Measuring Morbidity: Prevalence and Incidence
Read the scenario below and complete the assignment as instructed.
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.
Measuring Morbidity: Prevalence and Incidence
Number of People Infected
The number of people infected with is 440 as at January 2012. It was calculated through the multiplication of the prevalence rate (2.2%) by the number of people in the population who were measured (20,000) and then divided by the total percentage (100). Ultimately it gives the number of people infected in the community. The numerator is the product of the prevalence rate and the population sampled while the denominator is the total percentage. The formulae used are as follows
Prevalence rate *Number of people in the Population/100
2.2*20,000/100 = 440 people infected with HIV in community X.
Incidence Rate
The incidence rate is used to denote the number of new cases in a given period. In the community, there were 50 new cases recorded between February 2012 and January 2013,bringing the number of HIV infections in community X to 490 cases. The numerator is the number of new cases reported within the 12 months between February 2012 and January 2013 while the denominator is the total number of persons in the population also described as person-year within the same period. Furthermore, it shows the person per year observed in community X.Therefore, the calculation is as follows
50/20,000 = 0.0025.
It is also expressed as 2.5 per 1000 person-year.
Relationship Between Prevalence and Incidence Rates
Prevalence and incidence rates are measures that are used to denote the disease burden in a community. Whereas the prevalence rate denotes the number of existing diseases cases in a population, incidence rate represents the number of new cases of the disease reported in a given period in the same observed sample population (Brinks & Landwehr, 2015). Moreover, the prevalence rate grows until it equals the death or mortality rate meaning that there is no disease in the given sample. In an epidemic, the prevalence growth is initially fast and later evens out as all the number of individuals at risk are infected and is contributed to by the incidence rate,which captures the new cases reported. Additionally, the prevalence rate indicates how widespread the diseases while the incidence rate shows the number of people at risk from the infection in a section of the population.
The epidemiologist should be concerned as the incidence rate in Community X has increased from 0.5 per 1000person year to 2.5 per 1000-person-year meaning that the prevention measures and strategies used to sensitize the community are not effective hence the high number of new cases (Jones, Sullivan, & Curran, 2019).Furthermore, the is the need to increase sensitization and awareness creation in community X to reduce the at-risk population and ensure behavior change,which would lower the incidence rate of the disease. Ultimately, the epidemiologist should be a concern and formulate strategies to enhance behavior change and eradicate or reduce the risk factors in the community through sensitization on HIV in community X.
Part 2
2*2 Contingency Table
| HIV Positive | HIV Negative | Total | |
| Rapid Test + | 436 | 17604 | 18040 |
| Rapid Test – | 4 | 1956 | 1960 |
| Total | 440 | 19560 | 20000 |
The above 2*2 contingency table shows the results of a rapid HIV test with a sensitivity of 99.1% and a specificity of 90% with a prevalence rate of the disease in Community X being 2.2%.The gold standard of diagnosis aids the epidemiologist in calculating the positive predictive value which denotes the actual percentage of the positive test results that have the disease with the given sensitivity and specificity as such the numerator is the number of positive tests and the denominator is the total of the positive tests. Ultimate the calculation is as follows:
436/18040*100= 2.42% Positive predictive value
The negative predictive test indicates the number of false negatives,which are denoted by the test. The numerator is the number of individuals that tested negative but are diseases while the denominator is the total number of people who are tested negative using the rapid detection kit. Consequently, the calculations are as follows:
4/1960*100 = 0.20% Negative predictive value
The epidemiologist should implement the test in the universal screening program executed in the community as it has a high sensitivity and specificity test with little margin of error. The negative predictive value of the test is 0.20% in the population sample of 20,000 in community X. Furthermore, the positive predictive value denoting false positives is 2.42% in the same population. As such there is the need to implement the test as the variance from the normal is minimal hence the risk of having false positives and negatives is minimal (Boadu, Darko, Nortey, Akweongo, & Sarfo, 2016). It will also eliminate the risk of cross-sensitivity with other related viruses which might be in the found in the community. The test is highly specific and can be sued in early detection with a high degree of accuracy hence once can denote the incidence rate through screeningwith the rapid kit test. Moreover, the negative tests after a high-risk activity will be minimized as the virus will be detected in a short window period (Power, Fell, & Wright, 2013). With the kit’s incorporation in the screening program, the number of actual HIV cases will be detected and the mitigation factors instituted as the first, second, and third level of prevention strategies thus reducing the burden of the disease.
References
Boadu, R., Darko, G., Nortey, P., Akweongo, P., & Sarfo, B. (2016). Assessing the sensitivity and specificity of First Response HIV-1-2 test kit with whole blood and serum samples: A cross-sectional study. AIDS Research and Therapy, 13(9), 1-8.
Brinks, R., & Landwehr, S. (2015). A new relation between prevalence and incidence of a chronic disease. Mathematical Medicine and Biology; A journal of the IMA, 32(4), 425-435. doi:10.1093/imammb/dqu024
Jones, J., Sullivan, P. S., & Curran, J. W. (2019). Progress in the HIV epidemic: Identifying goals and measuring success. PLoS Medicine, 16(1), e1002729. Power, M., Fell, G., & Wright, M. (2013). Principles for high-quality, high-value testing. BMJ Evidence-Based Medicine, 18(1), 5-10