Pre-test probability is high in someone with typical symptoms of covid-19, an occupational risk of exposure, and working in a high prevalence region, and negative test results can therefore be misleading. The sensitivity can be compromised here. I.e. The more sensitive a test, the fewer “false-negative” results it produces. Figure 1 shows how a clinician’s thinking about a patient’s probability should shift, based on either a positive or negative test result for covid-19. Although few if any tests succeed in diagnosing disease correctly 100% of the time, most tests produce only a small proportion of false-positive or false-negative results. This article is made freely available for use in accordance with BMJ's website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. Across the world there is a clamour for covid-19 testing, with Tedros Adhanom Ghebreyesus, director general of the World Health Organization, encouraging countries to “test, test, test.”1 The availability of the complete genome of covid-19 early in the epidemic facilitated development of tests to detect viral RNA.2 Multiple assays with different gene targets have been developed using reverse transcriptase polymerase chain reaction (RT-PCR).3 These viral RNA tests use samples usually obtained from the respiratory tract by nasopharyngeal swab, to detect current infections. How do you explain covid-19 test results to patients? She is admitted and placed in isolation on droplet precautions. [3], (See Diagnostic Testing Accuracy Table 1). Picture a bull’s-eye target with darts all clustered together – but not in the centre ring – and you see what a precise but inaccurate method produces: the method can be counted on to reach the same target over and over again but the target may not be the one intended. Specificity As both sensitivity and specificity are proportions, their confidence intervals can be computed using the standard methods for proportions2. No test gives a 100% accurate result; tests need to be evaluated to determine their sensitivity and specificity, ideally by comparison with a “gold standard.” The lack of such a clear-cut “gold-standard” for covid-19 testing makes evaluation of test accuracy challenging. PhD A false-negative result fails to identify disease states even though they are present.

In the case where, the number of excellent candidates and poor performers are equal, if any one of the factors, Sensitivity or Specificity is high then Accuracy will bias towards that highest value. This amount of variability does not usually detract from the test’s value as it is taken into account. A test’s sensitivity becomes particularly important when you are seeking to exclude a dangerous disease. Author contributorship: JW JB and PW contributed to the conception of the work, JW ran the searches and wrote the first draft of the paper with assistance from JB. The provider found that a total of 384 individuals actually had the disease, but how accurate was the blood test? While positive tests for covid-19 are clinically useful, negative tests need to be interpreted with caution, taking into account the pre-test probability of disease. When a test method is precise, the amount of random variation is small. ROC tells us, how many mistakes are we making to identify all the positives. 2009 May-Jun; A total of 1,000 individuals had their blood tested. [5] False positives are a consideration through measurements of specificity and PPV. A test method can be precise (reliably reproducible in what it measures) without being accurate (actually measuring what it is supposed to measure), or vice versa. How did this alter with the results of tests?


This amount of variability does not usually detract from the test’s value as it is taken into account. Interpretation of a test result depends not only on the characteristics of the test itself but also on the pre-test probability of disease. Although a test that is 100% accurate and 100% precise is the ideal, in reality, this is impossible.

Understanding that other diagnostic test data techniques do exist (e.g., receiver operating characteristic curves), the topics in this article represent essential starting points for healthcare providers. It is therefore safest for this GP with strongly suggestive symptoms to self-isolate in line with guidelines for covid-19, even though his test results are negative. The information above allows us to enter the values in the table below. If we consider all the possible threshold values and the corresponding specificity and sensitivity rate what will be the final model accuracy. For example, a certain test may have proven to be 90% sensitive. Let’s calculate the sensitivity, specificity, PPV, NPV, LR+, and LR-. A diagnostic test’s validity, or its ability to measure what it is intended to, is determined by sensitivity and specificity. In general, during this pandemic, pre-test probabilities of covid-19 will be high, particularly in high prevalence secondary care settings.

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