**Core Concept**
The percent prevalence of a disease is the total number of cases of the disease in a population divided by the total population, multiplied by 100. In this scenario, we need to calculate the true prevalence of the disease using the given test results.

**Why the Correct Answer is Right**
To calculate the true prevalence, we can use the Bayes' theorem or the concept of sensitivity and specificity. The test has a sensitivity of 90% (400 true positives out of 400 + 20 false negatives) and a specificity of 95% (20 false positives out of 400 + 20 false negatives). However, to calculate the prevalence, we can use the concept of positive predictive value (PPV). PPV is the proportion of individuals with a positive test result who actually have the disease.

**Why Each Wrong Option is Incorrect**
**Option A:**
This option is incorrect because it does not take into account the specificity of the test. A positive result alone is not enough to calculate prevalence.

**Option B:**
This option is incorrect because it does not use the correct formula for calculating prevalence. Prevalence is calculated as the number of true positives divided by the total number of individuals in the population.

**Option C:**
This option is incorrect because it does not take into account the sensitivity of the test. A high sensitivity is necessary to calculate the true number of cases.

**Option D:**
This option is incorrect because it does not use the correct formula for calculating prevalence. The correct formula is the number of true positives divided by the total number of individuals in the population.

**Clinical Pearl / High-Yield Fact**
To calculate the true prevalence of a disease, it's essential to use the correct formula and take into account the sensitivity and specificity of the diagnostic test.

**Correct Answer:** . 2.5%