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Ash's Certification Study > Surveillance and Epi Investigation > Flashcards

Surveillance and Epi Investigation Flashcards

1
Q

Basic stat measures for descriptive stats

A

Measures of frequency
Measures of central tendency
Measures central dispersion
Percentiles

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2
Q

What are the measures of frequency

A

Ratio
Rates
Proportions

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3
Q

Relationship between two groups, offers insights into proportion and connections inherent within the data

A

Ratio

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4
Q

Occurrence of particular event within specified population during defined period, facilitate comparisons and trend assessments across different populations and time intervals

A

Rate

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5
Q

Relative magnitude of a specific category or event within a larger context. Show distribution and relevance if events within a dataset

A

Proportion

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6
Q

Percentage of people in population who have a specific condition at a particular moment

A

Prevalence

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7
Q

How many new cases of a particular condition occur within a population during a set period of time

A

Incidence

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8
Q

Number of deaths that happen within a population during a specific period of time

A

Mortality rate

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9
Q

Percentage of people who were exposed to a risk factor and ended up developing the condition

A

Attack rate

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10
Q

Average of the values in a data srt

A

Mean

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11
Q

Middle value in a ranked data set

A

Median

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12
Q

Mode

A

Value that appears most freq in a dataset

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13
Q

Which measure of central tendency is impacted by outliers?

A

Mean

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14
Q

Span between the smallest and largest value within a data set

A

Range

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15
Q

Average square difference between each data point and the mean. It provides a comprehensive understanding of how individual values vary from the data set Central value

A

Variance

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16
Q

Difference between an individual data point and the mean of the data set. It gives us a sense of how much each value deviates from the average

A

Deviation

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17
Q

Distribution and values around the mean. It quantifies the extent to which data points deviate from the central value helping us gauge overall variability.

A

Standard deviation

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18
Q

Set of methods that can be used for improving systems, processes, and outcomes

A

Statistical process control

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19
Q

Variation that is inherent to the system

A

Common cause variation

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20
Q

Variation that is indicative of exceptional events or changes

A

Special cause variation

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21
Q

Best process control chart for less than 25 points

A

Run chart

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22
Q

Best chart for 25-50 points

A

Control chart

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23
Q

Evaluates whether differences observed in data are significant and not due to chance

A

Hypothesis testing

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24
Q

Provide range within which population parameters are likely to exist

A

Confidence intervals

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25
Q

Unveiled relationships between variables and forecast outcomes

A

Regression analysis

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26
Q

Compares means across multiple groups helping us discern more meaningful distinctions

A

Anova

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27
Q

What are the two types of hypotheses used in statistical testing?

A

H0- null hypothesis- there is no association or difference between groups or relationship between variables

Ha- alternative hypothesis- there is a difference between groups or relationship between two variables

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28
Q

Describe the one sample test

A

Compare a sample mean to a known population parameter

Determines if the sample mean is significantly different from the population mean

Used when analyzing a single groups data

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29
Q

Describe the two sample t-tests

A

Compares means between two independent groups

Independent samples t-test is an example

Determines if it means of the two groups are significantly different

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30
Q

What are the two types of t-test

A

Dependent samples t-test
Independent samples t test

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31
Q

Describe the dependent samples t test

A

It compares means of related pairs of data

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32
Q

Describe independent samples t-test

A

Compares means between two independent groups

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33
Q

Describe chi-square test

A

-Used for categorical data
- Test for association or Independence between categorical variables
- Compare observed and expected frequencies

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34
Q

When should you reject the null hypothesis

A

When the p-value is less than alpha. The alpha is reset by the researcher and is typically 0.05 or 0.01. the p-value is calculated from the data

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35
Q

Type 1 error

A

False positive

-Occurs when the null hypothesis is wrongly rejected
- Concluding an effect exist when it doesn’t
- controlled by setting the significance level alpha before the test
- results in a p-value below alpha leading to the rejection of a true null hypothesis

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36
Q

Type 2 error or beta

A

False negative

  • occurs when the null hypothesis is wrongly accepted
  • failing to detect a true effect that exists
  • controlled by sample size, affect size, and variability
  • and results in a p-value above alpha leading to the acceptance of a false null hypothesis
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37
Q

Confidence interval

A

Range of values within which the true population parameter is likely it’s a lie

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38
Q

Offer insight into the precision and reliability of an estimate

A

Confidence intervals

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39
Q

If the confidence interval includes the null value the result is..

A

Not statistically significant

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40
Q

If the confidence interval excludes the null value the result is..

A

Statistically significant

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41
Q

What does a wider confidence interval suggest

A

Higher uncertainty and less precise estimates

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42
Q

What does a narrower confidence interval suggest

A

Greater precision and higher confidence in the estimate

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43
Q

Describe regression analysis

A

Statistical technique used to model the relationship between one or more independent variables and a dependent variable

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44
Q

Linear regression

A

Models linear relationship between independent and dependent variables

Used when the relationship appears to be a straight line

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45
Q

Multiple regression analysis

A

Incorporates more than one independent variable

Accounts for multiple factors influencing the dependent variable

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46
Q

Logistic regression

A

Used when the dependent variable is binary with two possible outcomes

Models the probability of an event occurring

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47
Q

Analysis of variance (ANOVA)

A

Statistical technique used to compare means across multiple groups

Assesses whether there are statistically significant differences in means among different categories

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48
Q

What are the types of anova tests?

A

One Way anova and two-way anova

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49
Q

One Way anova

A

Compares means among three or more independent groups

Determines if there is a significant difference between at least one pair of groups

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50
Q

Two-way anova

A

Analyzes the effect of two independent variables on a dependent variable

Unveils interactions between the variables and their combined effects

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51
Q

Systemic and ongoing collection, analysis, interpretation, and dissemination of data on the occurrence and distribution of health related events in a population

A

Surveillance

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52
Q

Diseases, injuries, behaviors, or health-related indicators to identify patterns, trends, or changes within a population

A

Health related events (outcomes

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53
Q

Healthcare workers, patients, visitors, or specific at risk groups

A

Population

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54
Q

Surveillance can be used to improve..

A

Performance, patient safety, and infection prevention

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55
Q

Types of surveillance methodologies

A

Total house surveillance and targeted surveillance

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56
Q

Comprehensive monitoring of all health Care associated infections across the entire population of a healthcare facility. Provides broad and inclusive perspective enabling the identification and potential risk and patterns on a facility-wide scale.

A

Total house surveillance

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57
Q

Surveillance that narrows its focus to a specific care unit and heis. By concentrating on specific areas where risk may be higher or wear specific interventions are needed, this methodology allows for more precise assessments. This approach is especially valuable when allocating resources efficiently and addressing particular concerns.

A

Targeted surveillance

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58
Q

Measure that accurately captures and represents the specific concept of construct it is intended to measure

A

Valid

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59
Q

Measurement produced same results when used repeatedly under consistent conditions

A

Reliable

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60
Q

Unusual aggregation, real or perceived, if health events that are grouped together in time and space

A

Cluster

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61
Q

Increase in disease among specific population in geographic area during a specific period of time

A

Outbreak

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62
Q

Cluster of positive microbiological results without actual clinical illness

A

Pseudo-outbreak

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63
Q

Study of distribution and determinants of health related states among specified populations

A

Epidemiology

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64
Q

Difference between surveillance and epidemiology

A

Surveillance - continuous monitoring of specific health events and conditions

Epidemiology- studies the causes, distribution, and determinants of health and disease in populations

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65
Q

Goals of infectious disease epi

A
  1. Prevention, control, and intervention strategies
  2. Hypotheses
  3. Associations between risk factors and disease
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66
Q

Parts of the epi triangle

A

Host, agent, env

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67
Q

Epi models

A

Triangle model
Wheel model
Web of causation
Chain of infection

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68
Q

Statistical relationship between a risk factor and a disease, two variables tend to occur together more often than would be expected by chance

A

Associaition

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69
Q

Cause and effect relationship between risk factor and diisease

A

Causation

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70
Q

Reasons for association

A
  1. Artifactual (spurious)
  2. Indirect (noncausal)
  3. Causal
71
Q

What causes artifactual associations?

A

Random error
Bias

72
Q

Chance influences presence of association between variables, with larger number of variables studies, likelihood of chance association increases

A

Random error

73
Q

Steps from errors in study design, data collection, or analysis

A

Bias

74
Q

What type of artifactual associations can be controlled?

A

Bias

75
Q

Associations that arise from interplay of multiple factors within an epi study

A

Indirect associations

76
Q

External fator related to exposure and outcome, creating a false appearance of association between the two

A

Confounding factor

77
Q

Ways to prevent confounders

A

Study design, statistical technique, and controlled experiment

78
Q

Describe Koch’s postulates

A
  1. Organism must always be found with disease
  2. Isolated and grown in pure culture
  3. Same disease reproduced when inoculated with organism grown in pure culture into healthy host
  4. Organism recovered from experimentally infected host
79
Q

What are Hill’s criteria of causation

A

Strength
Temporality
Analogy
Consistency
Plausibility
Coherence
Specificity
Biological gradient
Environmental evidence

80
Q

Incidence of the disease should be higher in those who are exposed to the factor under consideration than those who are not exposed

A

Strength of association

81
Q

The association should be observed in the numerous studies preferably by different researchers using different research methodologies

A

Consistency

82
Q

The association between one factor and one disease is more likely to be causal

A

Specificity

83
Q

Exposure to the hypothesized causal Factor must proceed onset of disease

A

Temporality

84
Q

A dose response relationship between increased exposure to a factor and increase likelihood of disease

A

Biological gradient

85
Q

Plausible considering current knowledge

A

Biological plausibility

86
Q

The association must be in accordance with other facts known about the natural history of the disease

A

Coherence

87
Q

Adds considerable weight to the evidence supporting causal associations. These experiments can be animal studies or clinical trials

A

Experimental knowledge

88
Q

It’s similar associations have been shown to be causal, the association is more likely to be causal

A

Analogy

89
Q

Chain of infection

A

Causative agent
Reservoir
Portal of exit
Mode of transmission
Portal of entry
Susceptible host

90
Q

Biological, physical, or chemical agent capable of causing disease

A

Causative agent

91
Q

Examples of causative agents

A

Bacteria, viruses, fungi, protozoa, and prions

92
Q

Place where infectious agent can survive but may or may not multiply

A

Reservoir

93
Q

Examples of reservoirs

A

Humans, animals, and the environment

94
Q

The path by which an infectious agent leaves the reservoir

A

Portal of exit

95
Q

Examples of the portal of exit

A

Respiratory tract, gastrointestinal tract, blood, skin and mucous membranes

96
Q

Method by which the organism reaches acceptable host

A

Mode of transmission

97
Q

Examples of modes of transmission

A

Droplet, airborne, vectors, contact

98
Q

The path by which an infectious agent enters the host

A

Portal of entry

99
Q

Examples of portal of entry

A

Respiratory tract, gastrointestinal tract, blood, skin / mucus membrane

100
Q

Host has variable that modifies the risk of becoming infected and developing disease

A

Susceptible host

101
Q

Examples of susceptible hosts

A

Humans and animals

102
Q

Complete prevention of a disease before any manifestation of that disease occurs

A

Primary prevention

103
Q

Examples of primary prevention

A

Vaccination and HIV prep

104
Q

Early diagnosis and treatment

A

Secondary prevention

105
Q

Examples of secondary prevention

A

TB skin testing

106
Q

Deals with sequelae of disease, occurs after the disease as well established

A

Tertiary prevention

107
Q

Example of tertiary prevention

A

Rehab for polio

108
Q

When to implement primary prevention

A

Before exposure and preclinical stage

109
Q

When to implement secondary prevention

A

Clinical stage

110
Q

Went to implement tertiary prevention

A

Resolution stage which is either a problem resolved, return to health, chronic stage, or death

111
Q

Correlation coefficient:
Interpretation of R

A

R= -1 perfect negative relationship
R= 0 no relationship
R= 1 perfect positive relationship

112
Q

Risk of an event occurring in an exposed group to the risk of it occurring in an unexposed group

A

Relative risk

113
Q

Calculation for relative risk

A

(number of cases in the exposed group/ total number in the exposed group) ÷ (number of cases in the unexposed group / total number in the unexposed group)

114
Q

How to interpret relative risk

A

RR <1 risk of outcome was higher in the group without exposure. the risk factor and the disease are negatively associated. it appears to be a protective Factor

RR=1 risk of outcome was the same for both groups. There is no association found between the risk factor and the outcome.

RR >1 risk of outcome was higher in the group with exposure to the risk factor. The risk factor and the outcome are positively associated

115
Q

How to interpret OR

A

OR<1: the odds ratio of exposure are higher among the controls, individuals with the outcome are less likely to have been exposed to the risk factor

OR=1: the odds of exposure are the same for both groups, no association was found between the outcome and having been exposed to the risk factor

OR>1: the odds of exposure are higher among the cases individuals with the outcome are more likely to have been exposed to the risk factor

116
Q

If someone has the outcome what is the likelihood the test will be positive?

A

Sensitivity

117
Q

Equation for sensitivity

A

Number of true positive results / by number of individuals with the outcome * 100

118
Q

If someone does not have the outcome what is the likelihood that the test will be negative

A

Specificity

119
Q

What is the equation for specificity?

A

Number of true negative results / number of individuals without the outcome * 100

120
Q

If the test result is positive what is the likelihood that the person truly has the outcome?

A

Positive predictive value

121
Q

If the test result is negative what is the likelihood that the person truly does not have the outcome?

A

Negative predictive value

122
Q

What is the equation for positive predictive value

A

Number of true positive results ÷ number of individuals with positive test s * 100

123
Q

What is the equation for negative predictive value

A

Number of true negative results / number of individuals with negative results * 100

124
Q

What is the relationship between sensitivity and specificity?

A

Inverse relationship, as one increases, the other decreases

125
Q

What happens to false negatives, NPV and specificity when sensitivity increase

A

Decreases false negatives
Increases NPV
Decreases specificity

126
Q

What happens to false positives, PPV and sensitivity when specificity increases

A

Decreases false positives
Increases PPV
Decreases sensitivity

127
Q

When prevalence of the disease is low it results in a ____ NPV

A

Higher

128
Q

When prevalence of a disease is high, it results in a ____ PPV

A

Higher

129
Q

Describe qualitative studies

A
  • Explore social, behavioral, and contextual factors impacting health in a population

-enhanced epidemiology by uncovering nuanced health insights

130
Q

Examples of contextual factors that impact health in a population

A

Susceptibility to illness
Severity of illness
Cost of carrying out behavior
Perceived threat
Cues to action
Health motivation
Perceived control

131
Q

What are the four types of qualitative studies?

A

Narrative
Phenomenology
Grounded theory
Ethnography

132
Q

Complex account of an individual’s experience in the context of their social cultural and even institutional environments

A

Narrative

133
Q

Biographical, autoethnographical, life history, or oral history methods can be applied to this type of qualitative study

A

Narrative

134
Q

This type of study gathers experiences to identify shared meanings of a phenomenon

A

Phenomenology

135
Q

This type of study aims for universal themes rather than individual uniqueness and reduces diverse experiences to a fundamental phenomenon

A

Phenomenology

136
Q

Example of narrative study

A

Interviewing nurse and documenting her experiences after contracting Ebola during the Ebola epidemic

137
Q

Examples of phenomenology

A

Desceibe patient experiences with surgical site infections

discerning patient preferences for bed baths

138
Q

This type of study creates new theories and concepts based on participants experiences of process

A

Grounded theory

139
Q

Unlike other qualitative approaches it doesn’t just describe but aims to explain a process

A

Grounded theory

140
Q

Process for grounded theory

A

Interview and then look through interviews to identify common themes

141
Q

Example of grounded theory

A

Healthcare workers compliance with hand hygiene- complete interviews and observations identify themes to identify contextua factors like social norms and perceived barriers

142
Q

This type of study aims to understand human behavior is and their meanings within specific cultures or subcultures

A

Ethnography

143
Q

This type of study involves participant observation, interviews, field notes, and archival data to provide detail descriptions of daily experiences in a culture

A

Ethnography

144
Q

Example of ethnographic study

A

Researcher immerses themselves within a nursing home to understand the experiences and behaviors of patients placed under isolation precautions due to contagious infections. They are able to observe interactions and engage with patients which helps them to gain insight into the lived realities of those navigating isolation protocols

145
Q

Two types of quantitative studies

A

Observational and experimental clinical trials

146
Q

In this study the investigator observes the exposure and disease status of the population

A

Observational study

147
Q

In this study the investigator determines the exposure for the population

A

Experimental clinical trial

148
Q

What are the two types of observational studies?

A

Descriptive and analytical

149
Q

This type of observational study describes data and basic quantitative terms

A

Descriptive study

150
Q

This type of observational study compares individuals with and without an outcome by the presence of one or more hypothesized risk factors

A

Analytical study

151
Q

What are the types of descriptive studies?

A

Case reports and case series

152
Q

What are the types of analytical studies?

A

Cross-sectional
Case control
Cohort

153
Q

Detailed description of an individual patient’s medical condition, symptoms, diagnosis, treatment, and outcomes

A

Case report

154
Q

This type of descriptive study is used for rare or unusual medical cases

A

Case report

155
Q

This type of descriptive study is typically written by healthcare professionals such as physicians, nurses, are medical researchers

A

Case report

156
Q

This type of descriptive study is a detailed analysis and description of a group of patients who share similar characteristics or have experienced a similar medical condition or event

A

Case series

157
Q

In this type of analytical study the exposure and outcome are collected from a population simultaneously. The study is done at a specific point in time providing snapshot of the population.

A

Cross-sectional study

158
Q

What is the purpose of cross-sectional studies?

A

To find prevalence and generate hypotheses

159
Q

What are the advantages and disadvantages of the cross-sectional study

A

Advantages- quick, inexpensive
Disadvantages- can only calculate prevalence not incidence, and temporal sequence cannot be determined

160
Q

This type of analytical study compares individuals with an outcome to individuals without the outcome.

A

Case control

161
Q

Is a case control study retrospective or prospective

A

Retrospective

162
Q

What can be calculated from case control studies?

A

Odds ratio

163
Q

What are the advantages of case control studies?

A
  • data already available
  • require relatively small number of subjects
  • useful for rare diseases
  • less expensive than cohort studies
  • require less time
164
Q

What are the disadvantages of case control studies?

A
  • dependent on completeness of records
  • difficult to select appropriate control group
  • subject to recall bias
165
Q

This type of study follows a group of individuals over a period of time. participants are classified into two groups based on their exposure status. These groups are then followed forward in time to determine if the outcome occurs.

A

Cohort study

166
Q

What can be calculated from a cohort study?

A

Relative risk

167
Q

What are the advantages of a cohort study

A

Typically less biased
Exposure precedes disease
Calculates incidence of disease
Carries more weight than case control

168
Q

What are the disadvantages of a cohort study

A

More expensive
Lengthy follow up
Lost a follow-up

169
Q

These studies are used to evaluate effectiveness of an intervention or treatment. Participants are randomly assigned to one of two or more groups. The treatment and control group that receives a placebo or standard treatment.

A

Experimental randomized control trial

170
Q

Advantages of randomized control trials

A

Design minimizes bias
Best evidence for direct causal relationship between factor and outcome

171
Q

Disadvantage of randomized controlled trial

A

Demanding
Expensive
Generalization is difficult

172
Q

This type of study is used to identify, collect, analyze, and summarize evidence related to a specific research question

A

Systematic review

173
Q

This type of study identifies gaps in research

A

Systematic review

174
Q

What is the hierarchy of epidemiological study designs?

A

Cross-sectional
Case control
Cohort
Randomized control trial
Minute analysis of randomized control trials

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