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This problem involves calculating the probability that a person tests positive for a disease based on the test's sensitivity, specificity, and the disease prevalence. Let’s break it down using the information provided.

### Given Information:
- 90% of the people who have the disease test positive (True Positive Rate or Sensitivity).
- 90% of the people who do not have the disease test negative (True Negative Rate or Specificity).
- 5% of the population has the disease (Prevalence).

We are asked to find the percentage of the total population that would test positive for the disease.

### Steps:

1. **Prevalence (Disease Rate):**
   - 5% of the population has the disease, so 95% of the population does not have the disease.

2. **True Positives (People with disease testing positive):**
   - Of the 5% of the population who have the disease, 90% of them will test positive.
   - This is \( 0.9 \times 0.05 = 0.045 \) or 4.5% of the total population.

3. **False Positives (People without disease testing positive):**
   - Of the 95% of the population who do not have the disease, 10% will falsely test positive (since 90% test negative).
   - This is \( 0.1 \times 0.95 = 0.095 \) or 9.5% of the total population.

4. **Total Percentage Testing Positive:**
   - Add the true positives and the false positives:
   \[
   4.5\% + 9.5\% = 14\%
   \]

### Answer:
The percentage of the population that would test positive for the disease is **14%**, which corresponds to option D.

Would you like further explanation on any of the steps?

Here are 5 related questions to further explore the concept:

1. How does changing the sensitivity of the test affect the total percentage of positive results?
2. What would happen if the prevalence of the disease increased to 10%? 
3. How can we calculate the percentage of people who truly have the disease given a positive test result?
4. What is the impact of lowering the test specificity to 80% on the total positive rate?
5. How do you interpret the meaning of false positive and false negative rates?

**Tip:** When evaluating test accuracy, always consider both sensitivity and specificity, as they provide crucial insights into the test’s reliability.

Ninety percent of the people who have a particular disease will have a positive result on a given diagnostic test. Ninety percent of the people who do not have the disease will have a negative result on this test. If 5 percent of a certain population has the disease, what percent of that population would test positive for the disease?

Learn how to calculate the percentage of a population that would test positive for a disease given test sensitivity, specificity, and prevalence. This problem involves key statistical concepts such as probability, true positive rates, and false positive rates. Ideal for high school or introductory college-level statistics.

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