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The model illustrates the difference by showing that $P(+\mid D)$ (sensitivity) is fixed at $95\%$, while $P(D\mid +)$ (positive predictive value) is calculated to be only $~16.1\%$. This demonstrates that the probability of a positive test given disease is not the same as the probability of disease given a positive test, especially when prevalence is low.

Conditions: Sensitivity is $95\%$.; Calculated $P(D\mid +)$ is $~16.1\%$.; Prevalence is $1\%$.

The model illustrates the difference by showing that $P(+\mid D)$ (sensitivity) is fixed at $95\%$, while $P(D\mid +)$ (positive predictive value) is calculated to be only $~16.1\%$. This demonstrates that the probability of a positive test given disease is not the same as the probability of disease given a positive test, especially when prevalence is low.

Conditions: Sensitivity is $95\%$.; Calculated $P(D\mid +)$ is $~16.1\%$.; Prevalence is $1\%$.