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False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

  • 1.  False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-10-2020 14:21
    Hello everyone, 

    I teach introductory statistics and I'm having a hard time finding information about the false positive rates, false negative rates, sensitivity, and specificity of COVID testing*. I'm not sure where or in what kinds of medical literature to find these details, either. If there is more than one diagnostic test, won't these 4 rates vary by manufacturer?

    If you're from the medical/statistical world and want to share more background information about these probabilities, please share!

    Thanks for your help. I look forward to using what I learn as a teaching tool this term.  :D

    -Jennifer



    *My apologies if I use the wrong medical terminology. I welcome corrections (in a private message) so that I'm not teaching my students incorrectly. :)

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    Jennifer Ward
    Clark College
    Vancouver, WA
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  • 2.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-13-2020 08:04
    I posted information and speculation on the molecular diagnostics tests on April 2 and the serological tests on April 6 at http://for-sci-law.blogspot.com/.

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    David Kaye
    Distinguished Professor Emeritus
    Penn State
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  • 3.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-14-2020 14:01
    This is great! Thanks, David! :D

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    Jennifer Ward
    Clark College
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  • 4.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-13-2020 18:39
    Jennifer, yes, you've got the correct terminology.
    David, great resource (http://for-sci-law.blogspot.com/)!

    Quick-and-easy definitions for those new to diagnostic tests:
    • False positive result: Positive test result for someone who does not have the condition of interest (here, COVID).
    • False negative result: Negative test result for someone who does have COVID.
    • Sensitivity: Ability of a test to identify (give a positive result for) someone with COVID; percentage of people with COVID whose test values are positive (denominator = # of people with COVID).
    • Specificity: Ability of a test to give a negative result for someone who does not have COVID; percentage of people without COVID whose test results are negative (denominator = # of people without COVID).
    Also of interest are predictive values - because when someone gets tested, they don't yet know whether they have COVID. These depend on prevalence of COVID, which could vary by state, suspected risk factors, etc. When evaluating test performance in a group of interest (representative prevalence):
    • Positive predictive value (PPV): Percentage of people with a positive test result who have COVID (denominator = # of positive test results).
    • Negative predictive value (NPV): Percentage of people with a negative test result who do not have COVID (denominator = # of negative test results).
    It often surprises people that in populations with a low prevalence of disease, tests with extremely high sensitivity and specificity (extremely low false negative and false positive rates) have very low positive predictive values. Making a 2-by-2 table shows why: Take a large population with a low prevalence of disease. Obtain expected cell counts using sensitivity and specificity. Most of the positive test results are from people without the condition of interest - because there are orders of magnitude more of them to begin with!

    When evaluating test performance in an enriched group - let's say, using a new test on some number of people already confirmed to have COVID and an equal number of people already confirmed to be COVID-free - we have to adjust back to the prevalence in the population of interest.

    One advantage of living in the US is that FDA's decisions are available on the internet for anyone who searches - pending time to post and with varying levels of detail.
    To find the latest posted materials on COVID tests:
    https://www.fda.gov/emergency-preparedness-and-response/coronavirus-disease-2019-covid-19/coronavirus-disease-2019-covid-19-frequently-asked-questions
    (accessed 2020-04-13) notes: "Currently there is no FDA-approved or cleared test to diagnose or detect COVID-19 because the virus that causes COVID-19 is new. Therefore, the FDA has issued several Emergency Use Authorizations (EUAs) ..."
    The EUA list is posted at:
    https://www.fda.gov/medical-devices/emergency-situations-medical-devices/emergency-use-authorizations#covid19ivd
    There are 33 entries in the "Test Kit Manufacturers and Commercial Laboratories Table"
    To see what goes to doctors, in the "Authorization Documents" column click "HCP;" similarly, for "Patients." To see numbers on sensitivity and specificity click "IFU" and look at Clinical Evaluation (or Clinical Performance).
    There are 10 entries in "High Complexity Molecular-Based Laboratory Developed Tests." To see numbers on sensitivity click "EUA Summary" and again look for Clinical Evaluation.
    [NOTE: Documents also report Analytical Sensitivity and Analytical Specificity for bench testing.]

    Hope that helps,
    Alicia

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    Alicia Toledano
    President
    Biostatistics Consulting, LLC
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  • 5.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-14-2020 14:09
    Thank you, Alicia! I especially appreciate your explanations of PPV and NPV where you clearly specify what the denominator value is.

    Thank you also for the link to the COVID-19 test materials!

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    Jennifer Ward
    Clark College
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  • 6.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-20-2020 13:40
    Hi Jennifer,
         I am teaching Intro Statistics at a local Community College and I am also interested in including something on the COVID -19 testing in class.  I am probably looking at something even more basic in the sense that I would first like to discuss how viruses spread and how the professionals approach sampling and testing.
        If you come across any good worksheets or discussions about this please let me know.

       Also, thank you for posting your interest in teaching this topic...I think this COVID-19 could be a great teaching "moment" for us.  The only problem is that much of the discussions so far are on such a high level my students really can't follow what is being said...I need something appropriate for a first year college student in their first Statistics course and just learning about Hypothesis Testing, etc.

                                                                                                                                                                        John Conrad

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    John Conrad
    Teacher
    Hudson Valley Community College
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  • 7.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-20-2020 18:29
    Straying from the title of this thread, the class could discuss the  sources of bias in the statistics on reported cases of the disease or of positive test results on people who get tested in order to estimate the incidence of the disease or infections. We'll be seeing more data from random sampling and serological tests. These will show that a much larger proportion of people have been infected. See https://www.latimes.com/california/story/2020-04-17/coronavirus-antibodies-study-santa-clara-county. In a way, that's good news. Consider the implications for estimates of the probability that an infection will prove fatal.
    A month ago, John Ionnidis wrote that "The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable. Given the limited testing to date, some deaths and probably the vast majority of infections due to SARS-CoV-2 are being missed. We don't know if we are failing to capture infections by a factor of three or 300."  https://www.statnews.com/2020/03/17/a-fiasco-in-the-making-as-the-coronavirus-pandemic-takes-hold-we-are-making-decisions-without-reliable-data/. It is worth asking whether that is still true. It could be turned into a research project.

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    David Kaye
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  • 8.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-20-2020 23:49
    John,

    Never underestimate your students abilities. I've taught 200-300 stats students and tutored hundreds more. Out of all of those students, I can only think of 5-6 that just weren't very good. I also give my students questions from the PhD qualifying exams for Industrial Engineers at WAyne State University. Once you remove all the Calculus and proof stuff, there is about 70% of each exam that the students could do. 

    If you weave everything in well, and give them a formula or 2, they can do wonderful things. I'm going to give my students something like:

    Suppose there are 10,000,000 people in the state. Calculate the number of people that are hospitalized and the number that die under the given situations.  

    1) In state A, they decide "exposure parties" are a great idea.

    2) In state B, they decide "closing the state" can't happen.

    3) In state C, they decide "Stay at home" is a good idea and mostly do it. 

    I will give them an equation and the values to use, and see what they get. 

    Then I will ask, between the 3 states, which one do you think had the "best" idea, based upon the outcomes? (All reasoned and reasonable answers are corrrect.) 

    I will follow that up with:

    Suppose that each person in the hospital cost $10,000. Each person that died cost $300,000. During the pandemic, economic output was $X per worker regardless of state. Based upon Decision Analysis, which state did best? worst? ( I might have state A and B do better economically. might not.) 

    And follow that up with:

    Do you take issue with the costs used above? Why or why not? 

    Based the economic and personal outcomes, which state do you think did "best"? (All reasoned and reasonable answers are correct.) 

    (I also require them to write their answers in english, not mathenese.) 

    I expect 80% to 90% of my students to get every point on this question. 

    I'll also have the testings and quarantining questions I wrote earlier..... (I think I wrote them here.)

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    Andrew Ekstrom

    Statistician, Chemist, HPC Abuser;-)
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  • 9.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-15-2020 10:26
    Thank you for the terminology and the explanation. I wondered, what number have you found to represent prevalence? Thanks!

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    Sheila Braun
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  • 10.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-15-2020 13:38
    Sheila,

    Great question. I'm not on the front lines, I hope someone who is can post that information. Absent that, your state may have a dashboard with case counts by smaller regions. [For the epidemiologists among us, prevalence with respect to affecting predictive values is closer to incidence because the COVID-19 cases are all "new." A discussion on this topic would also be welcome.] [I should also note that there are global dashboards by country, sometimes with subdivisions; and discussions in other ASA communities/listservs.]

    Maryland, where I live, has a dashboard that posts by county and by zip code (https://coronavirus.maryland.gov/datasets/md-covid-19-data-dashboard). These would have to be paired with denominators, for example, from the census (https://www.census.gov/quickfacts/fact/table/US/PST045219). From the Maryland dashboard at the time of this reply, there were 10,032 "confirmed cases" among 10,032 positive +  45,731 negative = 55,763 tests. Ignoring the possibility of multiple tests per person, 17.99% of people tested get positive test results. Using population as the denominator, the census projection for 2019 is 6,045,680 people in Maryland (2020 census is in progress). Ignoring population change and the possibility of multiple positive tests per person, 0.166% of people in Maryland have tested positive for COVID-19. I spent time typing the assumptions (Ignoring yada yada; assumptions would be one test per person and no change in population from 2019 projection) because that's always the right thing to do.

    Now pull in sensitivity and specificity, and say they are both 99.9% (total benefit-of-the-doubt guess, as there's not a lot of data on EUAs and LDTs): 1 person per 1,000 with COVID-19 will have a false negative result (FNR = 0.1%), and 1 person per 1,000 without COVID-19 will have a false positive result (FPR = 0.1%). The number of people who test positive is (sensitivity times number with COVID-19) + (FPR times number without it); the number of people who test negative is derived similarly. This gives 2 equations in 2 unknowns (number with COVID-19, number without it). Solve for the unknowns and make the 2-by-2 tables for expected cell counts among Marylanders tested and among all Marylanders. Both of the negative predictive values (NPVs) are ~100%. Positive predictive value (PPV) is > 99% for Marylanders tested, but if we tested everyone independent of symptoms and need for different actions if the test is positive the PPV in Maryland would be ~40%. That gut feeling about the importance of reserving test kits for people with symptoms for whom different actions would be taken with a positive test result now has (ballpark) numerical support.

    Stay safe, stay healthy!

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    Alicia Toledano
    President
    Biostatistics Consulting, LLC
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  • 11.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-16-2020 10:35
    Thanks for the "worked out examples" Alicia! :D

    My students just did an activity about the census so seeing that you referenced the census to compute probabilities makes the census projections directly relevant to them. 

    Jennife

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    Jennifer Ward
    Clark College
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  • 12.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-17-2020 07:45
    Also, you might be interested in these early serologic data from Johns Hopkins Center for Health Security: https://www.centerforhealthsecurity.org/resources/COVID-19/serology/Serology-based-tests-for-COVID-19.html#sec2

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    Donna Stroup
    Director
    Data for Solutions, Inc.
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  • 13.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-15-2020 16:17
      |   view attached
    Hey Jen,

    I do something similar to what you are looking for. I keep it generic though. I uploaded an Excel sheet I give my Intro to stats students. I use it to reinforce ideas about probability, conditional probability and the consequences of being wrong. I base the calculations off of 100,000 subjects. The reason for that is, a lot of diseases are given as a disease rate or (number with disease) per 100,000 subjects. So, we can talk about the cancer rate in my area. It is about 750. So, about 0.75% of the people in my area have cancer. You can put that probability in cell ​​D9. In cell D8 and D7 you enter your false positive and false negative rates. The sheet calculates the Probability of a correct answer/result, Prob(Event(+)|Test(+)) and Prob(Test(+)|Event(+)).

    I will ask questions like, "Suppose that a cancer screening test has Prob(Event(+)|Test(+)) = 0.1256. What would you tell a patient or friend that just tested positive?" 

    With this outbreak of COVID-19, I'm going to up the ante. I'll say that the probability of the disease is 5%. False(+)=False(-) = 5% and ask, "What is the probability that a positive test means the person has the disease? What do you do with those who test positive? If someone suggested that all those that test positive be put into a centralized quarantine, how many healthy people might get infected? and, do you think that is a good idea? and Why?" 

    Then follow that up with, "What if you found out that False(+) = 0.10, False(-) = 0.12: What is the probability of a correct test result? What is the new probability that a positive test means the person has the disease? What do you do with those who test positive? If someone suggested that all those that test positive be put into a centralized quarantine, how many healthy people might get infected? and, do you think that is a good idea? and Why?" 

    I'm sure my students will be fully annoyed with these questions. But, they need to understand the consequences of decisions. For the opinion questions, as long as they use the info I gave and their beliefs, I am fine with whatever they write. (I tend to have nurses and nursing students in my classes. Some business majors too. They tend to use the info I gave and knowledge they gained in other classes to answer those opinion questions.) 



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    Andrew Ekstrom

    Statistician, Chemist, HPC Abuser;-)
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    Attachment(s)



  • 14.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-16-2020 11:02
    Hey Andrew! 

    I recognize you from one of my other ASA posts. :) Sheila, too, actually.

    I have a lot of pre-nursing student in my classes and, until now, I felt like I had a missed opportunity to talk about the false positive rate, positive predictive value, etc. Thanks for the Excel spreadsheet. I *really* like it because students can quickly put in some numbers and make comparisons. My original thought would have been to have students compute false positives, false negatives, etc by hand but that's so slow. This term, it makes more sense to get to the heart of the objective faster and interpret the results.

    Jennifer


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    Jennifer Ward
    Clark College
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  • 15.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-16-2020 11:29
    What about the fact that only a portion of the population is getting tested, and not a random portion?  How does the prevalence in the tested portion compare to the prevalence in the whole population?  How do we come up with reasonable guesses about that?

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    Alexa Sorant
    NIH/NHGRI
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  • 16.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-16-2020 12:04
    When I asked a virologist friend about prevalence, they said that when it's an infectious disease and still spreading, you can't use that term to any effect. You have to use Ro, but I haven't figured out how to use that number in Bayes's Theorem. There's probably a way, but it's outside the scope of my work to figure it out and I have limited free time to look into it.

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    Sheila Braun
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  • 17.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-16-2020 15:34
    The reproduction rate r0 is not a prior probability (or a prevalence or incidence). See doi: 10.3201/eid2501.171901. It is not something to plug into Bayes' rule along with sensitivity and specificity estimates. Instead, it can be used in a model to estimate the number of cases in the whole population. See  Kathleen M. Jagodnik, Forest Ray, Federico M. Giorgi & Alexander Lachmann, Correcting Under-reported COVID-19 Case Numbers: Estimating the True Scale of the Pandemic.

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    David Kaye
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  • 18.  RE: False positive, false negative, sensitivity, specificity of COVID testing (for teaching)

    Posted 04-16-2020 17:06
    When I am teaching my intro classes, I have them use calculators. After the first HW problem or 2, I figure they know how to add, multiply and divide. So, I just give them sheets like that. It saves time. It also gives them a sense that Excel and other software actually make things easier to do. My hope is that my students can take the ideas from Excel sheets and apply them in other classes. By not wasting too much time with fundamental stuff, I have a lot more time for useful stuff. Like discussing and having the students run multiple linear regressions. (Last time I taught the class, I had my students use student level data from the last 10 years, select 2-3 classes they were interested in, (math and science classes only) run a regression with semester, professor, class and something else on "Pass" and "Pass with an A". Then optimize it. Then I asked, did they get different results? What class should they take, when should they take it and with whom, if they want to maximize their chances of passing. Passing with an A. I won over 25 student that day.  They won't be experts. But, they know what is possible. So, they at least know they can ask someone or do a web search for it.

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    Andrew Ekstrom

    Statistician, Chemist, HPC Abuser;-)
    ------------------------------