Question

The RDT SARS-COV-2 test has 93.8 sensitivity (the probability of a true positive result) and 95.6%...

The RDT SARS-COV-2 test has 93.8 sensitivity (the probability of a true positive result) and 95.6% specificity (the probability of a true negative result) . Suppose that 10% of population is infected with SARS-COV-2. If a randomly selected individual tests positive, what is the probability he or she is infected?

Homework Answers

Answer #1

Probability that the selected individual who is tested positive is actually infected

= Positive Predictive Value

Here, sensitivity of test = 93.8% = 0.938

Specificity of test = 95.6% = 0.956

Prevalence of SARS-COV-2 = 10% = 0.10

Therefore, Positive predictive value =

= 0.703

So, the probability that the randomly selected individual who is tested positive is actually infected is 0.703 (or 70.3%)

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Suppose you live in a city where 10% of the population has had Coronavirus. There is...
Suppose you live in a city where 10% of the population has had Coronavirus. There is an antibody test that screens to see whether you have had the disease. Like all medical tests, it is not perfect; the sensitivity is 93.8% and the specificity is 95.6%. [These are real figures for a particular test.] These numbers refer to the true positive and true negative rate, respectively; that is, sensitivity is P(positive test | had disease) and specificity is P(negative test...
3. A diagnostic test has 95% sensitivity (the probability a person with the condition tests positive...
3. A diagnostic test has 95% sensitivity (the probability a person with the condition tests positive = 0.95) and 95% specificity (the probability a person without the condition tests negative = 0.95). In a population of people given the test, 1% of the people have the condition (probability a person has the condition = 0.01). (a) What proportion of the people will test positive? (b) Given a person has tested positive, what is the probability he/she has the condition?
The sensitivity and specificity of a diagnostic test in health care are defined as: • Sensitivity...
The sensitivity and specificity of a diagnostic test in health care are defined as: • Sensitivity = probability that the diagnostic test result is positive IF the patient has the disease; • Specificity = probability that the diagnostic test result is negative IF the patient does not have the disease. Suppose that two tests for the disease TB are applied as follows. Test A is applied to the full population, and anyone found positive according to test A is treated....
Sensitivity and specificity essential characteristics of medical tests. Sensitivity is the probability that the test will...
Sensitivity and specificity essential characteristics of medical tests. Sensitivity is the probability that the test will indicate “disease” given that the individual actually has the disease, and specificity is the probability that the test will indicate “no disease” given that the individual does not have the disease. Answer the following questions for a test with sensitivity 75% and specificity 99%. Let p denote the prevalence of the disease (i.e., proportion of the population with the disease). (a) For p =...
The most commonly used test for HIV has a sensitivity of 0.997 and a specificity of...
The most commonly used test for HIV has a sensitivity of 0.997 and a specificity of 0.985. In other words, a person infected with HIV will test positive for the virus 99.7% of the time while a person NOT infected with HIV will test NEGATIVE for the virus 98.5% of the time. Research current rates of infection for the indicated population in order to answer the following questions. 1. If a US randomly selected US resident is tested for HIV...
At present, the infection rate of COVID-19 in New York City is about 2.5%. A widely...
At present, the infection rate of COVID-19 in New York City is about 2.5%. A widely used nucleic acid based test has sensitivity of 93.8% and specificity 95.6%. Here, to quote Wikipedia: “sensitivity (also called the true positive rate, the recall, or probability of detection in some fields) measures the proportion of actual positives that are correctly identified as such; specificity (also called the true negative rate) measures the proportion of actual negatives that are correctly identified as such.” If...
In medical diagnosis, test sensitivity is the ability of a test to correctly identify those with...
In medical diagnosis, test sensitivity is the ability of a test to correctly identify those with the disease (true positive rate), whereas test specificity is the ability of the test to correctly identify those without the disease (true negative rate). This means that: • Sensitivity of test = P(test is positive | person has disease); • Specificity of test = P(test is negative | person does not have disease). Suppose that 1% of the population have a particular disease, and...
We have a test with sensitivity 95% and specificity 98%. We assume that 2% of a...
We have a test with sensitivity 95% and specificity 98%. We assume that 2% of a population is infected with a virus. The question is: What is the probability of a person beeing infected, even though they test negative?
We have an illness, where 2% of the polulation is infected, and we have a test...
We have an illness, where 2% of the polulation is infected, and we have a test with sensitivity 94% and specificity 98%. A="infected" and B="tests positive" The question: What is the probability that a test-subject tests positive, even when not infected? And how high does the specificity need to be such that the probability is below 10%
QUESTION 91 Use the table below to find the probability. Positive Test Result Negative Test Result...
QUESTION 91 Use the table below to find the probability. Positive Test Result Negative Test Result Subject Uses Drugs 44 (True Positive) 6 (False Negative) Subject is Not a Drug User 90 (False Positive) 860 (True Negative) If 2 of the 1000 test subjects are randomly selected, find the probability that both had false positive results. Assume that the 2 selections are made without replacement. (Round to 4 decimals)