Suppose that in January 1996, 1000 adult residents of a community accepted an invitation to be examined for hypothyroidism at a local clinic. Eight persons were found to have the disease, it was newly discovered in 3, and 5 were already under treatment. The same group was examined again in January 1998. Six new cases of hypothyroidism were discovered; of these, two had developed symptoms several months before and had been diagnosed and treated by their personal physicians. It was learned that of the 8 hypothyroid persons discovered at the 1996 examination, one had discontinued medication and died of heart disease in 1997. Otherwise, all persons examined in 1996 came to the second examination.
Using the above information, respond to the following questions – don’t forget to use the formulas already provided in this chapter:
I would greatly appreciate your assistance in verifying my calculations and providing any insights you may have.
1. Jan 1996: 8/1000; Jan 1998: (8+6-1)/1000
2. Annual incidence: 6/(2years*1000 assuming a representative sample of study population or population at risk)
3. 6/1000
4. 0% -- not counting death due to heart disease
5. (3+6)/(8+6) --- assuming newly discovered is regardless of being on treatment
6. #1-4 would have been changed due to a different denominator (sample of 900 representing the study population/population at risk). #5 would remain the same.
The prevalence in Jan 1996 was 8 per 1000.
The prevalence in Jan 1998 was (13/999)*1000 = 13/1000
Incidence in 1997: 2 new cases in 1997/992 who should be free from disease at the start of the period. so 2/1000.
Two-year period prevalence: 13/999 * 1000 = 13/1000
Case fatality rate: It is not clear whether stopping the medication affected the heart condition or not.
Newly discovered: 7/14 * 100 = 50%
The answers will be changed if you change the denominator but the case fatality will not be affected.
Note: I am not sure 100% that all my answers were correct.
1A, ordnance in 1996= 8/1000=0.8%
1B, prevalence in 1998=8-1+6/1000=13/1000=1.3%
2, Annual incidence =(6/2)/992=0.0030 or 0.3%
3, The 2-year period prevalence=6+8/1000=14/1000=1.4% that means total case means existing plus new cases
4, The CFR =1/8=12.5 because of proportion who died due to the disease from those diagnosed in 1996.
5, from all case detected at both exam = 9/14=63.4%
All my response may not be 100% true!!!!!!
Here are the definitions and explanations for some key epidemiological terms, including prevalence and case fatality rate, among others:
1. Prevalence
- Definition: The total number of cases of a specific disease or condition present in a population at a given time.
- Formula: Prevalence=Number of existing casesTotal population×10n\text{Prevalence} = \frac{\text{Number of existing cases}}{\text{Total population}} \times 10^nPrevalence=Total populationNumber of existing cases×10nwhere 10n10^n10n is a multiplier (e.g., per 1,000 or per 100,000 individuals).
- Types:Point Prevalence: The proportion of a population with a specific disease at a single point in time. Period Prevalence: The proportion of a population with a specific disease over a specified period of time.
2. Incidence
- Definition: The number of new cases of a specific disease occurring in a population during a specific period of time.
- Formula: Incidence=Number of new cases during a specified periodPopulation at risk during that period×10n\text{Incidence} = \frac{\text{Number of new cases during a specified period}}{\text{Population at risk during that period}} \times 10^nIncidence=Population at risk during that periodNumber of new cases during a specified period×10n
- Types:Incidence Rate: Reflects the occurrence of new cases over a specified time period. Cumulative Incidence: Reflects the probability of developing a disease over a specified period.
3. Case Fatality Rate (CFR)
- Definition: The proportion of individuals diagnosed with a particular disease who die from that disease within a specified period.
- Formula: CFR=Number of deaths due to diseaseNumber of diagnosed cases×100\text{CFR} = \frac{\text{Number of deaths due to disease}}{\text{Number of diagnosed cases}} \times 100CFR=Number of diagnosed casesNumber of deaths due to disease×100
- Usage: Often used to indicate the severity of a disease and its impact on affected individuals.
4. Mortality Rate
- Definition: The frequency of death in a given population during a specific period.
- Formula: Mortality Rate=Number of deathsTotal population×10n\text{Mortality Rate} = \frac{\text{Number of deaths}}{\text{Total population}} \times 10^nMortality Rate=Total populationNumber of deaths×10n
- Types:Crude Mortality Rate: The overall death rate in a population. Specific Mortality Rate: The death rate for a specific disease or population subgroup.
5. Attack Rate
- Definition: The proportion of individuals exposed to an infectious agent who become ill.
- Formula: Attack Rate=Number of new casesNumber of people exposed×100\text{Attack Rate} = \frac{\text{Number of new cases}}{\text{Number of people exposed}} \times 100Attack Rate=Number of people exposedNumber of new cases×100
- Usage: Commonly used in outbreak investigations.
6. Risk
- Definition: The probability that an individual will develop a specific disease or condition over a specified period.
- Formula: Risk=Number of new casesPopulation at risk×100\text{Risk} = \frac{\text{Number of new cases}}{\text{Population at risk}} \times 100Risk=Population at riskNumber of new cases×100
7. Relative Risk (RR)
- Definition: A measure of the strength of the association between exposure to a risk factor and the occurrence of a disease.
- Formula: RR=Incidence rate in exposed groupIncidence rate in unexposed group\text{RR} = \frac{\text{Incidence rate in exposed group}}{\text{Incidence rate in unexposed group}}RR=Incidence rate in unexposed groupIncidence rate in exposed group
8. Odds Ratio (OR)
- Definition: A measure of the association between an exposure and an outcome, often used in case-control studies.
- Formula: OR=Odds of exposure in casesOdds of exposure in controls\text{OR} = \frac{\text{Odds of exposure in cases}}{\text{Odds of exposure in controls}}OR=Odds of exposure in controlsOdds of exposure in cases
9. Sensitivity and Specificity
- Sensitivity: The ability of a test to correctly identify individuals with a disease. Sensitivity=True PositivesTrue Positives + False Negatives×100\text{Sensitivity} = \frac{\text{True Positives}}{\text{True Positives + False Negatives}} \times 100Sensitivity=True Positives + False NegativesTrue Positives×100
- Specificity: The ability of a test to correctly identify individuals without a disease. Specificity=True NegativesTrue Negatives + False Positives×100\text{Specificity} = \frac{\text{True Negatives}}{\text{True Negatives + False Positives}} \times 100Specificity=True Negatives + False PositivesTrue Negatives×100
10. Positive Predictive Value (PPV) and Negative Predictive Value (NPV)
- PPV: The probability that individuals with a positive test truly have the disease. PPV=True PositivesTrue Positives + False Positives×100\text{PPV} = \frac{\text{True Positives}}{\text{True Positives + False Positives}} \times 100PPV=True Positives + False PositivesTrue Positives×100
- NPV: The probability that individuals with a negative test truly do not have the disease. NPV=True NegativesTrue Negatives + False Negatives×100\text{NPV} = \frac{\text{True Negatives}}{\text{True Negatives + False Negatives}} \times 100NPV=True Negatives + False NegativesTrue Negatives×100
Understanding these terms and how to calculate them is fundamental to epidemiology, helping public health professionals assess and respond to disease outbreaks and other health-related events.
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Here are brief definitions for key epidemiology terms:
These measures help understand the frequency, severity, and impact of health conditions.
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