**Core Concept**
The predictive value of a positive test in a population is influenced by the disease prevalence. It refers to the probability that a person with a positive test result actually has the disease. This concept is crucial in understanding the performance of diagnostic tests.

**Why the Correct Answer is Right**
As the prevalence of a disease in a population increases, the predictive value of a positive test also increases. This is because a higher disease prevalence means that more individuals in the population are likely to have the disease, making the positive test result more indicative of the disease. The likelihood ratio of the test (positive test result in diseased individuals vs. healthy individuals) remains the same, but the change in disease prevalence shifts the pre-test probability, leading to an increase in the predictive value of a positive test.

**Why Each Wrong Option is Incorrect**
* **Option A:** This option is incorrect because the predictive value of a positive test actually increases with disease prevalence, not decreases.
* **Option B:** This option is incorrect because the predictive value of a positive test depends on the disease prevalence, not the test's sensitivity or specificity.
* **Option C:** This option is incorrect because the predictive value of a positive test is not directly related to the disease's severity or mortality rate.

**Clinical Pearl / High-Yield Fact**
Remember the "Bayes' Theorem" - the predictive value of a positive test is influenced by the pre-test probability (disease prevalence) and the test's likelihood ratio. A higher disease prevalence increases the predictive value of a positive test, while a lower disease prevalence decreases it.

**Correct Answer:** C.