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Transcript of epidemiology
Descriptive studies Person, Place, Time distribution Frequencies and patterns of health events within groups in a population applications Rate includes a dimension of time
how F A S T the disease is occurring in a population
person-time Proportion Incidence Rate when individuals are observed for different lengths of time Patient 1
Patient 10 Healthy Sick Healthy measures risk:
Numerator = No. of Non-diseased -> Diseased individuals
Denominator = Sum of (Time that each individual is observed) Person-year Over the past 7 years, a team of researchers observed the incidence of early childhood asthma, in a small neighbourhood, somewhere in Jurong.
indicates an incident of early childhood asthma;
The total person-time observed for all 10 patients was 24 person-years.
What was the incidence rate (person-years) of early childhood asthma in this cohort?
a) 3 / (24 person-years) = 0.125 per person-year
b) 0 / (24 person-years) = 0 per person-year
c) 10 / (24 person-years) = 0.417 per person-year
The incidence rate (proportion) in this cohort is: 3 person yrs 1 person yr 2 person yrs 3 person yrs 3 person yrs distribution Prevalence measures burden of disease:
"Snap-shot" at certain point in time
Numerator = No. of Diseased individuals (at specified time)
Denominator = No. of individuals in the population (at specified time) validity of diagnostic tests Sensitivity Specificity Measures ability of test to correctly detect
True positives (Diseased)
Numerator = True Positives (a)
Denominator = True Positives (a) + False Negatives (c)
(All diseased individuals) Measures ability of test to correctly detect
True negative (Non-diseased)
Numerator = True Negatives (d)
Denominator = True Negatives (d) + False Positives (b)
(All non-diseased individuals) Compared with a "Gold Standard" (Definitive) test Gold Standard + - New
Test + - Sensitivity = (80) / (80 + 20) X 100%
= 80% Specificity = (800) / (800 + 100) X 100%
= 89% Definitive test detected 100 Diabetics Definitive test detected 900 Non-Diabetics exercise The prevalence of gout in this population (n=1000) is 10%. This suggests that 100 individuals have Gout.
A new joint-fluid test is used to detect gout.
There were 70 True Positives, and 450 True Negatives. Gout Joint-fluid
Test What was the sensitivity and specificity of the new joint-fluid test? ROC curves Receiver Operator Characteristic An ROC curve is obtained by plotting sensitivity against false positive (1-specificity) for all possible cut-off points of the instrument.
Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. The area under the ROC curve (AUC) is a measure of how well a parameter can distinguish between two diagnostic groups (diseased/normal).
Therefore the closer the ROC curve is to the upper left corner, the higher the overall accuracy of the test (Zweig & Campbell, 1993). To determine optimal cutoff point for diagnostic screening tests: high sensitivity and high specificity The cutoffs showing the best equilibrium between sensitivity and specificity approached 5.6 and 5.0 mmol/1 for diabetes and IGT, respectively. predictive value given the test result sensitivity & specificity measures ability of the test to correctly detect Disease Diagnostic
test + - + - to determine whether or not patient has disease, true positives & true negatives Doctor: "Given this positive test result, what's the likelihood that this patient has the disease?" Lab: "What proportion of people who have the disease, would be correctly identified?" predictive value Prevalence and Predictive Value distribution exercise In a high prevalence setting, it is more likely that persons who test positive truly have disease, than if the test is performed in a population with low prevalence. Low prevalence (1%) In a population of 10,000 people, the prevalence of pertussis increases from 1 - 5%.
The sensitivity of a test for this disease is 99%; Specificity is 95%. Higher prevalence (5%) PPV increases summary therefore,
targeted screening on high-risk groups
(high prevalence) yields
higher positive predictive value conversely,
screening a relatively infrequent disease
(low prevalence) may yield
relatively fewer undetected cases resource management determinants Causes and factors that are associated with
increased risk or probability of disease Risk factors:
personal behavior or lifestyle (obesity, smoking)
an environmental exposure (haze, sun)
or a hereditary characteristic (breast cancer, parkinson's disease) interpreting medical literature with high PPV statements about high PPV may be misleading because studies are usually conducted in university hospitals, where prevalence is high (selection bias). Person: Age, gender, ethnicity Place: Countries, healthcare settings Time: Seasonal, outbreaks 2 person yrs 4 person yrs 3 person yrs 1 person yr 2 person yrs Between Jan-Dec 2011, there were 1500 reported cases of Type II Diabetes.
Between Jan-Dec 2012, there were 2000 reported cases of Type II Diabetes.
On 1 Jan 2013, 50 people were newly diagnosed with Type II Diabetes.
The point prevalence of Type II Diabetes on 1 Jan 2013 is 3550.
The period prevalence of Diabetes from 2011 - 2012 is 3500. summary Epidemiology
Incidence & Prevalence
Time, Place, Person
Diagnostic measures -
Predictive Values -
Positive PV, Negative PV