• Clin. Infect. Dis. · Apr 2018

    Virus and Antibody Dynamics in Travelers With Acute Zika Virus Infection.

    • Luisa Barzon, Elena Percivalle, Monia Pacenti, Francesca Rovida, Maurizio Zavattoni, Paola Del Bravo, Anna Maria Cattelan, Giorgio Palù, and Fausto Baldanti.
    • Department of Molecular Medicine, University of Padova, Italy.
    • Clin. Infect. Dis. 2018 Apr 3; 66 (8): 1173-1180.

    BackgroundTo improve our understanding of the natural history of Zika virus (ZIKV) infection in humans, we described the dynamics of ZIKV RNA shedding in different body fluids and antibody responses in patients with acute infection.MethodsTwenty-nine adults with travel-associated infection and 1 case of sexual transmission were enrolled and followed up with weekly ZIKV RNA testing in blood, urine, saliva, and semen samples and antibody testing.ResultsZIKV RNA was detected in plasma, urine, and saliva of 57%, 93.1%, and 69.2% of participants, with estimated median times to clearance of 11.5 days (interquartile range [IQR] 6-24 days), 24 days (IQR, 17-34), and 14 days (IQR, 8-31), respectively. In 2 pregnant women, ZIKV RNA persisted in blood until delivery of apparently healthy infants. ZIKV RNA was detected in semen of 5 of 10 tested men; median time to clearance was 25 days (IQR 14-29), and the longest time of shedding in semen was 370 days. In flavivirus-naive patients, the median times to detection of ZIKV nonstructural protein 1 (NS1)-specific immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies were estimated as 8 days (IQR, 5-15 days) and 17 days (IQR, 12-26 days), respectively. ZIKV NS1 IgM antibodies were undetectable in patients with previous dengue.ConclusionsProlonged viremia and ZIKV RNA shedding in urine, saliva, and semen occur frequently in patients with acute ZIKV infection. At the time of diagnosis, about half of patients are ZIKV IgM negative. ZIKV NS1 IgM antibodies remain undetectable in patients with previous dengue. Estimates of the times to viral clearance and seroconversion are useful to optimize diagnostic algorithms.

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