It depends on properties of the test: this isn’t enough information for an answer.
If the test is failing for reasons that are independent from one test to another (say, there was a manufacturing defect in one test), then you’d have independent probabilities of failure, and the chance would be (1-0.98)(1-0.98) = ~0.04% of both being wrong (i.e., about 2% of 2%).
But if they’re wrong for some underlying reason (say, you aren’t exposing the specific antigen it’s testing for), then one failing would ensure the other fails, and it’d still be 2%.
More likely, both failure modes are possible, and the probability is somewhere between these extremes.
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