back 41

H0: μ1 = μ2

(that is that mean for the intervention group will equal mean for control group)

Front 42

Research hypothesis:

What is the equation in terms of means? Describe what the equation means in words.

Back 42

H1: μ for intervention > μ for control group

Front 43

What are the two variables found in studies?

Back 43

Factors (Independent variable)

Outcomes (Dependent variable)

Front 44

Which of these statistical calculations assume normal distribution?

t-test
Chi square
ANOVA

Back 44

Chi-square and ANOVA

Front 45

Type I error:

Back 45

reject the null hypothesis when it’s really true;

goal is to keep Type I error as low as possible

Front 46

Type II error:

Back 46

say the hypothesis is null when it’s really not

Front 47

How is the alpha level (α) related to type I and type II errors?

Back 47

When we pick the alpha level, we set upper limit on probability of making an erroneous decision to reject the null hypothesis (type I error)

Front 48

What is the typical alpha value that is chosen for studies?

We are aiming for ______ type I error.

Back 48

α = 0.05

We are aiming for low type I error

Front 49

degrees of freedom (df) =

Back 49

degrees of freedom (df) = total n - 2

total n = total number of participants in the study

Front 50

Once we have an alpha value, degrees of freedom and a calculated t value,

What do we do to determine whether there is statistical significance?

Back 50

use the student’s t distribution table

- look for the t - value that corresponds to the alpha value and the DoF

-Statistical Significance if
calculated t-value > table t-value

Front 51

T-Test

What does it mean if:

table t-value > calculated t-value?

Back 51

we cannot reject the null hypothesis; that is our t is not rare enough and our p value is not small enough

Front 52

p-value:

Is the probability that...

Back 52

probability that difference between groups during an experiment happened by chance or sampling error;

is the probability (0 to 1.0) of the sample statistics, given the samples size and assuming the sample was derived from a population in which the null hypothesis is true

Front 53

T/F P-value tells you whether or not the results are important

Back 53

False:

p-value does not tell you whether the null hypothesis is true or not but instead it is a probability- it tells you if your t is rare

Front 54

What is the equation for power?

What does this means in terms of the two types of errors?

Back 54

power = 1-β and is the probability of rejecting the null hypothesis when it’s false

Front 55

How can we increase power?

Back 55

- you can increase the power by increasing α (making it less stringent), making more room for error to capture more t’s but at the same time increasing chances of making a Type I error

Front 56

Increased power leads to an increased chance of making a _______ error.

Back 56

Type I error

Front 57

T/F Virtually any study can be shown to be significant by using a big enough sample size

Back 57

True

Front 58

We can increase the power by increasing the ______ because small samples have “flukiness” and more sampling error which equals _______

Back 58

sample size,

larger p value

Front 59

What is the purpose of a standard error as it relates to the sample statistic?

Back 59

standard error is related to the precision of sample statistic- we can express our confidence in our mean by calculating standard error

Front 60

SE gets _____ as the SD increases and _____ as n increases

Back 60

larger

smaller

Front 61

SE

Back 61

SE = SD/ sq. rt (n)

Front 62

What does a large SE of the means indicate?

Back 62

a large SE of means says that there’s a lot of variability between sample means;

that is, we don’t have confidence that our estimate (mean) equals the population

Front 63

As n increases what happens to the means and the SE?

Back 63

as n is increased, we get more and more stable means (smaller and smaller SE)

Front 64

As n increases what happens to the probability that you will get a statistically significant mean?

Back 64

Increases

Front 65

What is the value of calculating power prior to the start of the study?

Back 65

Knowing the power allows you to pick the proper n for the study

Front 66

Confidence intervals

If the confidence interval for a risk interval crosses one, is there statistical significance?

Back 66

No

- if the null hypothesis is that the odds ratio = 1 (no difference), then a 95% CI range that includes 1 means no statistical significance while a 95% CI range that does not include 1 means statistical significance

Front 67

Confidence Intervals

If the null hypothesis is that the difference in the means is 0, what must be true about the CI if we want to reject the null hypothesis of no difference?

Back 67

The CI cannot include 0

Front 68

What is the difference between clinical and statistical significance?

Back 68

it’s important to note the difference between statistical significance and clinical significance; to determine clinical significance, we want to know if the effect (shown to be statistically significant) is enough to make a real-world/practical difference

Front 69

What measure is typically used to determine clinical significance?

Back 69

effect size:

the observed and standardized measure of the magnitude of the observed effect

Front 70

Effect size:

Back 70

the observed and standardized measure of the magnitude of the observed effect

Front 71

Cohen’s d (an effect size) =

How do we interpret the Cohen's d value?

Back 71

(mean1 – mean2)/SD pooled

- an effect size of 0.2 is a small effect
- 0.5 a medium effect
- 0.8 or higher a large effect

Front 72

Cohen's d, small effect value

Back 72

0.2

Front 73

Cohen's d, medium effect value

Back 73

0.5

Front 74

Cohen's d, large effect value

Back 74

0.8 or higher

Front 75

Why is the effect size important for studies?

Back 75

effect sizes help address stability of effect across studies: helps scientists collectively move forward with the business of science

Front 76

T/F A result that is rare is necessarily significant

Back 76

False

Front 77

T/F A p-value above 0.05 means the research is not valuable.

Back 77

False. It is possible that the sample size was not sufficient.

Front 78

T/F Scientists are more likely to put more credibility in a lower p-value

Back 78

True

BUT REMEMBER
- don’t base your belief in something because of a low p value

Front 79

T/F Just because results are statistically significant means that they are important

Back 79

False

Front 80

_____ or ______ is responsible for ALL mean differences

Back 80

chance or sampling error is responsible for ALL mean differences.

Front 81

weak positive correlation-

Back 81

as x ↑, y ↑ but weak correlation

Front 82

strong negative correlation

Back 82

as x ↑, y ↓

Front 83

perfect positive correlation

Back 83

for every degree x increases, so does y

Front 84

Pearson Correlations
Requirements

Back 84

1. random selection of sample
2. normality of traits measured
3. at least interval level measurement
4. similar variation in x and y scores (assume that x and y distributions are normal, not skewed)
5. linear relation between x and y

Front 85

Describe the range of the Pearson's coefficient

Back 85

Pearson: r value ranges between -1 (a perfect negative relationship) to 0 (no relationship) to +1 (a perfect positive relationship)

Front 86

Pearsons Coefficient (r)

(+ or -) 0.8-1.0

Back 86

very strong relation

Front 87

Pearsons Coefficient (r)

(+ or -) 0.6 -0.8

Back 87

strong relation

Front 88

Pearsons Coefficient (r)

(+ or -) 0.4-0.6

Back 88

moderate relation

Front 89

Pearsons Coefficient (r)

(+ or -) 0.2-0.4

Back 89

weak relation

Front 90

Pearsons Coefficient (r)

(+ or -) 0.0-0.2

Back 90

little or no relation

Front 91

What does r^2 (coefficient of determination) tell you

Back 91

r^2 (coefficient of determination) tells you the percentage of shared variability (the strength of the association in proportion of variation in y explained by x)
- the higher the coefficient of correlation, the more you can explain x by y

*remember that correlation does not equal causation

Front 92

T/F Correlation = Causation

Back 92

False

Front 93

T/F Pearson's correlations do not allow us to determine causation

Back 93

True.

** it’s important to remember that Pearson correlations help determine a relationship between 2 variables but does not allow us to determine causation**

Front 94

Ordinal tests require ________ tests

why?

Back 94

nonparametric

data that’s ordinal requires nonparametric tests because with ordinal data, we don’t understand how much one scale point is different from another

Front 95

T/F Nonparametric tests do not assume a normal distribution

Back 95

True

Front 96

Spearman Rank

Back 96

a commonly used nonparametric test is the Spearman Rank correlation which is a nonparametric alternative to Pearson’s r that makes no assumptions about the populations mean or standard deviation

Front 97

Data is ordinal and does not follow a normal distribution.

Spearman's or Pearsons?

Back 97

Spearman's Rank correlation

Front 98

Data follows a normal distribution.

Spearman's or Pearsons?

Back 98

Pearsons correlation

Front 99

Spearman's Rank correlation

What are the requirements

Back 99

1. random selection of sample
2. both distributions of scores are in ordinal form (may have been converted by making continuous variables into categories)
3. linear relation between sets of scores

Front 100

Spearman's Rank Correlation

What are the steps in determining correlation?

Back 100

- computed “obtained” test statistic value (rs) is calculated and then the “critical” value of the test statistic (rcrit) is derived from a table

- rs is compared to rcri and:

- if absolute value of rs is greater than rcrit, reject the null hypothesis

- if absolute value of rs is smaller than rcrit, then fail to reject the null hypothesis

Front 101

Chi-Square Test
Requirements:

Back 101

1. randomly select samples
2. nominal level of measurement
3. independent cell entries (each participant can only be in 1 cell)
4. no expected cell frequency below 5 (assume 5 incidences in each cell)

Front 102

Chi-Square Test

Cell frequency 3

Can we run the Chi-Square?

Back 102

No.

no expected cell frequency below 5 (assume 5 incidences in each cell)

Front 103

Assumptions of a Chi-Square test:

Back 103

H0: fo = fe
Ha: fo ≠ fe

Front 104

Steps in performance of a Chi-Square test:

Back 104

1. then determine degrees of frequency: df = (# of rows-1)(# of columns-1)

2. using df and the α level you choose, get critical chi from a table

3. calculate chi for the data

4. compare chi calculated to chi critical

Front 105

Chi-Square Test:

What is our interpretation when the
chi calculated > chi critical?

Back 105

- if chi calculated is larger, then reject the null and conclude that the variables are not independent

Front 106

the n you choose depends on 4 other values:

Back 106

1. significance level, α (usually 0.05)

2. desired power (usually 80-95%) [power is the probability of rejecting the null when the null is not true]

3. variability of the population(s), σ’s

4. amount of change, Δ, from H0 (null) that we realistically want to detect

Front 107

sample size required for a study is increased by what changes in the following?

alpha
power
standard deviation
delta

Back 107

smaller alpha

larger power

larger standard deviation

decreases in delta (the changes we want to detect)

Front 108

randomization:

Back 108

randomly assigning each participant to a treatment group

Front 109

How do we use randomization in clinical trials?

Back 109

Used to reduce bias

used in clinical trials for internal validity by reducing bias (ex: having more people with a similar characteristic in 1 group than another group)

Front 110

How do we use randomization in interventional studies?

Back 110

Used to average out confounding bias

in intervention studies, we have the opportunity to select which subjects get which treatment- by randomly assigning subjects to treatment groups, we hope to average out the effects of confounding variables

Front 111

T/F Randomization doesn’t guarantee a perfect balance among confounders;

Back 111

True;

however, for reasonably large n’s, it’s unlikely that serious imbalances will occur

Front 112

Name two situations where randomization isn't possible

Back 112

when studying the difference between men and women

when randomization would be unethical

Front 113

HIV Pandemic showed us the ______ systems are important warning systems

Back 113

surveillance

Front 114

HIV Pandemic

What is the common cause mode of transmission in males? females?

Back 114

males - male-male
female - high risk heterosexual activity

Front 115

How can the prevalence of HIV be increasing while incidence remains stable?

Back 115

- duration of HIV is increasing due to improved treatment (HIV pts are living longer with the disease)

Front 116

The upper respiratory tract is capable of removing particles greater than _____

Back 116

4-5 microns

Front 117

Epidemic Curves

Latent Period (Definition)

Back 117

time between infection and when it can be spread to others

Front 118

Epidemic Curves

Incubation Period (Definition)

Back 118

time between infection and when symptoms appear

Front 119

Epidemic Curves

What is significant about the timing of the latent period and incubation periods?

Back 119

Latent period starts earlier than the Incubation period


This allows the infection to spread to individuals prior to when the symptoms start to appear

Front 120

Epidemic Curves:

Point Source Infections appear _____ skewed

Back 120

Positively

Front 121

Epidemic Curves:

The gaps between the peaks on the curve of a propagated infection indicate the _______

Back 121

incubation period

Front 122

Epidemic Curves:

Propagated infection refers to ________

Back 122

Transmission of infection from person to person

Front 123

Multivariable Models

Back 123

have more than 1 independent variable AND 1 dependent variable

Front 124

Multivariable Models

multivariate models (MANOVAs)

Back 124

are models with more than 1 independent variable and more than 1 dependent variable

Front 125

Multivariable Models

Requirements for multivariable models:

Back 125

1. random selection of samples

2. normality of traits in population

3. homogeneity of variance

4. at least 1 independent variable (nominal or ordinal) with 3 or more “levels” (which is the only distinction between multivariable models and t-tests)

5. one dependent variable (interval or ratio level)

Front 126

Multivariable Models

Regression Models:

Back 126

are models with an independent variable that’s either interval or ratio (not nominal) and the dependent variable is also interval or ratio

Front 127

ANOVA

Back 127

are defined by the number of independent variables (with 3 or more levels)

Front 128

ANOVA

a simple or one-way ANOVA has ________

Back 128

1 independent variable

Front 129

ANOVA

factorial ANOVA:

Back 129

designs with more than 1 independent variable

Front 130

two-way ANOVA

Back 130

has 2 independent vaiables

- ex: dosage groups with 3 levels and age groups with 4 levels- this would be called a 3x4 ANOVA

Front 131

- three-way ANOVA

Back 131

has 3 independent variables

- ex: 3 levels of dosage, 4 levels of age, and 3 levels of weight- this would be called a 3x4x3 ANOVA

Front 132

repeated measures ANOVA:

Back 132

where dependent variable is measured multiple times (time is an independent variable- longitudinal)

Front 133

analysis of covariance (ANCOVA):

Back 133

where dependent variable is corrected based on covariates (control for impact of potential cofounder)

Front 134

How are the t-test and ANOVA related?

Back 134

ANOVA is really just a mathematical extension of the t-test

- t-test has 2 levels of independent variables while ANOVA has more than 2 levels of independent variables

Front 135

ANOVA is an "omnibus" test. What does this mean?

Back 135

it tells you whether there are any significant differences between ANY of the means, but does not tell you which pairs had significant differences

Front 136

What kind of test usually follows an ANOVA?

Back 136

another type of test called a “post hoc” test must be done

Front 137

in combining probabilities, if the events A and B are mutually exclusive

A = 0.4
B = 0.3

Back 137

P(A or B) = P (A) + P (B)
= 0.4 + 0.3 = 0.7

Front 138

say your chance of surviving a year after a diagnosis of prostatic cancer is 80% and that the chance of surviving 2 years is 60%- given that you’ve survived 1-year, what’s your chance of making it to 2 years?

Back 138

A = “survive 2 years”
B = “survive 1 year”
P (A|B) = 0.6/0.8 = 0.75 (75%)

Front 139

Decision Trees

Back 139

can be described as a graphical aid to keep track of probabilities, both conditional and otherwise

Front 140

Independence

When A and B are independent then P (B|A) = ???

Meaning

Back 140

P (B|A) = P (B|A*) = P(B)

- that means that the probability of B is the same whether you know that A is true, that A is not true, or you don’t know anything about A at all

Front 141

Multiplication Rule

A box has 5 black balls and 5 white balls. The chance of picking 2 black balls is

Back 141

5/10 * 4/9 = 20/90 = 2/9

second number is 4/9 because there is one less black ball to pick from (4) and consequently one less ball to pick from overall (9)

Front 142

The responsibility of the health of the US population falls under control of the _________

Back 142

state government

Front 143

What organization is responsible for the health of the US population when there are interstate implications for a health situation such as an outbreak?

Back 143

Centers for Disease and Prevention (CDC), which is part of the Department of Health and Human Services

Front 144

In an outbreak that effects multiple states, what is the relationship between the states and the CDC?

Back 144

The states report data to and request assistance from the CDC

Front 145

Cases can be first noted or identified by _______ or ______

Back 145

astute clinicians

surveillance

Front 146

What do you call the first case identified by surveillance?

Back 146

The "Index case"

Front 147

An index case may represent a _______ that is, when investigated, more cases are found and a need for public health action is determined

Back 147

"sentinel" health event

Front 148

Surveillance's main purposes

Back 148

As an early warning system

prompt identification of shared exposures in order to prevent additional cases

Front 149

The Paradox of Public Health:

Back 149

The problem is that we only care about public health when it fails;

When public health infrastructure is working well, it appears like a waste of resources

Front 150

The following paragraph describes what epidemiological concept?

Tuberculosis was very well-controlled in the US until the 1970s when government decided to cut back on funding; there was a huge surge of TB outbreaks (esp associated with HIV); then the need for public health initiatives was recognized and in the mid 1990s TB cases declined again

Back 150

The Paradox of Public Health

Front 151

Surveillance is targeted to the level of ____________ and is an _____ _____ prevention method

Back 151

Surveillance is targeted to the level of populations and is an indirect primary prevention method

Front 152

Who generally handles surveillance?

Back 152

State public health agencies

Front 153

What are the four main components of Surveillance?

Back 153

1. case reporting (physicians report to state agency)

2. data analysis (done by the state public health agency)

3. communication of results (state agency informs physicians about outbreaks so that they are more vigilant)

4. application of findings (usually by physicians)

Front 154

Surveillance - who is responsible?

Case reporting

Back 154

physicians report to state agency

Front 155

Surveillance - who is responsible?

Data analysis

Back 155

Done by the state public health agency

Front 156

Surveillance - who is responsible?

Communication of results

Back 156

state agency informs physicians about outbreaks so that they are more vigilant

Front 157

Surveillance - who is responsible?

Application of findings

Back 157

usually done by physicians

Front 158

What is a brief way to define surveillance?

Back 158

information for action

Front 159

Life cycle of Disease Prevention and Control

Back 159

Surveillance -> epidemiological research -> applied research -> prevention methods - (back to)> surveillance

Epidemiological research is also linked to prevention methods

Front 160

Public Health Surveillance Loop

Back 160

Physicians report to the health agencies who analyze the data and return summaries, interpretations and recommendations to physicians and the general public

Front 161

Bioterrorism requires that we have a good _______ _______ _____ for preparedness and good ______ _____

Back 161

Bioterrorism requires that we have a good public health system for preparedness and good surveillance systems

Front 162

How are cases in bioterrorism usually reported and what does this mean?

Back 162

syndromic case-reporting

- case reports describe a constellation of symptoms (syndrome)

This is done because bioterror agents are rare and therefore diagnosis of a specific disease can be difficult

Front 163

CDC Category A Diseases/Agents for Bioterrorism:

what are the four major features of these diseases?

Back 163

- “high-priority agents include organisms that pose a risk to national security because they:

- can be easily disseminated or transmitted from person to person
- result in high mortality rates and have potential for major public health impact

might cause public panic and social disruption

- require special action for public health preparedness”

Front 164

CDC Category A Diseases/Agents for Bioterrorism:

what are the 6 Cat. A diseases/agents?

***KNOW***

Back 164

1. anthrax
2. botulism
3. plague
4. smallpox
5. tularemia
6. viral hemorrhagic fevers (both filoviruses like Ebola and Marburg and arenaviruses like Lassa and Machupo)

Front 165

Important Attributes of Surveillance Systems

Back 165

Simplicity
flexibility
Data Quality
Timeliness
Acceptability
Sensitivity
Positive Predictive Value
Stability
Representativeness

Front 166

Important Attributes of Surveillance Systems

Why is simplicity important?

Back 166

a simple form that is easy to complete helps to increase compliance

Front 167

Important Attributes of Surveillance Systems

Flexibility

Back 167

flexibility: able to respond to changes (esp if there’s social disruption)

Front 168

Important Attributes of Surveillance Systems

Reliability

Back 168

must be valid, reliable, and standardized (so can compare with past data)

Front 169

Important Attributes of Surveillance Systems

Timeliness

Back 169

must report quickly, analyze quickly, and get information back to physicians quickly

Front 170

Important Attributes of Surveillance Systems

Acceptable

Back 170

everyone is willing to participate

Front 171

Important Attributes of Surveillance Systems

Do we want low or high sensitivity?

Back 171

want high sensitivity (like in screening tests) even at expense of specificity

Front 172

Important Attributes of Surveillance Systems

Do we want high or low false positives? why?

Back 172

don’t want a lot of false positives because would trigger system for unnecessary reasons and waste money

Front 173

Important Attributes of Surveillance Systems

Stability

Back 173

esp if there’s social disruption

Front 174

Important Attributes of Surveillance Systems

- representativeness

Back 174

need to report across various groups in a population (rich, poor, all ages, all races, insured and uninsured, homeless, etc.)

Front 175

Types of Surveillance

Describe passive surveillance. What are some features and problems of passive surveillance

Back 175

passive: physician, infection control personnel (ICP), or lab reports cases as prescribed by state or local law without prompting

- problem: physicians are highly noncompliant

- features: provider-initiated, less complete, less labor, cheap

Front 176

Types of Surveillance

active or stimulated: Define, compare to passive surveillance, features

Back 176

active or stimulated: same as passive but also have regular examination and prompting done to ascertain presence or absence of cases

- results in better compliance
- features: Health Department-initiated, more complete, labor intensive, expensive

Front 177

Types of Surveillance

T/F Active or stimulated surveillance is cheaper than passive surveillance

Back 177

False.

Since active or stimulated surveillance often is Health Department-initiated, more complete, and labor intensive, the cost is usually higher than in passive surveillance

Front 178

Who is required by state law to report Disease under penalty of law?

Back 178

Licensed practitioners and labs

Front 179

What is the problem with licensed practioners and labs when it comes to reporting disease?

Back 179

penalty laws are rarely enforced

Front 180

T/F Most cases of reportable disease are not reported

Back 180

True

Front 181

CSTE and CDC list of reportable Diseases

Category 1 - time to report is ____

report to?

Back 181

24hrs

Category 1: reportable to local public health department within 24 hours of diagnosis
- ex: botulism

Front 182

CSTE and CDC list of reportable Diseases

Category 2 - time to report is ____

report to?

Back 182

1wk

Category 2: reportable to local public health department within 1 week
- ex: cryptosporidiosis

Front 183

CSTE and CDC list of reportable Diseases

Category 3 - time to report is _____

report to?

Back 183

1wk

Category 3: reportable to local WV Bureau of Public Health (State Health Department) within 1 week of diagnosis unless otherwise noted
- ex: HIV/AIDS must be reported to the state (not locally) within 30 days

Front 184

What is true reporting of diseases in WV?

Back 184

- in WV, not all reportable diseases are infectious
- ex: elevated lead, birth defects, cancer, hemophilia, etc.
- in WV, reporting is required by law and failure to report results in fines (but this is rarely enforced)
- in WV, for some diseases, may need to fill out supplemental forms for CDC and WVBPH

Front 185

What is the general rule in the reporting of diseases?

Back 185

More severe, rarer diseases are more likely to be reported than less severe, more common diseases

Front 186

International health regulations require mandatory declaration of what diseases to WHO?

Back 186

Cholera, plague, and yellow fever

Front 187

Steps in Epidemic Investigation

Back 187

1. establish the diagnosis** (most important)- only trust your own eyes to get credible information

2. establish a case definition
- a very operational definition which can identify cases easily and quickly, not a definition based on serological studies that take long time to get results

3. is an epidemic occurring?

4. characterize by person, place, and time

5. develop hypotheses regarding spread of disease

6. test hypotheses

7. initiate control measures

8. follow-up

Front 188

Food-caused illnesses often cause this kind of epidemic.

Back 188

Point Source Epidemic

Front 189

Attack rates for determining which foods caused the disease.

What two calculations should be done?

Back 189

attack rate for eating x = # of people ill that ate x / total # of people who ate x

attack rate for not eating x = # of ill that did not eat x/ total # of people who did not eat x

attack rate for eating x – attack rate for not eating x = difference in attack rates

Front 190

Attack rates for determining which foods caused the disease

The food with the highest positive difference in attack rates is usually the ______

Back 190

cause of the outbreak

there are some exceptions - make sure that the numbers make sense in the context of the whole table

Recall in our example that barbecued chicken and cola had the highest attack rates, but cola was a confounder

Front 191

What is the equation for the basic reproductive number?

Back 191

Ro = c x p x d

c: number of contacts per unit of time
p: probability of transmission with contact
d: duration of infectiousness (in units of time)

Front 192

T/F Ro varies with populations, behavior, time, and other factors

Back 192

True

Front 193

T/F Ro only accounts for the first spread of disease and does NOT account for secondary transmissions

Back 193

True, subsequent infections are NOT included in Ro

Front 194

If we want to control infections we should try to keep Ro ______

Back 194

below 1

if Ro <1, then 1 person is spreading the disease to less than 1 other person on average

Front 195

T/F Ro gives us an indication of the period between the spread of disease

Back 195

False

Ro tells us nothing about how long this takes (since the units of time cancel out in calculating Ro)

Front 196

What is a unique situation where Ro falls below one?

Back 196

Ro usually falls below 1 when the pool of susceptible people “runs out” because they all get the disease

Front 197

Describe the characteristics of an epidemic in terms of time when Ro is high

Back 197

if Ro is high, then there’s an explosive spread of the disease which depletes S (the pool of susceptible people) just as quickly so it dies out quickly- shorter epidemic

Front 198

Describe the characteristics of an epidemic in terms of time when Ro is low

Back 198

- if Ro is low, then have longer epidemic

Front 199

T/F Kid 1 doesn't have any symptoms of a disease. He is unable to pass the disease along to one of his friends

Back 199

False

- it’s important to note that the infectious period proceeds the symptomatic period (this is necessary for successful propagation of the organism)

Front 200

What are the three main things we can do to control infections?

Back 200

Environmental measures

Prompt investigation and management of outbreaks

Vaccinations

Front 201

What is the #1 thing that you should always remember to do to help curb infection control in the Health Care Setting?

***KNOW***

Back 201

hand-washing is the single most important/effective tool for disease control in the healthcare setting

Front 202

What are some ways we can help control infection in the hospital setting?

Back 202

Handwashing
Appropriate attire
Appropriate use of antibiotics
Reduce use of invasive devices
Surveillance systems

Front 203

T/F Doctors have a high compliance when it comes to handwashing

Back 203

False

Front 204

Quarantine

Two major features

Back 204

:restriction of activities on the basis of exposure
another important feature of quarantine is early detection of disease

Front 205

Quarantine

Two major forms

Back 205

2 forms:
- absolute or complete: no contact whatsoever
- modified: partial restriction in activities

- ex: a single man brought SARS to Toronto from Singapore and 100’s became ill; many health workers were put in modified quarantine- they were told to stay at home, wear a mask when they were around their families, and to take their temperatures twice a day (early detection of disease)

Front 206

Absolute Quarantine

Back 206

No contact whatsoever

Front 207

Modified Quarantine

Back 207

modified: partial restriction in activities

Front 208

Isolation

Back 208

restriction of activities on the basis of infection until infectious period has passed
- usually specific to mode of transmission

Front 209

The difference between Isolation and Quarantine is?

Back 209

Isolation - person is infected

Quarantine - person may/may not be infected (they may have been exposed)

Front 210

The purpose of vaccines it to provide herd immunity. What does this mean?

Back 210

With a high proportion of immune individuals the spread of disease is minimized and the individuals who are susceptible are protected by the immune individuals (are “free riders”)

Front 211

T/F Vaccinations are individual-level efforts to keep Ro low

Back 211

FALSE

- vaccinations are population-level efforts to keep Ro low

Front 212

Disease Eradication

Incidence of the disease

Types of disease that can be eradicated

Back 212

is the permanent reduction of a disease to 0 incidence

- only infectious diseases can be eradicated

Front 213

WHO definition of eradication.

Back 213

elimination is reducing a condition to lowest feasible levels

preventive measures are no longer needed

usually eradication involves a non-sustainable campaign where lots of money is gathered to eradicate a disease

Front 214

The only disease to have ever been eradicated is _____ and it was the ___ WHO eradication effort

Back 214

smallpox,

5th

Front 215

What are some factors that must be considered before attempting to eradicate a disease?

Back 215

- non-human reservoirs make eradication almost impossible
- ex: cholera is impossible to eradicate because its reservoir is water
- simple measure (vaccination, filtering water, etc)
- disease is easily identified

Front 216

What characterizes a vaccine that can be used for eradication?

Back 216

- safe for all age groups
- effective
- single dose
- stable in field conditions (don’t need to refrigerate)
- inexpensive

Front 217

Currently the WHO is trying to eradicate ____

Back 217

polio

Front 218

Dr. Martin thinks this horrible disease will be the next to be eradicated.

Back 218

Dracunculiasis (Guinea worm disease)

where a worm found in fresh-water crustaceans is taken in by drinking, the crustacean dies but the worm lives and travels down to the human’s foot where it burrows out

Front 219

How can we prevent the drinking of the worm that causes dracunculiasis?

Back 219

drinking in this worm is easily prevented: can filter water through cheese cloth which removes the crustacean, can boil water which kills the organism, or can use larvicide to kill

Front 220

What are some new emerging infectious diseases?

Back 220

- HIV
- SARS
- Ebola

Front 221

What are some old infectious diseases that are reemerging?

Back 221

TB
antibiotic resistant bacteria

Front 222

What are three host factors that make us more susceptible to emerging infectious diseases?

Back 222

more immuno-compromised people

international travel

behaviors

Front 223

What are three environmental factors that are making us more susceptible to emerging infectious disease?

Back 223

Competition for land which brings us into closer contact with farm animals

Globalization

Breakdown of public health systems
- such as reduced vaccination

Front 224

What are two factors in agents that are increasing our risk of emerging infectious diseases?

Back 224

Development of antibiotic resistance

Ability to mutate

Front 225

Definition of Injury

Back 225

“damage to an individual due to energy exchange or from acute disruption in the normal body energy process”
- excessive transfer of energy can be mechanical (75%), electrical, chemical, thermal, and radiation
- mechanical injury includes motor vehicles (31% of all injuries), firearms (22%), falls (8%), and other forms (13%); the remaining 25% of injuries are results of other types of energy transfer

Front 226

Injuries

Are they accidents?
Are they random?

Back 226

are not accidents

are predictable (not random) events that are preventable because they have known risk factors

Front 227

Injuries

2 classifications

Back 227

Intentional

Unintentional

Front 228

What are some examples of injuries resulting from acute disruption of a normal energy process?

Back 228

Drowning, near drowning
asphyxiation, CO
poisonings, ingestions

Front 229

Injuries were the leading cause of death for what age groups in 1945 and 2004?

Back 229

1945 - ages 1-24
2004 - ages 1-44

Front 230

What is striking about the incidence of injury and lifetime cost due to injury when we compare the years 1985 and 2000?

Back 230

Incidence of injury dropped 12%

lifetime cost due to injury has increased 158%

Front 231

What are some ways we can look at injury cost data?

Back 231

incidence counts and rates

fatal, hospitalized, nonhospitalized
lifetime productivity losses medical costs
total lifetime costs age and sex
body region injured mechanism of injury
nature of injury

Front 232

The 3% decrease every 5 years in injury fatality rate since 1910 indicates what?

Back 232

The drop in injury fatality rate parallels the decreases seen in chronic diseases that were more commonly fatal during the earl 20th century (influenza/pneumonia, TB, gastroenteritis)

Front 233

T/F New chronic disease are making the deaths due to chronic disease rise

Back 233

True. AIDS is one example

Front 234

Who were the "parents of injury epidemiology"?

Back 234

- the parents of injury epidemiology were William Haddon, who worked for highway safety, and Susan Baker, author of Injury Fact Book

Front 235

What are the four steps in the public health approach to injury?

Back 235

1. surveillance

2. risk factor identification

3. intervention evaluation

4. implementation

Front 236

What is the ultimate goal of the public health approach to injury?

Back 236

to change policy to change human behavior

Front 237

What are the 3 phases of injury?

Back 237

pre-injury: control of energy source lost

injury event: injury is transferred to people, causing damage

post-injury: regain physiological homeostasis and repair damage

Front 238

Pre-injury

Back 238

control of energy source is lost

Front 239

injury event

Back 239

injury is transferred to people, causing damage

Front 240

post-injury

Back 240

regain physiological homeostasis and repair damage

Front 241

The host agent and environmental factors determine what in an injury?

Back 241

Determine the loss of control which leads to injury, the extent of injury, and the degree of recovery

Front 242

Injury as it pertains to the epidemiological triangle

Agent?
Vector?

Back 242

Agent is the source of energy that caused the injury

Vector can transmit energy from the agent to the host

Front 243

What can we do to reduce the likelihood of an injury event?

Back 243

prevent or limit energy buildup

control circumstances of energy use to prevent unintended release

modifiy energy transfer to limit damage

Improve emergency, definitive, and rehabilitative care to affect recovery

Front 244

What is Haddon's Matrix?

Back 244

- takes the applied temporal factors into account with the epidemiological triangle

- was originally used to create highway safety measures: safer vehicles, safer roads, safer occupants, significant reductions in vehicle deaths per miles driven

- since 1972 (the matrix’s creation), Haddson’s matrix has been applied to both intentional and unintentional injury control

Front 245

What is the practical use of Haddon's matrix?

Back 245

Haddson’s matrix has been applied to both intentional and unintentional injury control

- useful for planning, resource allocation, and preventive strategy identification

Front 246

injury control:

Back 246

reducing frequency of injury and/or reducing impact from injury

Front 247

injury prevention (primary prevention

Back 247

preventing an injury from occurring in the first place

Front 248

acute care (secondary prevention):

Back 248

improving the medical response to an injury to help limit the amount of damage

Front 249

rehabilitation:

Back 249

improving the outcome from injury and decreasing disability

- often education, law, and technology are used together to help control and prevent injury

Front 250

Rehabilitation:

Out of education, law, and technology, which one is the most important?

Back 250

- of these 3, technology is the most important but it’s also very expensive and time-consuming to develop

Front 251

Injury prevention strategies

education

Back 251

reduce unsafe behaviors and promote safe behaviors

Front 252

Injury prevention strategies

legislation

Back 252

laws and policies to promote safety, remove unsafe products or punish unsafe behaviors

Front 253

Injury prevention strategies

engineering

Back 253

making the environment and products safer through design and manufacturing improvements; minimize human involvement (thus minimize error)

Front 254

What are some past injury control successes?

Back 254

- injury control successes include seat belts, auto safety, roadway design, bike helmets, smoke alarm programs, and graduated license programs

Front 255

Challenges to Injury Control

ATV

Back 255

- even though bike deaths are decreasing due to access to safer places to ride bikes and to use of helmets, ATV deaths are increasing

Front 256

Challenges to Injury Control

Gun Control

Back 256

gun control: guns are faster, more efficient, and have more rounds; they are also easy to obtain

*death from firearms is considered a U.S. epidemic

Front 257

Challenges to Injury Control

Impaired driving

Back 257

- 30-35% of automobile fatalities are due to DUI’s
- elderly driving also raises issues- should the elderly have to take a license exam every year?

Front 258

Role of the Practitioner in Injury Control

What can we do?

Back 258

- identify injury problems
- design and evaluate interventions
- counseling and education
- media interactions
- legislative advocacy

Front 259

ATV

Characteristics

Back 259

300-600 lbs; oversized, low-pressure tires; straddle seat; operator must be “rider-active”; handle bar for steering; motorized, gas-powered; increasingly larger engines and speeds up to 100 mph;

Front 260

ATV

Intended Use

Practical use

Back 260

intended for use off-road and on non-paved surfaces

are important part of WV culture: farming, mining, other occupations, hunting, competitive riding, and recreation

Front 261

T/F More than one third of ATV deaths in the last 2 years in WV are due to DUI

Back 261

True. 35% of ATV deaths in the last 2 years in WV are due to DUI

Front 262

T/F It is legal to use an ATV on any road with any center line markings in WV

Back 262

False. It is illegal

Front 263

ATV

What kind of intervention is described below?

Make ATVs safer, educate on wearing helmet and not driving when drunk, and outlawing the use of ATVs on roads and highways

Back 263

Pre-incident (primary prevention)

Front 264

ATV

What kind of prevention is described below?

Don't carry passengers while riding on an ATV

Back 264

incident (secondary prevention)

Front 265

T/F The typical passenger victim in an ATV accident is a 12-14 year old female

Back 265

True

Front 266

T/F People typically do not wear helmets while riding an ATV

Back 266

True

Front 267

Why are children more likely than adults to have a head/neck/spine injury in an ATV accident than adults?

Back 267

Because they are thrown out of the vehicle

Front 268

Describe the Public Health Burden of ATV injuries in terms of YPLL

Back 268

YPLL (based on 75, not 65) for males is 37 years and for females is 54 years

(this means the average age of death in males from an ATV injury is 38, while it’s 19 in females)

Front 269

What makes ATV injuries quite costly to taxpayers?

Back 269

- 1/3 of people injured by ATVs are insured by Medicare or Medicaid, a significant burden to taxpayers

Front 270

What are the three objectives for Healthy People 2010 pertaining to ATVs?

Back 270

Pass helmet law for youth and adults

Reduce death rates

improve injury surveillance

Front 271

WV 2007 Strategic Highway Safety Plan

Back 271

- reduce fatalities by 20%
- expand helmet law, require liability insurance
- require training
- develop crash tracking system

Front 272

What was the only successful legislation passed in WV on ATV safety?

Back 272

in 2004 legislation was passed pertaining to where ATVs can be ridden, passengers, helmets for kids, training, penalties, and local government authority

Front 273

ATV

Who can educate individuals about ATV safety?

Back 273

- adults and parents can lead by example and use common sense

community provides DMV safety awareness course, school education, healthcare education, and 4H education

parents should supervise their children, ensure helmet use, ensure training, understand and explain the risk, and use common sense (which unfortunately can’t be legislated)

Front 274

ATV

Who is ultimately responsible for the safety of the ATV rider?

Back 274

- the responsibility for careful operation rests almost entirely on the ATV rider

Front 275

demography:

Back 275

scientific study of the determinants and consequences of population trends (mortality, fertility, migration)

Front 276

Our population has reached 6 billion when has most of the population growth occured?

Back 276

In the past 200 years

Front 277

Who brought up the issue of the population explosion?

Back 277

Paul Ehrlich,

a population biologist, wrote The Population Bomb, bringing attention to the issue of the population explosion

Front 278

What is the equation for the natural increase in population?

Back 278

Natural increase = birth rate - death rate

Front 279

Why is the population of the world growing despite the fact that both birth rates and death rates are declining?

Back 279

Death rates are lower than birth rates

Front 280

Over 90% of the population increase in the 20th and 21st century is occuring in the ______

Back 280

less-developed world

Front 281

What is the Law of 70?

Back 281

if a population is growing at a constant rate of 1% per year, it can be expected to double approximately every 70 years

Front 282

If the population is growing at a rate of 0.5% per year what is the doubling time?

Back 282

140 years

Front 283

What did Malthus propose about populations in his Essay on the Principle of population?

Back 283

population tended to grow geometrically (exponentially) while the means of subsistence (food) grew only arithmetically (this is now known as the “Malthusian Trap”)

Front 284

What are Malthus's postulates?

Back 284

1. food is necessary to the existence of man

2. the passion between the sexes is necessary and will remain nearly constant

- the power of population is indefinitely greater than the power in the earth to produce subsistence for man

Front 285

Malthus's postulates

Since there is tension between the growth of the population and the means of subsistence, _____ would serve as a positive check on population growth

Back 285

mortality

Front 286

Malthus's postulates

Solutions to the population growth/Subsistence problem

Back 286

preventive checks via birth control through

1. abstinence from sex outside marriage

2. later age at marriage

Front 287

What major period of time allowed for transition from linear to exponential growth of subsistence?

Back 287

Industrial revolution.

Front 288

Demographic transition framework

Back 288

demographic transition framework illustrates population growth in terms of discrepancies and changes in 2 crude vital rates: mortality and fertility (it ignores migration)

Front 289

reasons for measuring health and ill-health:

Back 289

- disease/injury prevention
- health promotion
- health services planning
- program evaluation

Front 290

crude death rate (CDR):

Back 290

CDR = (number of deaths/midyear population) x 100,000

Front 291

crude birth rate (CBR):

Back 291

CBR = (number of births/midyear population) x 100,000

Front 292

Demographers typically express rates per ______

Epidemiologists typically express rates per _____

Back 292

Demographers: rates/1,000

Epidemiologists: rates/100,000

Front 293

What is true when we compare Crude Birth Rate and Crude Death Rate?

Back 293

the CBR is more “crude” than the CDR because we are all at risk of dying but we are not all at risk of giving birth

Front 294

Demographic Transition

pretransition stage:

Back 294

pretransition stage: both birth and death rates are high but birth rate is constant while death rate fluctuates; sometimes there is a net increase, sometimes there is a net loss

Front 295

Demographic Transition

transition stage:

Back 295

- transition stage: mortality rate drops while there’s a lag in the drop of the birth rate so there are major discrepancies between the 2 (large rate of natural increase)- this is a population explosion

- developed countries have gotten through this stage and into the post-transition stage

Front 296

Demographic Transition

post-transition stage:

Back 296

post-transition stage: both birth and death rates are low but death rate is constant while birth rate fluctuates

- during this stage, perhaps human beings are in a better position to control their fertility

Front 297

What are the four "perspectives" on Demographic Transition?

Back 297

Description
Classification
Explanation
Prediction

Front 298

T/F Demographic Transition is poor at explaining and good at predicting

Back 298

True

Front 299

immigration:

Back 299

permanent moves in across natural boundaries

Front 300

emigration:

Back 300

permanent moves out across natural boundaries

Front 301

Brain Drain

Back 301

describes movement of educated people from less developed countries to more developed countries (like the US)

Front 302

T/F In the US immigration exceeds emigration

Back 302

True

Front 303

a great paradox: as mortality rates declined over time what happens to the proportion of younger and older people and why?

Back 303

as mortality rates declined over time, this made the population younger, not older because the big beneficiaries of the mortality decline are the young

Front 304

infant mortality rate =

Back 304

infant mortality rate = # of infant deaths/# of live births

Front 305

Describe family size in a transitional stage such as the Victorian Era.

Back 305

- large families were characteristic of Victorian England not because the culture was concerned with having large families but because it was a transitional stage: kids were being born and surviving unexpectedly (the people were used to 50% or more of children dying before the age of 8 which is what happened in the pretransitional stage)

Front 306

Describe family size in a pretransitional stage.

Back 306

pretransitional stage did not have large families (had many children but died in childhood)

Front 307

Why was the female infant mortality rate much greater than the male infant mortality great in India (year 2000)?

Back 307

There is a strong preference for male infants -

female infant neglect > male infant neglect

Front 308

What are the two ways that age-pyramids can be graphed?

Back 308

1. in absolute numerical terms
2. in percentage distribution (better because gives comparability across time and space)

Front 309

Age Pyramids

What are we comparing?

Back 309

1. variation across age groups
2. variations within age group by sex

Front 310

Describe the shape of an age pyramid for less developed regions.

Back 310

pyramid for less developed regions have a wide base which means high fertility rate so high rate of population growth

Front 311

Describe the shape of an age pyramid for more developed regions

Back 311

more developed regions have a narrow base which means low fertility

Front 312

Age pyramids are a cross section of data from 1 year and as a result they count _______

Back 312

immigrants

Front 313

Bumps in a pyramid can reflect what?

Back 313

Wars can reduce male populations

Bias. such as immigrations of males into the United Arab Emirates

Front 314

What were the major causes of the death in the early 1900's?

Back 314

communicable, infectious diseases

Front 315

What are the major causes of death today?

Back 315

Chronic diseases

Front 316

T/F Life expectancies have increased in most parts of the world

Back 316

True

Front 317

What are the four stages of the epidemiological transition?

Back 317

1.) Pestilence and Famine

2.) Receding Pandemics

3.) Degenerative and Man-Made Diseases

4.) Delayed Degenerative Diseases and Emerging Infections (Hybristic)

(see page 46 of Allison's SG for diagram)

Front 318

What were some of Thomas McKeown's conclusions about the population explosion?

Back 318

modern medicine had little to do with decrease in mortality rates

showed that decreased death rate trends preceded effective therapies

the industrial revolution and increased affluence (not clinical medicine) were responsible for rising life expectancies

Front 319

Life expectancy is calculated on basis of ____________ but has long-term implications

Back 319

Cross-sectional data

Front 320

Public health measures developed in the West have been more important in bringing about decline in mortality rates in _________

Back 320

Developing Countries

Front 321

What is the goal of public health in terms of the appearance of the graph of survival?

Back 321

We want the graph to be as rectangular as possible

Front 322

Life expectancy refers just to _______

We'd preferably want to ________.

Back 322

quantity of life

maximize quality of life (compression of morbidity)

Front 323

Who developed DALY? What is DALY?

Back 323

Murray and Lopez

Disability Adjusted Life Years which incorporate mortality (quantity of life concerns) and morbidity and other quality of life concerns

Front 324

Study interpretation: Describe the decision tree that leads from Association to Causal relationship

Back 324

Association present ->Chance absent-> Hypothesis formed beforehand -> no bias -> no confounding -> fits causal criteria -> Causal relationship

Front 325

In the decision tree that leads from Association to Causal relationship,

What probably occurred if chance was present? What can we do?

Back 325

There is not a statistical significance.
Type II error

We need to consider whether the sample size was sufficient.

Front 326

In the decision tree that leads from Association to Causal relationship,

What happens if a hypothesis was not specified first?

Back 326

Hypothesis generating

Study/cluster

Front 327

What do you need to consider when you are interpreting a "Positive study"?

Back 327

Chance - Random Variability

Is the effect real?

Data Dredging

Hypothesis testing

Front 328

What do you need to consider when you are interpreting a "Negative study"?

Back 328

The possibility of:

Random variability, which could have obscured a real association.

This relates to sample size and statistical power

Front 329

The number of the sample size, n is determined by:

Back 329

Magnitude of effect

Proportion of population exposed for case-control studies, or developing the outcome for cohort studies / clinical trials

Front 330

Error questions:

Ho is True
Accept Ho

Back 330

Correct

Front 331

Error questions:

Ho is True
Reject Ho

Back 331

Type I error

Reflected in p value
cutoff is denoted as alpha

Front 332

Error questions

Ho is False
Reject Ho

Back 332

Correct

Power = 1-B

Front 333

Error questions

Ho is false
Accept Ho

Back 333

Type II error.

Front 334

T/F Increasing Type I error decreases Type II error and vice versa

Back 334

True

Front 335

When do we look at Type I and Type II errors?

Back 335

Type I errors: After the study

Type II errors: Before study
- this is related to the power!

Front 336

What is true about most negative studies that are published in the literature?

Back 336

They are underpowered

Front 337

Key question is:
How big a sample do I need so that if my study is negative, I know I’m not missing anything?

Back 337

This is the statistical power of a study

Front 338

What is RR or OR are considered "small effects"

Is it easy to detect small effects?

Back 338

It is harder to detect small effects (RR or OR < 1.5)

Front 339

Why should we be wary of studies reporting small effects?

Back 339

Studies reporting small effects may easily have arisen because of chance, bias, confounding

Front 340

Exposure is difficult to determine and can limit epidemiological efforts. What are two examples of this?

Back 340

EMF, Cancer

Front 341

What are two methods to increase statistical power?

Back 341

precise classification of disease and exposure status (minimize random misclassification)

adequate follow-up in cohort studies and clinical trials

Front 342

Adequate follow up?

97%

Back 342

yes

according to Sackett
> 95% : no worries

Front 343

Adequate follow up?

87%

Back 343

maybe

according to Sackett
>80: gray zone

Front 344

Adequate follow up?

75%

Back 344

no

according to Sackett
<80: No

Front 345

Prospective cohort study looking at mortality in 100 patients with 84% follow-up reported 4 deaths

Is this adequate?

Back 345

NO

4 die, 16 lost to follow-up

Reported mortality is 4/84 = 4.8%

If all those lost to follow-up had died,
worst case mortality: 20/100 = 20%

If all those lost to follow-up had lived,
best case mortality: 4/100 = 4%

Front 346

Types of Bias

Two Broad Types

Back 346

Selection and Information Bias

Front 347

Selection Bias

Three types

Back 347

The Healthy Worker Effect
Volunteer bias
Berkson’s bias

Front 348

The Healthy Worker Effect

What type of bias? Description?

Inventor?

Back 348

Selection bias

Worker population may not represent the general population. May be healthier

Anthony McMichael.

Front 349

Volunteer Bias

Type of bias? Description?

Back 349

Selection Bias

People who agree to be in a study are different than those in general population

Front 350

Berkson’s Bias

Type? Description.

Back 350

Patients getting care (clinics, hospitals, etc) are systematically different from patients in general populations

Front 351

Patients with co-morbid conditions are more likely to seek treatment than those with only disease

What kind of bias is shown here? What was the example given in class?

Back 351

Berkson's bias

Eating disorders and substance abuse together are more likely to be reported by family members than either one condition alone

Front 352

Information Bias

Back 352

Any error in how information is gathered about exposure and/or disease

Front 353

What are the types of Information Bias?

Back 353

1. Recall bias
2. Interviewer / Measurement / Expectancy / Systematic or Differential misclassification bias
4. Loss to follow-up
5. Expectancy bias
6. Proficiency bias
7. Neyman bias

Front 354

Neyman bias

What type of bias? Describe.

Back 354

Errors is WHEN we collect data

Length bias will be discussed under Screening

Look back bias

If we look at point prevalence, those individuals who had a short duration of disease will be underrepresented

Front 355

Neyman Bias is also known as ________

Back 355

prevalence-incidence bias

Front 356

What two types of studies are particularly prone to Loss to Follow-up bias?

Back 356

cohort and intervention studies

Front 357

What are ways we can control/limit bias in our studies?

Back 357

Must rely on study design

Prospective studies generally superior

Choice of controls in case-control study

Rigorous, standardized assessment methods

Use of blinding

Follow-up

Front 358

T/F Prospective studies are generally superior in limiting bias than the other types of studies.

Back 358

True

Front 359

In a study of prophylactic administration of isoniazid, tuberculin-positive school children were randomly assigned to drug or placebo treatment groups. A third group, consisting of those who elected not to enroll in the study, was also observed. After several years, the third group had a significantly higher rate of tuberculosis than the placebo group.

What kind of bias is shown here?

Back 359

Volunteer bias (type of selection bias)

Front 360

T/F A confounder can be complex and either known or unknown

Back 360

True

Front 361

What can we do if we know what the confounder is?

Back 361

If known, can be measured and statistically controlled

Front 362

What is Simpson's Paradox, and what can it determine for us in terms of a variable?

Back 362

If an apparent effect disappears after controlling for variable, it is a confounder

Front 363

Methods to Control Confounding

Back 363

Restriction
Randomization
Stratification
Multivariate analysis
Matching

Front 364

Methods to Control Confounding

Restriction

Back 364

Only study people who are homogenous with respect to a known confounder

Front 365

Methods to Control Confounding

Early heart studies were primarily focused on men, what kind of confounding reduction method is being employed?

Back 365

Restriction

Front 366

Methods to Control Confounding

Stratification: Examples

Back 366

Indirect, direct, SMR

Mantel Haenszel stratification

Chi square, RR for cohort

Front 367

Mantel Haenszel stratification

Back 367

Can calculate weighted average as OR or RR to obtain summary unconfounded risk estimate

Also works for Chi square

Front 368

Stratification can only be done on a _____ number of factors

Back 368

limited

Front 369

Multivariate analysis

Describe it. Pros? Cons?

Back 369

Computer based
Develop a model to explain data

Pros: Linear or logistic regression of multiple variables

Cons: Not good for complex relationships

Front 370

What is the effect of matching on a confounder?

Back 370

Match by using same status for potential confounder so effect “cancels out”

Front 371

In which kind of study can individuals be matched to themselves?

Back 371

Cross-over study

Front 372

Influences on study results

Hawthorne Effect

Back 372

Production of workers improved solely because they knew they were being observed

May account for false positive results

Front 373

Prosecutor’s Fallacy

Back 373

1/50,000 that DNA sample taken from innocent person matches DNA at the crime seen

3/4 that person that has DNA that matches the DNA at crime scene is innocent.

Front 374

Gambler’s Fallacy

Back 374

A random event is more likely to occur because it has not happened for a period of time

Front 375

Regression to the Mean

What is can happen when you take a test and your find out your score (relative to the True score that you really deserve...)

Back 375

Be unlucky and score below your ‘true’ grade

Score exactly at your ‘true’ grade

Be lucky and score above your ‘true’ grade

Front 376

Ockham’s Razor

Back 376

"Entities should not be multiplied beyond necessity.”

in other words, the simplest explanations are preferred

Front 377

Validity (aka internal validity)

Back 377

= is it a good study?

Front 378

Generalizability (aka external validity)

Back 378

= does the study mean anything for the patient before me?

Front 379

T/F Generalizability is more important than validity.

Back 379

FALSE.

Validity is more important. It has to be a good study before you can generalize the findings to the general population

Front 380

What factors can threaten generalizability?

Back 380

Volunteer bias

Restriction

Invasive intervention studies usually performed on advanced cases

Studies usually performed in academic settings

Compliance

Efficacy (ideal) versus effectiveness (real world)