Dataset Information

Detection of post-vaccination enhanced dengue virus infection in macaques: An improved model for early assessment of dengue vaccines.

ABSTRACT: The need for improved dengue vaccines remains since the only licensed vaccine, Dengvaxia, shows variable efficacy depending on the infecting dengue virus (DENV) type, and increases the risk of hospitalization for severe dengue in children not exposed to DENV before vaccination. Here, we developed a tetravalent dengue purified and inactivated vaccine (DPIV) candidate and characterized, in rhesus macaques, its immunogenicity and efficacy to control DENV infection by analyzing, after challenge, both viral replication and changes in biological markers associated with dengue in humans. Although DPIV elicited cross-type and long-lasting DENV-neutralizing antibody responses, it failed to control DENV infection. Increased levels of viremia/RNAemia (correlating with serum capacity at enhancing DENV infection in vitro), AST, IL-10, IL-18 and IFN-γ, and decreased levels of IL-12 were detected in some vaccinated compared to non-vaccinated monkeys, indicating the vaccination may have triggered antibody-dependent enhancement of DENV infection. The dengue macaque model has been considered imperfect due to the lack of DENV-associated clinical signs. However, here we show that post-vaccination enhanced DENV infection can be detected in this model when integrating several parameters, including characterization of DENV-enhancing antibodies, viremia/RNAemia, and biomarkers relevant to dengue in humans. This improved dengue macaque model may be crucial for early assessment of efficacy and safety of future dengue vaccines.

SUBMITTER: Borges MB

PROVIDER: S-EPMC6497418 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Detection of post-vaccination enhanced dengue virus infection in macaques: An improved model for early assessment of dengue vaccines.

Borges Maria Beatriz MB Marchevsky Renato Sergio RS Carvalho Pereira Renata R da Silva Mendes Ygara Y Almeida Mendes Luiz Gustavo LG Diniz-Mendes Leonardo L Cruz Michael A MA Tahmaoui Ouafaâ O Baudart Sébastien S Freire Marcos M Homma Akira A Schneider-Ohrum Kirsten K Vaughn David W DW Vanloubbeeck Yannick Y Lorin Clarisse C Malice Marie-Pierre MP Caride Elena E Warter Lucile L

PLoS pathogens 20190422 4

The need for improved dengue vaccines remains since the only licensed vaccine, Dengvaxia, shows variable efficacy depending on the infecting dengue virus (DENV) type, and increases the risk of hospitalization for severe dengue in children not exposed to DENV before vaccination. Here, we developed a tetravalent dengue purified and inactivated vaccine (DPIV) candidate and characterized, in rhesus macaques, its immunogenicity and efficacy to control DENV infection by analyzing, after challenge, bot ...[more]

PMID: 31009499

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Project description:BackgroundVaccine confidence is described as a belief that vaccines are effective, safe, and part of a trustworthy health system. The objective of this study was to develop and validate an Arabic tool to evaluate confidence in the received coronavirus disease 2019 (COVID-19) vaccines (ARAB-VAX-CONF).MethodsThe research team developed the ARAB-VAX-CONF based on three areas specified by the Centers for Disease Control and Prevention (CDC): confidence in vaccine effectiveness, confidence in vaccine safety, and confidence in the healthcare system. The analysis includes data from 406 eligible vaccinated persons (≥ 18 years). Cronbach's alpha was used to measure internal consistency, while convergent, discriminant, exploratory, and confirmatory factor analyses were used to verify construct validity.ResultsA total of 406 adults were recruited, with a mean age of 33.0 ± 12.2 years. A total of 63.1% were males, 56.7% were married, 21.9% had chronic conditions, 93.3% were nonsmokers, and 39.6% were obligated to obtain vaccines. The three domains of the scale met the criterion of internal consistency (Cronbach's alpha > 0.7). Convergent validity was identified by the significant inter-item and item-mean score of the domain correlation (P < 0.001). Discriminant validity was reported as the inter-factor correlation matrix (< 0.7). The Kaiser-Meyer-Olkin sampling adequacy measure was 0.80, and Bartlett's sphericity test was significant (P < 0.001). Exploratory factor analysis indicated that the scale could be summarized into three factors. Confirmatory factor analysis confirmed the adequate psychometric properties and fit with observed data (root-mean-square error of approximation = 0.08, comparative fit index = 0.945, Tucker-Lewis index = 0.924, standardized root-mean-square residual = 0.086, normed fit index = 0.918, and goodness-of-fit index = 0.909).ConclusionsThe ARAB-VAX-CONF developed in this study is valid and reliable for assessing confidence in vaccine effectiveness, safety, and confidence in the healthcare system. The ARAB-VAX-CONF can support decision-makers in addressing the gap in vaccine confidence among various populations.

Project description:BackgroundIdentifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app.MethodsWe conducted a prospective observational study in 1,072,313 UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (N=362,770) (other than local symptoms at injection site) and were tested for SARS-CoV-2 (N=14,842), aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models considering UK testing criteria.FindingsDifferentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. Most of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue).InterpretationPost-vaccination symptoms per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2 or quarantining, to prevent community spread.FundingUK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Chronic Disease Research Foundation, Zoe Limited.

Dataset Information

Detection of post-vaccination enhanced dengue virus infection in macaques: An improved model for early assessment of dengue vaccines.

Publications

Detection of post-vaccination enhanced dengue virus infection in macaques: An improved model for early assessment of dengue vaccines.

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