1. Epidemiology and Global Health
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Efficacy profile of the CYD-TDV dengue vaccine revealed by Bayesian survival analysis of individual-level Phase III data

  1. Daniel J Laydon  Is a corresponding author
  2. Ilaria Dorigatti
  3. Wes R Hinsley
  4. Gemma L Nedjati-Gilani
  5. Laurent Coudeville
  6. Neil M Ferguson
  1. Imperial College London, United Kingdom
  2. Sanofi-Pasteur, France
Research Article
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Cite this article as: eLife 2021;10:e65131 doi: 10.7554/eLife.65131

Abstract

Background: Sanofi-Pasteur’s CYD-TDV is the only licensed dengue vaccine. Two phase III trials showed higher efficacy in seropositive than seronegative recipients. Hospital follow-up revealed increased hospitalisation in 2-5-year-old vaccinees, where serostatus and age effects were unresolved.

Methods: We fit a survival model to individual-level data from both trials, including year one of hospital follow-up. We determine efficacy by age, serostatus, serotype and severity, and examine efficacy duration and vaccine action mechanism.

Results: Our modelling indicates that vaccine-induced immunity is long-lived in seropositive recipients, and therefore that vaccinating seropositives gives higher protection than two natural infections. Long-term increased hospitalisation risk outweighs short-lived immunity in seronegatives. Independently of serostatus, transient immunity increases with age, and is highest against serotype 4. Benefit is higher in seropositives, and risk enhancement is greater in seronegatives, against hospitalised disease than febrile disease.

Conclusions: Our results support vaccinating seropositives only. Rapid diagnostic tests would enable viable “screen-then-vaccinate” programs. Since CYD-TDV acts as a silent infection, long-term safety of other vaccine candidates must be closely monitored.

Funding: Bill and Melinda Gates Foundation, National Institute for Health Research, UK Medical Research Council, Wellcome Trust.

Data availability

Qualified researchers may request access to patient level data and related study documents including the clinical study report, study protocol with any amendments, blank case report form, statistical analysis plan, and dataset specifications. Patient level data will be anonymized and study documents will be redacted to protect the privacy of trial participants. Further details on Sanofi's data sharing criteria, eligible studies, and process for requesting access can be found at: https://www.clinicalstudydatarequest.com. Additional details of the trial designs and data can be found in Sridhar et al (NEJM 2018).All model code is available at https://github.com/dlaydon/DengVaxSurvival, which is linked to in the manuscript. This repository also contains simulated data, generated to closely match the trial data, giving comparable case numbers across strata. When our model is fitted to the simulated data, the resulting parameter estimates closely approximate the results presented in this analysis.

Article and author information

Author details

  1. Daniel J Laydon

    Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
    For correspondence
    d.laydon@imperial.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4270-3321
  2. Ilaria Dorigatti

    Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9959-0706
  3. Wes R Hinsley

    Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
    Competing interests
    No competing interests declared.
  4. Gemma L Nedjati-Gilani

    Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, United Kingdom
    Competing interests
    No competing interests declared.
  5. Laurent Coudeville

    Sanofi-Pasteur, Sanofi-Pasteur, Lyon, France
    Competing interests
    Laurent Coudeville, Laurent Coudeville is employed by Sanofi-Pasteur.
  6. Neil M Ferguson

    MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
    Competing interests
    No competing interests declared.

Funding

Bill and Melinda Gates Foundation

  • Daniel J Laydon
  • Gemma L Nedjati-Gilani
  • Neil M Ferguson

National Institute for Health Research (NIHR: PR-OD-1017-20002)

  • Daniel J Laydon
  • Gemma L Nedjati-Gilani
  • Neil M Ferguson

Medical Research Council (MR/R015600/1)

  • Daniel J Laydon
  • Ilaria Dorigatti
  • Wes R Hinsley
  • Gemma L Nedjati-Gilani
  • Neil M Ferguson

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Ben S Cooper, Mahidol University, Thailand

Publication history

  1. Received: November 24, 2020
  2. Accepted: June 29, 2021
  3. Accepted Manuscript published: July 2, 2021 (version 1)
  4. Version of Record published: July 29, 2021 (version 2)
  5. Version of Record updated: August 4, 2021 (version 3)

Copyright

© 2021, Laydon et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Mark Ferris et al.
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    Background:

    Respiratory protective equipment recommended in the UK for healthcare workers (HCWs) caring for patients with COVID-19 comprises a fluid-resistant surgical mask (FRSM), except in the context of aerosol generating procedures (AGPs). We previously demonstrated frequent pauci- and asymptomatic severe acute respiratory syndrome coronavirus 2 infection HCWs during the first wave of the COVID-19 pandemic in the UK, using a comprehensive PCR-based HCW screening programme (Rivett et al., 2020; Jones et al., 2020).

    Methods:

    Here, we use observational data and mathematical modelling to analyse infection rates amongst HCWs working on ‘red’ (coronavirus disease 2019, COVID-19) and ‘green’ (non-COVID-19) wards during the second wave of the pandemic, before and after the substitution of filtering face piece 3 (FFP3) respirators for FRSMs.

    Results:

    Whilst using FRSMs, HCWs working on red wards faced an approximately 31-fold (and at least fivefold) increased risk of direct, ward-based infection. Conversely, after changing to FFP3 respirators, this risk was significantly reduced (52–100% protection).

    Conclusions:

    FFP3 respirators may therefore provide more effective protection than FRSMs for HCWs caring for patients with COVID-19, whether or not AGPs are undertaken.

    Funding:

    Wellcome Trust, Medical Research Council, Addenbrooke’s Charitable Trust, NIHR Cambridge Biomedical Research Centre, NHS Blood and Transfusion, UKRI.

    1. Epidemiology and Global Health
    Andria Mousa et al.
    Research Article

    Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focussed on high-income settings.

    Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys we explored how contact characteristics (number, location, duration and whether physical) vary across income settings.

    Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age-groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income-strata on the frequency, duration and type of contacts individuals made.

    Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions.

    Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).