The Complex Interpretation and Management of Zika Virus Test Results

Kenneth W. Lin, MD, MPH; John D. Kraemer, JD, MPH; Rachael Piltch-Loeb, MSPH; Michael A. Stoto, PhD


J Am Board Fam Med. 2018;31(6):924-930. 

In This Article

Clinical Scenarios

The drivers of Zika virus testing outlined above highlight the varying reasons and motivations for initiating a Zika virus test. Health departments/facilities have developed complex algorithms to initiate Zika virus testing, but the guidelines are subject to change and the meaningful interpretation of a positive or negative Zika virus test result depends on understanding how test and context-dependent factors interact. The sensitivity and specificity of any test depends on what type of test was done and when it was done relative to the time of exposure. Furthermore, the interpretation of a positive or negative test also depends on the pretest probability of infection, which is a function of who was tested, where he or she lives or has traveled, and why the test was performed. We provide 3 scenarios to illustrate these points.

Scenario 1: Low Pretest Probability

Suppose a woman attends a routine antenatal visit in Minneapolis, where there is no local Zika virus transmission. She has flu-like symptoms but no history of travel to an affected area and no recent sexual partners who have traveled to an affected area. There is no indication for ordering a Zika virus test in this patient, and it is not recommended. However, because it was in the news, she requests a Zika virus test. Her likelihood of Zika virus infection is very small, perhaps 1 in 10,000 (though likely much lower). She is given a well-performing IgM ELISA test with 99% sensitivity and 95% specificity. In this situation, a positive result would only have a positive predictive value (PPV) of 1 in 500, reflecting the very low likelihood of an actual history of Zika virus infection. A negative result would rule out Zika virus with near certainty.

Scenario 2: High Pretest Probability

At the opposite end of the spectrum, consider a pregnant woman who lives in Puerto Rico and presents to her physician with classic Zika virus symptoms: fever, muscle and joint pain, and rash. In this case, we assume her pretest probability of Zika virus infection is 80%. She is given an appropriate reverse transcription-PCR test that has been shown not to cross-react with dengue fever virus or other likely infections. Limited data are available on sensitivity and specificity but assume 99% sensitivity and 95% specificity. In this scenario, a positive test is 98.8% likely to signal actual Zika virus infection. Even in the situation where there is a 50% chance she is coinfected with dengue and her test has a 10% likelihood of cross-reacting (which would be worse performance than what seems to be likely for PCR tests), she would still be 97.6% likely to actually have Zika virus if her test were positive. Negative results in either situation are about 96% likely to rule out Zika virus. Of course, if she were given 1 of the least-sensitive PCR tests (suppose 50%), the predictive value of a positive test would remain high (95%) but would fall greatly for a negative test (31%). Because a negative test result would not rule out the possibility of Zika virus infection, prenatal surveillance for fetal abnormalities and newborn referrals to hearing, vision, and neurologic evaluations would still be warranted. In this situation, testing the woman has relevance primarily for public health surveillance.

Scenario 3: Intermediate Pretest Probability

Suppose a patient has only a 25% pretest probability of infection. Perhaps she had nonspecific symptoms 2 months ago, early in her pregnancy, after traveling briefly to Brazil. She has no other risk factors for Zika virus and lives a part of the United States with no local transmission. She is given the same well-performing IgM ELISA as the woman from Minneapolis. In this case, a positive test signals an 86.8% likelihood of infection; it is likely but uncertain that she has been infected with Zika virus in the past several months, and her travel history may make it unlikely that infection occurred before her pregnancy (if it occurred). A negative result excludes Zika virus with near certainty. Suppose, however, that she were instead given a PCR test, which her low level of viremia this long after putative infection would render insensitive (perhaps 20%) but otherwise performs the same as before. Now, a positive test is only 57% likely to signal infection and a negative test is 78% likely to signal noninfection.

Even at a higher likelihood of infection, intermediate risks are hard to interpret. Suppose the patient had a 50% pretest probability of infection; maybe she stayed a few weeks in Brazil and her symptoms are ambiguous but more consistent with Zika virus. Now, her well-performing ELISA returns positive and negative predictive values of 95% and 99%, respectively. Her poorly advised PCR test returns 80% and 54% positive and negative predictive values, respectively. Also, suppose she is given a less well-performing ELISA, which is plausible given the relatively limited information about the performance of particular tests on the market. If her test has 70% sensitivity and specificity, the approximate range of some tests on the market,[17] her positive and negative predictive value drop to 70% each.