Read the scenario below and complete the assignment as instructed.
Scenario
In Community X (population 20,000), an epidemiologist conducted a prevalence survey in January of 2012 and reported an HIV prevalence of 2.2%. Over the next 12 months, the department of health reported an additional 50 new HIV cases between February 2012 and January 2013. The total population stayed constant at 20,000.
Part 1
- How many people had HIV in January 2012? Present or describe the formula you used to arrive at your answer.
- Calculate the incidence rate assuming no HIV-related deaths over the 12-month period. Present or describe the formula you used to arrive at your answer. Be sure to clearly indicate the numerator and denominator used in your calculation and include an appropriate label for the rate.
In a summary of 200-250 words, interpret the results and discuss the relationship between incidence and prevalence. Discuss whether or not the epidemiologist should be concerned about these new HIV infections, assuming a previous incidence rate of 0.5 per 1,000 person-years prior to this updated risk assessment.
Part 2
A rapid test used for diagnosing HIV has a sensitivity of 99.1% and a specificity of 90%. Based on the population prevalence of 2.2% in 2012, create a 2×2 table showing the number of true positives, false positives, false negatives, and true negatives. Calculate the positive predicative value and negative predictive value for this test. Refer to the “Creating a 2×2 Contingency Table” resource for guidance.
In 200-250 words, discuss whether or not the epidemiologist should recommend this test as part of a universal HIV screening program. Provide rationale for your recommendation applying the positive and negative predictive values. Present or describe the formula you used to arrive at your answer.
General Requirements
APA style is not required, but solid academic writing is expected.
Expert Solution Preview
Introduction:
This assignment requires an understanding of epidemiology and calculations associated with it. The scenario presents a prevalence survey in a community and the subsequent increase in HIV cases. The first part requires the calculation of HIV prevalence and incidence rate, while the second part requires the creation of a 2×2 table and the recommendation of an HIV screening test based on the positive and negative predictive values.
Part 1:
1. To determine the number of people with HIV in January 2012, we multiply the HIV prevalence rate by the total population: 2.2% x 20,000 = 440 individuals.
2. The formula for incidence rate is: (number of new cases during a time period / population at risk during that time period) x constant (multiplier for easier interpretation, e.g. 1,000). In this case, the numerator is 50 new HIV cases, and the denominator is the constant population of 20,000. Assuming no HIV-related deaths, the incidence rate is (50/20,000) x 1,000 = 2.5 per 1,000 person-years.
Interpretation and Relationship between Incidence and Prevalence:
Prevalence refers to the number of individuals with a disease in a population, while incidence represents the rate of new cases in a specified time period. The increase in HIV cases in the community indicates a higher incidence rate than the previous rate of 0.5 per 1,000 person-years. Although prevalence and incidence are related, they do not provide the complete picture of the community’s HIV status. The epidemiologist should be concerned about the new HIV infections and initiate further investigation.
Part 2:
The 2×2 Table is as Follows:
| | HIV Positive | HIV Negative |
|—————–|—————-|—————-|
| Test Positive | 96 | 1980 |
| Test Negative | 4 | 18920 |
The formula for positive predictive value (PPV) is: true positives / (true positives + false positives). In this case, the PPV is 96 / (96 + 1980) = 4.61%.
The formula for negative predictive value (NPV) is: true negatives / (true negatives + false negatives). In this case, the NPV is 18,920 / (18,920 + 4) = 99.98%.
Recommendation and Rationale:
Based on the low PPV, the epidemiologist should not recommend this test as part of a universal HIV screening program. A high false positive rate would lead to unnecessary anxiety and further testing in individuals who do not have HIV. The high NPV indicates that the test is useful for ruling out HIV in individuals who test negative, but the low PPV negates its significance in confirming HIV in individuals who test positive. As such, an alternative test with a higher PPV should be recommended.
Conclusion:
The assignment requires an understanding of epidemiology calculations, interpretation of results, and recommendation based on positive and negative predictive values. It highlights the significance of the relationship between incidence and prevalence and the need for epidemiologists to keep a close eye on changes in HIV rates in a community.
