Estimated dates of detectable infection (EDDIs) as an improvement upon Fiebig staging for HIV infection dating

Abstract

Abstract Accurate methods for determining the duration of HIV infection at the individual level are valuable in many settings, including many critical research studies and in clinical practice (especially for acute infection). Since first published in 2003, the ‘Fiebig staging system’ has been used as the primary way of classifying early HIV infection into five sequential stages based on HIV test result patterns in newly diagnosed individuals. However, Fiebig stages can only be assigned to individuals who produce both a negative and a positive test result on the same day, on specific pairs of tests of varying ‘sensitivity’. Further, in the past 16 years HIV-testing technology has evolved substantially, and three of the five key assays used to define Fiebig stages are no longer widely used. To address these limitations, we developed an improved and more general framework for estimating the duration of HIV infection by interpreting any combination of diagnostic test results, whether obtained on single or multiple days, into an estimated date of detectable infection, or EDDI. A key advantage of the EDDI method over Fiebig staging is that it allows for the generation of a point estimate, as well as an associated credibility interval for the date of first detectable infection, for any person who has at least one positive and one negative HIV test of any kind. The tests do not have to be run on the same day; they do not have to be run during the acute phase of infection and the method does not rely on any special pairing of tests to define ‘stages’ of infection. The size of the interval surrounding the EDDI (and therefore the precision of the estimate itself) depends largely on the length of time between negative and positive tests. The EDDI approach is also flexible, seamlessly incorporating any assay for which there is a reasonable diagnostic delay estimate. An open-source, free online tool includes a user-updatable curated database of published diagnostic delays. HIV diagnostics have evolved tremendously since that original publication more than 15 years ago, and it is time to similarly evolve the methods used to estimate timing of infection. The EDDI method is a flexible and rigorous way to estimate the timing of HIV infection in a continuously evolving diagnostic landscape.