Testing for HIV can create anxiety for many individuals, especially those who want to know as soon as possible whether or not they are HIV positive.
There are a variety of tests that are used to detect HIV; some test for antibodies against HIV while others test for viral proteins and genetic material. No matter which test is used, it can take days to weeks for a test to detect HIV infection.
The period of time between becoming infected with HIV and the ability of a test to detect the infection is called the ‘window period’. In other words, for individuals who have actually been infected with HIV, their blood tests may be negative if they test during the window period. We refer to this as a false negative result.
The number of different HIV tests available and their associated window periods (and chances of getting a false negative test result) can be confusing for both patients and clinicians.
A table to calculate window periods
A tool has been developed to help guide clinicians and patients on the best time to test for HIV after a possible exposure.
The tool was developed by examining HIV test results from individuals who donate plasma on a regular basis and were tested for HIV each time they donated. These test results do not contain any personally identifiable information and are publically available.
Our study showed that the median window period for antibody tests (3rd generation) is 22 days and the median window period for antibody/antigen tests (4th generation) is 18 days. By pooling 780 test results from 136 donors, we were able to calculate the chances of getting a false negative test when testing with an antibody test or antigen/antibody test.
The below table displays the chances of getting a false negative result for a range of days after a possible exposure.
* Measures the body’s response to HIV through the detection of antibodies (3rd generation test)
** Measures a specific HIV protein in the body as well as antibodies (4th generation test)
How to use the table
To use this table, a clinician should ask their patient to estimate the number of days since they may have been exposed and then look at the corresponding probability of a false negative. For example, if someone thinks it’s been 14 days since the day they may have been exposed, there would be a 79-99% chance of a false negative result if they were to test that day with a 4th generation test.
More detailed probabilities can be found in the Taylor et al. manuscript. You can find more information and an easy-to-use version of the above table [/health-providers/hiv-tools]here.
We believe that the availability of a table providing the probability of a false negative test will facilitate decision-making for the best time to test for HIV and may reduce patient anxiety.
- BCCDC. HIV Laboratory Testing: a resource for health professionals. 30 June 2010.
- Worthington C, Myers T. Factors underlying anxiety in HIV testing: risk perceptions, stigma, and the patient-provider power dynamic. Qual Health Res 2003 May;13(5):636-55.
- Taylor D, Durigon M, Davis H, Archibald C, Konrad B, Coombs D, Gilbert M, Cook D, Krajden M, Wong T, Ogilvie G. Probability of a false negative HIV antibody test result during the window period: a tool for pre- and post-test counselling. Int J STD AIDS. 2014 Jul 16.