Background: We recently conducted a serosurvey of newly arrived workers in Taiwan from four Southeast Asian countries which revealed that 1% of the migrant workers had laboratory-confirmed recent Zika virus (ZIKV) infection. Taiwan, where Aedes mosquitoes are prevalent, has a close relationship with Southeast Asian countries. Up to now, 21 imported cases of ZIKV infection have been reported in Taiwan, but there has been no confirmed indigenous case. The aim of this serosurvey was to assess whether there was unrecognized ZIKV infections in Taiwan.
Methods: A total of 212 serum samples collected in a cross-sectional seroepidemiologic study conducted during the end of the 2015 dengue epidemic in Tainan, Taiwan, were analyzed. Anti-ZIKV IgM and IgG were tested using commercial enzyme-linked immunosorbent assays (ELISAs). Plaque reduction neutralization tests (PRNTs) for ZIKV and four dengue virus (DENV) serotypes were performed for samples with positive anti-ZIKV antibodies. A confirmed case of ZIKV infection was defined by ZIKV PRNT titer ratio ≥ 4 compared to four DENV serotypes.
Results: The mean age of the 212 participants was 54.0 years (standard deviation 13.7 years), and female was predominant (67.0%). Anti-ZIKV IgM and IgG were detected in 0 (0%) and 9 (4.2%) of the 212 participants, respectively. For the 9 samples with anti-ZIKV IgG, only 1 sample had 4 times higher ZIKV PRNT titers compared to PRNT titers against four dengue virus serotypes; this individual denied having traveled abroad.
Conclusions: The results suggest that undetected indigenous ZIKV transmission might have occurred in Taiwan. The findings also suggest that the threat of epidemic transmission of ZIKV in Taiwan does exist due to extremely low-level of herd immunity. Our study also indicates that serological tests for ZIKV-specific IgG remain a big challenge due to cross-reactivity, even in dengue non-endemic countries.
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http://dx.doi.org/10.1186/s12879-019-4491-4 | DOI Listing |
Virology
December 2024
The Centre for Infection and Immunity Studies, School of Medicine, Sun Yat-sen University, Shenzhen, Guangdong, 518107, China. Electronic address:
The knowledge on the life cycle of flaviviruses is still incomplete, and no direct-acting antivirals against their infections are clinically available. Herein, by screening via a Zika virus (ZIKV) replicon assay, we found that the N-terminus of NS2A exhibited great tolerance to the insertions of different split fluorescent proteins (split-FPs). Furthermore, both ZIKV and dengue virus encoding a split-FP-tagged NS2A propagated efficiently, and the split-FP-tagged ZIKVs had good genetic stability.
View Article and Find Full Text PDFPediatr Res
January 2025
Center for Genetic Medicine, Children's National Research Institute, Washington, DC, USA.
Background: Prenatally transmitted viruses can cause severe damage to the developing brain. There is unexplained variability in prenatal brain injury and postnatal neurodevelopmental outcomes, suggesting disease modifiers. Of note, prenatal Zika infection can cause a spectrum of neurodevelopmental disorders, including congenital Zika syndrome.
View Article and Find Full Text PDFJ Virol
December 2024
1Division of Gastroenterology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA.
Flaviviruses utilize the cellular endoplasmic reticulum (ER) for all aspects of their lifecycle. Genome replication and other viral activities take place in structures called replication organelles (ROs), which are invaginations induced in the ER membrane. Among the required elements for RO formation is the biogenesis of viral nonstructural proteins NS4A and NS4B.
View Article and Find Full Text PDFVirol Sin
December 2024
Department of Medical Laboratory Science, University of Maiduguri, College of Medical Sciences, P.M.B. 1069, Maiduguri, Nigeria. Electronic address:
Sci Rep
December 2024
Public Health and community medicine Department, Theodor Bilharz Research Institute, Helwan University, Cairo, Egypt.
Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to effictively mitigate their impact. This study applies advanced machine learning techniques to forecast outbreaks of Dengue, Chikungunya, and Zika, utilizing a comprehensive dataset comprising climate and socioeconomic data. Spanning the years 2007 to 2017, the dataset includes 1716 instances characterized by 27 distinct features.
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