**Core Concept**
False positive rates in screening tests are influenced by disease prevalence. In low-prevalence settings, even a sensitive test can produce many false positives due to the small number of actual cases, leading to a higher proportion of non-cases being incorrectly identified as diseased.

**Why the Correct Answer is Right**
In a community with **low prevalence**, the majority of individuals are healthy. A screening test, even if specific, will still misclassify many healthy individuals as having the disease — resulting in **high false positive rates**. When **incidence is high**, it means new cases are frequent, but low prevalence implies the disease is still uncommon overall. This combination amplifies false positives because the test detects more non-diseased individuals as positive. The key is that **low prevalence** drives false positives, while **high incidence** reflects frequent new cases, which is consistent with active disease spread.

**Why Each Wrong Option is Incorrect**
Option A: High prevalence & low incidence is illogical — high prevalence contradicts low false positives; low incidence doesn't support high false positives.
Option C: Low prevalence & low incidence implies very few cases, leading to minimal false positives, not high ones.
Option D: High prevalence reduces false positives because most people have the disease, so test results are more likely to be true positives.

**Clinical Pearl / High-Yield Fact**
In low-prevalence populations, **screening tests often yield more false positives** — this is why screening is usually reserved for high-risk groups or when prevalence is high. Always consider population-level disease burden when interpreting test results.

✓ Correct Answer: B. High incidence & Low prevalence