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Title
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Challenges in diagnosing Zikaexperiences from a reference laboratory in a non-endemic setting
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Author
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Abstract
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| Diagnosing a patient with Zika infection is not always straightforward. Here, we aim to describe our data collected from December 2015 to December 2017 and discuss the implemented algorithm and diagnostic challenges we encountered. At the National Reference Center for Arboviruses at the Institute of Tropical Medicine, Antwerp, Belgium (ITM), a commercial Zika virus (ZIKV) enzyme-linked immunosorbent assay (ELISA) detecting immunoglobulin (Ig) M and IgG, a commercial ZIKV immunofluorescence assay (IFA) detecting IgM, and an in-house Zika virus neutralization test (VNT) were implemented. For molecular detection of ZIKV, an in-house and a commercial real-time RT-PCR were applied. An algorithm, adapted from the European Centre for Disease Control and Prevention (ECDC), was implemented. Between December 2015 and December 2017, we tested 6417 patients for ZIKV. Of those, according to ECDC criteria, 127 (2.0%) were classified as a confirmed Zika infection of which 39 by RT-PCR (0.6%), 15 (0.2%) as a probable Zika infection, 73 (1.1%) as undefined, and 65 (1.0%) as false positive reactions. Main challenges were the brief window for detection of IgM, cross-reactivity of antibodies with other flaviviruses and malaria, and low VNT titers in the acute phase. In RT-PCR negative samples, classification of ZIKV infection as recent or past proved difficult, when IgM was negative. The majority of patients could be classified according to ECDC criteria, though 1.1% of patients remained undefined and 1.0% were ELISA false positive reactions. Complementary IFA IgM was of added value to increase IgM detection rates. Improved serological assays and more longitudinal data on antibody kinetics are needed. |
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Language
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English
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Source (journal)
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European journal of clinical microbiology and infectious diseases. - Wiesbaden
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Publication
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Wiesbaden
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2019
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ISSN
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0934-9723
[print]
1435-4373
[online]
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DOI
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10.1007/S10096-019-03472-8
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Volume/pages
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38
:4
(2019)
, p. 771-778
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ISI
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000461781100021
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Pubmed ID
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30680570
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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