**Core Concept**
The predictive value of a positive test, also known as the positive predictive value (PPV), is a measure of the probability that a person with a positive test result actually has the disease. It depends on the test's sensitivity, specificity, and the prevalence of the disease in the population being tested.

**Why the Correct Answer is Right**
To calculate the PPV, we can use the following formula:

PPV = (Sensitivity x Prevalence) / ((Sensitivity x Prevalence) + ((1 - Specificity) x (1 - Prevalence)))

Given that the sensitivity and specificity of the ELISA test are both 95%, we can plug these values into the formula:

PPV = (0.95 x 0.05) / ((0.95 x 0.05) + ((1 - 0.95) x (1 - 0.05)))
PPV = 0.0475 / (0.0475 + 0.00075)
PPV = 0.0475 / 0.04825
PPV ≈ 0.983

**Why Each Wrong Option is Incorrect**
**Option A:** This option is incorrect because it is less than 0.95, which is the sensitivity of the test. The PPV should be higher than the sensitivity due to the low prevalence of the disease.

**Option B:** This option is incorrect because it is greater than 0.95, which is the sensitivity of the test. The PPV should be lower than the sensitivity due to the low prevalence of the disease.

**Option C:** This option is incorrect because it is not a valid calculation for the PPV. The correct formula is given above.

**Option D:** This option is incorrect because it is not a valid calculation for the PPV. The correct formula is given above.

**Clinical Pearl / High-Yield Fact**
When interpreting the results of a diagnostic test, it's essential to consider the test's sensitivity, specificity, and the prevalence of the disease in the population being tested. The PPV can be affected by these factors, and a high PPV does not necessarily mean that the test is accurate.

**Correct Answer:** . 0.983