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To calculate the probability of having the disease given a positive test result, you must count the number of true positives and divide it by the total number of positive results (true positives plus false positives). In the model, this involves identifying the 19 true positives out of the 118 total positive tests, yielding approximately $16.1\%$.

Conditions: Prevalence is $1\%$ in a population of 2,000.; Sensitivity is $95\%$.; Specificity is $95\%$.

To calculate the probability of having the disease given a positive test result, you must count the number of true positives and divide it by the total number of positive results (true positives plus false positives). In the model, this involves identifying the 19 true positives out of the 118 total positive tests, yielding approximately $16.1\%$.

Conditions: Prevalence is $1\%$ in a population of 2,000.; Sensitivity is $95\%$.; Specificity is $95\%$.