Transcript The Community as Client - Kimberly Ferren Carter

Applications of Epidemiology in
Rural and Urban Communities
NURS 633
Kimberly Carter PhD, RN
Fall 2000
Epidemiology
The study of the
distribution of health
and of the
determinants of
deviations from health
in populations
Purpose of Epidemiology
To obtain necessary data to prevent and
control disease through Community Health
Intervention
Epi - “on or upon”
Demos - “the people”
Logos - “Knowledge”
Uses of epidemiology
 study effects of disease states in populations
over time and predict future health needs
 diagnose the health of the community
 evaluate health services
 estimate individual risk from group
experience
Uses of epidemiology (con’t)
 Identify syndromes
 complete the clinical picture so that
prevention can be accomplished before
disease is irreversible
 search for cause
Epidemiologic investigations
focus on:
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Infectious disease
Non-infectious chronic conditions
Acute events
Emotional/Mental Health conditions
Normal characteristics of populations
2 Models to describe the factors
necessary to make an
epidemiologic event happen
 Web of Causation
 Ecological (or
epidemiologic) Model
Example of a Web of Causation
Overcrowding
Malnutrition
Exposure to
Mycobacterium
Susceptible Host
Infection
Tuberculosis
Tissue Invasion
and Reaction
Vaccination
Genetic
Host:
Intrinsic factors, physical factors,
psychological factors, immunity
Health
or
Illness
?
Agent:
Amount, infectivity, pathogenicity,
virulence, chemical composition,
cell reproduction
Environment:
Physical, biological, social
Examples of Agents of Disease
 Nutritive excesses or deficiencies
(Cholesterol, vitamins, proteins)
 Chemical agents (carbon monoxide, drugs,
ragweed, medications)
 Physical agents (Ionizing radiation
 Infectious agents (hookworm, amoebae,
malaria, tuberculosis, syphilis,
histoplasmosis, polio, rabies, mumps)
Examples of Host Factors
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Genetic (Sickle cell disease)
Age
Gender
Ethnic group
Physiologic state (fatigue, pregnancy, puberty)
Prior immunologic experience (maternal
antibodies, immunization, prior infection)
 Intercurrent or preexisting disease
 Human behavior (Food handling, diet, hygient,
recreation, use of resources)
Examples of Environmental
Factors
 Physical environment (geology, climate
 Biologic environment (population density,
sources of food, influence of vertebrates and
arthropods
 Socioeconomic (exposure to chemical
agents, urban crowding, tensions/ pressures,
cooperative efforts in health education,
wars, floods
Epidemiology within the U.S.
Health Care System
Curative
Medicine
Epidemiology
Individual
Aggregate
Community Health
Nursing/Public Health
Basic Nursing
Preventive
Levels of Prevention
 Primary: Activities to decrease the
probability of specific illnesses or
dysfunctions No Disease Present
 Secondary: Early Diagnosis and prompt
intervention allowing early return to ADLs.
Disease has occurred
 Tertiary: A defect or disability is fixed,
stabilized or irreversible. Rehabilitation.
Disease has advanced
Natural History of Disease
The process by which
diseases occur and
progress in humans
Natural History of Disease
Exposure to Agent
Symptom
Development
Pre-exposure
Stage:
Factors present
leading to
problem
development
Preclinical
Stage:
Exposure to
causative
agent: no
symptoms
present
Primary
Prevention
Clinical
Stage:
Resolution
Stage:
Symptoms
present
Problem resolved.
Returned to health
or chronic state or
death
Secondary
Prevention
Tertiary
Prevention
Epidemiologic Control Measures
 Rapid identification of isolated disease
outbreaks
 Notification to local health authority
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Local
District or state
National
WHO
Role of CDCP
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Publish MMWR
Track diseases required by Federal law
Surveillance monitoring
Track noncommunicable disease
Relative Risk (Risk Ratio)
 The ratio of the risk of death among those
exposed to a factor to the risk among those
not exposed.
= Incidence of disease in exposed group
-------------------------------------------------Incidence of disease in nonexposed group
Calculating Relative Risk
Daily avg # drinks
Cirrhosis Cases
(per 1,000)
0
7
1
26
2-3
48
4+
40
Relative Risk
Attributable Risk
Attributable Risk: Rate of a disease among
exposed individuals that can be attributed to
the exposure and not to other causes
rate of outcome (incidence or mortality)
among exposed - rate among the unexposed
per K
Calculating Attributable Risk
Exposed Rate-Unexposed Rate
=
Basic Definitions
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Morbidity
Mortality
Epidemic
Endemic
Pandemic
Rates
 Allows comparison
between populations
 Frequency in numerator
 Comparison population
in denominator
 X/Y x K
 Usually per 1,000 or
100,000 (NOT %)
Incidence
# of new cases of disease in a place
from Time 1 to Time 2
___________________________________ x K
# of persons in a place at midpoint
of time period
Prevalence
# of existing cases in a place at a given time
_________________________________ x K
# of persons in a place at midpoint of year
Crude Mortality Rate
# of deaths during a year
___________________________
Average (midyear) population
/per 100,000 population
Cause-Specific Mortality Rate
# of deaths from a stated cause in a year
_______________________________
Average (midyear) population
/per 100,000 population
Age-specific mortality rate
# of deaths of a given age group in a year
____________________________________
Average (midyear) population of same group
/per 100,000
Standardized Mortality Rates
Adjusts for differences in populations so that
comparisons are interpretable.
 Age-adjusted
 Race-adjusted
 Gender-adjusted
Maternal Mortality Rate
# of maternal deaths during a year
__________________________________
# of live births in same year
per 100,000 live births
Infant Mortality Rate
# of deaths of children < 1 year during a year
__________________________________
# of live births in same year
per 100,000 live births
Crude Birth Rate
# of live births during year
_____________________________
Total midyear population
per 100,000
Case Fatality Percentage
# of deaths from specific disease
___________________________
# of cases
TIMES 100%
Interpreting Epidemiological
Information
 Indices of population change are fertility,
mortality, and migration
 Indices of overall health status are IMR and
MMR
 To plan for future health needs, look at age
distribution, “at-risk” groups, screening
protocols, treatment modalities, and referral
mechanisms
Screening Validity
 Sensitivity
 Specificity
 Positive and Negative Predictive Values
The Ideal Screening Test
Normal
Diabetic
Blood Glucose
Sensitivity
 Test’s ability to identify correctly those who
do have disease
 = True positives/All those with the disease
 = TP /TP + FN
Specificity
 Test’s ability to identify correctly those who
do not have disease
 = True negatives/All without the disease
 =TN/ TN + FP
Indices to evaluate accuracy of
Screen or diagnostic test
Test
Positive Result
Negative Result
Totals
Disease Present Disease Absent
A
B
(True positives)
(False positives)
C
D
(False Negatives)
(True negatives)
A+C
B+D
Application of Sensitivity & Specificity
Blood Glucose Level
(mg/100 ml) using
screening test
Actual diabetics; n=70)
Actual nondiabetics;
n=510)
80
90
100
110
100.0 (n=1)
98.6 (n=1)
97.1 (n=3)
92.9 (n = 3)
1.2 (n=6)
7.3 (n=31)
25.3 (n=91)
48.4 (n=116)
120
130
140
150
160
170
180
190
200
88.6 (n=4)
81.4 (n= 5)
74.3 (n=7)
64.3 (n= 6)
55.7 (n= 3)
52.9 (n=2)
50.0 (n=4)
44.3 (n=5)
37.1 (n=26)
68.2 (n=101)
82.4 (n=71)
91.2 (n=45)
96.1 (n=25)
98.6 (n=12)
99.6 (n=5)
99.8 (n=6)
99.8 (n=0)
100.0 (n=1)
Application (Continued)
Blood Glucose Level
(mg/100 ml)
True Diabetics (%)
True Nondiabetics
(%)
All over 110mg/100 ml
are classified as
diabetics
(True positives)
All under 110mg/100
ml are classified as
non-diabetics
(False Negatives)
(True negatives)
Totals
100.0
100.0
(False positives)
Application (Continued)
 Sensitivity =
 Specificity =
Predictive Values
 Determines relationship between sensitivity,
specificity, and prevalence
 When prevalence is low, even a highly
specific test will give a relatively large
number of false positives because of the
many nondiseased persons being tested.
Positive Predictive Value
 Likelihood that an individual with a positive
test has the disease
 TP/TP+FP
Negative Predictive Value
 Likelihood that an individual with a
negative test does not have the disease
 TN / TN + FN
Predictive Value of Diabetes
Application
 Positive Predictive Value =
 Negative Predictive Value =
Considerations for Selection of Screens
 Prevalence
 Financial
 Availability/
Feasibility of
Treatment
 Relative costs of
classifying persons as
FN and FP