Summary Background Knowledge regarding the risks associated with Zika virus (ZIKV) infections in pregnancy has relied on individual studies with relatively small sample sizes and variable risk estimates of adverse outcomes, or on surveillance or routinely collected data. Using data from the Zika Brazilian Cohorts Consortium, this study aims, to estimate the risk of adverse outcomes among offspring of women with RT-PCR-confirmed ZIKV infection during pregnancy and to explore heterogeneity between studies. Methods We performed an individual participant data meta-analysis of the offspring of 1548 pregnant women from 13 studies, using one and two-stage meta-analyses to estimate the absolute risks. Findings Of the 1548 ZIKV-exposed pregnancies, the risk of miscarriage was 0.9%, while the risk of stillbirth was 0.3%. Among the pregnancies with liveborn children, the risk of prematurity was 10,5%, the risk of low birth weight was 7.7, and the risk of small for gestational age (SGA) was 16.2%. For other abnormalities, the absolute risks were: 2.6% for microcephaly at birth or first evaluation, 4.0% for microcephaly at any time during follow-up, 7.9% for neuroimaging abnormalities, 18.7% for functional neurological abnormalities, 4.0% for ophthalmic abnormalities, 6.4% for auditory abnormalities, 0.6% for arthrogryposis, and 1.5% for dysphagia. This risk was similar in all sites studied and in different socioeconomic conditions, indicating that there are not likely to be other factors modifying this association. Interpretation This study based on prospectively collected data generates the most robust evidence to date on the risks of congenital ZIKV infections over the early life course. Overall, approximately one-third of liveborn children with prenatal ZIKV exposure presented with at least one abnormality compatible with congenital infection, while the risk to present with at least two abnormalities in combination was less than 1.0%. Funding National Council for Scientific and Technological Development - Brazil (Conselho Nacional de Desenvolvimento Científico e Tecnológico – CNPq); Wellcome Trust and the United Kingdom's Department for International Development; European Union's Horizon 2020 research and innovation program; Medical Research Council on behalf of the Newton Fund and Wellcome Trust; National Institutes of Health/National Institute of Allergy and Infectious Diseases; Foundation Christophe et Rodolphe Mérieux; Coordination for the improvement of Higher Education Personnel (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Capes); Ministry of Health of Brazil; Brazilian Department of Science and Technology; Foundation of Research Support of the State of São Paulo (Fundação de Amparo à Pesquisa do Estado de São Paulo – FAPESP); Foundation of Research Support of the State of Rio de Janeiro (Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro – FAPERJ); Foundation of Support for Research and Scientific and Technological Development of Maranhão; Evandro Chagas Institute/Brazilian Ministry of Health (Instituto Evandro Chagas/Ministério da Saúde); Foundation of Research Support of the State of Goiás (Fundação de Amparo à Pesquisa do Estado de Goiás – FAPEG); Foundation of Research Support of the State of Rio Grande do Sul (Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul – FAPERGS); Foundation to Support Teaching, Research and Assistance at Hospital das Clínicas, Faculty of Medicine of Ribeirão Preto (Fundação de Apoio ao Ensino, Pesquisa e Assistência do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto); São Paulo State Department of Health (Secretaria de Saúde do Estado de São Paulo); Support Foundation of Pernambuco Science and Technology (Fundação de Amparo à Ciência e Tecnologia de Pernambuco – FACEPE).

6th February 2023 • comment

In this paper the authors describe an altmetrics-based framework which allows the identification of specialists and important research in specific research scenarios.

1st October 2019 • comment

The authors present and show a new tool that can detect endemic and epidemic viruses in different mosquito species in an epidemic context. This fast and low-cost method can be suggested as a novel epidemiological surveillance tool to identify circulating arboviruses.

27th September 2019 • comment

In this study, the authors developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype).

8th May 2019 • comment

This study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region.

7th March 2019 • comment