Tuesday, November 18, 2014

Ebola Tests: Sensitivity and Specificity

Yesterday's headlines on USA Today included one that stated "Nebraska Patient Cases Raises Questions about Ebola Test."  The reason for this is the fact that the Nebraska patient was a physician treating Ebola patients who came down with symptoms and was tested and found not to be Ebola positive before other clinicians eventually realized (and found in a later test) that the man in question did have Ebola.  If the physician had been treated earlier, it is possible that his outcome--being brought back to the US and treated--may have been different from the unfortunate death he suffered.

I'd like to comment on this because it raises some really important issues about diagnostic tests.  I would have expected to find some previous writing on this, but I do not.  So here it goes.

People either have a condition or do not.  We refer to those who have the condition as positive and those who dont' as negative.  Sometimes it is good to be "positive."  With the Ebola virus, it is obvious that being positive is a very bad thing.

Test results are also positive or negative.  (Some tests are uncertain, but for the time being we will ignore that.)  So, the result at the end of a diagnostic test suggests that a person either has or does not have a condition.

What makes this most interesting is the fact that there are some people who are truly positive and for which the test identifies the person as positive.  Similarly, there are some people who are negative and whom the test identifies as negative.  These are both desirable outcomes.

However, there are also two other groups.  There are some people who are positive whom the test incorrectly identifies as negative.  And there are some people who are negative whom the test incorrectly identifies as positive.  

A test's ability to correctly identify those who are positive as positive is called sensitivity.  A test's ability to correctly identify those who are negative as negative is called specificity.

In different situations, clinicians and policy makes focus on either sensitivity or specificity.  Sometimes it is important not to over identify cases.  If the consequences of being positive are fairly small, there will be future attempts to diagnose, and further identification and treatment is costly, we can focus on making sure to identify negatives properly--specificity.  Or if there are strong negative connotations and stigmas associated with being positive it can be important to correctly identify negatives.

However there are other cases in which failing to identify a positive case can be deadly.  This is true with Ebola.  This is why in other cases sensitivity is critical.  This does not mean that there should not be concerns about specificity.  If we had a lot of people mis-identified as positive this would require an enormous amount of resources and there may be side effects of the treatment.

The main "question" I think we should asking about the Ebola test is whether there is a way to develop a test that is more sensitive.  And quickly.  And if the government can support that and someone can find it, there may be a profit to be made from an innovation for humanity.  


  1. Great article! I would also consider the disease prevalence and the signs and symptoms of the patient when deciding on whether to treat or not; the clinical diagnosis of some conditions can have a high positive predictive value (PPV) depending on the epidemiological characteristics of the population. In high endemic areas and in cases where mortality rates are high for certain diseases, I would like to see some minimum criteria for empiric treatment or some basic interventions (such as fluid and electrolyte replacements, blood pressure maintenance) for Ebola. In these endemic areas, fever may also be a symptom for other diseases such as typhoid or malaria; but given the high mortality rates of Ebola and the delay in test results from symptom onset, a minimum diagnostic criteria with basic intervention support would be a wise clinical decision to decrease preventable mortality.

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