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Applications of Epidemiology in Communities
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 communityevaluate health servicesestimate individual risk from group
experience
Uses of epidemiology (con’t)
Identify syndromescomplete the clinical picture so that
prevention can be accomplished before disease is irreversible
search for cause
Epidemiologic investigations focus on:
Infectious diseaseNon-infectious chronic conditionsAcute eventsEmotional/Mental Health conditionsNormal characteristics of populations
2 Models to describe the factors necessary to make an epidemiologic event happen
Web of CausationEcological (or
epidemiologic) Model
Example of a Web of Causation
Susceptible Host Infection Tuberculosis
Vaccination Genetic
Overcrowding Malnutrition
Tissue Invasion and Reaction
Exposure to Mycobacterium
Agent:Amount, infectivity, pathogenicity, virulence, chemical composition,
cell reproduction
Environment:Physical, biological, social
Host:Intrinsic factors, physical factors, psychological factors, immunity
Health
or
Illness
?
Examples of Agents of Disease
Nutritive excesses or deficiencies (Cholesterol, vitamins, proteins)
Chemical agents (carbon monoxide, drugs, ragweed, medications)
Physical agents (Ionizing radiationInfectious agents (hookworm, amoebae,
malaria, tuberculosis, syphilis, histoplasmosis, polio, rabies, mumps)
Examples of Host Factors
Genetic (Sickle cell disease)AgeGenderEthnic groupPhysiologic state (fatigue, pregnancy, puberty)Prior immunologic experience (maternal antibodies,
immunization, prior infection) Intercurrent or preexisting diseaseHuman behavior (Food handling, diet, hygient,
recreation, use of resources)
Examples of Environmental Factors
Physical environment (geology, climateBiologic 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
Individual Aggregate
Curative
Preventive
Basic Nursing Community Health Nursing/Public Health
Medicine Epidemiology
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
Primary Prevention
Secondary Prevention
Tertiary Prevention
Pre-exposure Stage:
Factors present leading to problem development
Preclinical Stage:
Exposure to causative agent: no symptoms present
Clinical Stage:
Symptoms present
Resolution Stage:
Problem resolved. Returned to health or chronic state or death
Exposure to AgentSymptom Development
Epidemiologic Control Measures
Rapid identification of isolated disease outbreaks
Notification to local health authority Local District or state National WHO
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)
Relative Risk
0 7
1 26
2-3 48
4+ 40
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
MorbidityMortalityEpidemicEndemicPandemic
RatesAllows comparison
between populationsFrequency in numeratorComparison population
in denominatorX/Y x KUsually 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-adjustedRace-adjustedGender-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
SensitivitySpecificityPositive and Negative Predictive Values
The Ideal Screening TestNormal 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 Disease Present Disease Absent
Positive Result AA(True positives)
B B (False positives)
Negative Result CC(False Negatives)
DD(True negatives)
Totals A+CA+C B+DB+D
Application of Sensitivity & SpecificityBlood 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)(False positives)
All under 110mg/100 ml are classified as
non-diabetics (False Negatives) (True negatives)
Totals 100.0 100.0
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
PrevalenceFinancialAvailability/
Feasibility of Treatment
Relative costs of classifying persons as FN and FP