Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study.


Journal

The Lancet. Global health
ISSN: 2214-109X
Titre abrégé: Lancet Glob Health
Pays: England
ID NLM: 101613665

Informations de publication

Date de publication:
05 2023
Historique:
received: 27 04 2022
revised: 08 02 2023
accepted: 09 02 2023
medline: 18 4 2023
entrez: 15 4 2023
pubmed: 16 4 2023
Statut: ppublish

Résumé

Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers. Using data from the 2013-14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies. The spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but that of national-level campaigns is preserved unless triggers have high thresholds. Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating only health-care workers, underlining the need for countries at risk of outbreaks to stockpile vaccines when available. UK Medical Research Council, UK National Institute for Health Research, UK Research and Innovation, UK Academy of Medical Sciences, The Novo Nordisk Foundation, The Schmidt Foundation, and Investissement d'Avenir France.

Sections du résumé

BACKGROUND
Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers.
METHODS
Using data from the 2013-14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies.
FINDINGS
The spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but that of national-level campaigns is preserved unless triggers have high thresholds.
INTERPRETATION
Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating only health-care workers, underlining the need for countries at risk of outbreaks to stockpile vaccines when available.
FUNDING
UK Medical Research Council, UK National Institute for Health Research, UK Research and Innovation, UK Academy of Medical Sciences, The Novo Nordisk Foundation, The Schmidt Foundation, and Investissement d'Avenir France.

Identifiants

pubmed: 37061313
pii: S2214-109X(23)00117-1
doi: 10.1016/S2214-109X(23)00117-1
pmc: PMC10101755
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e759-e769

Subventions

Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : Department of Health
ID : PR-OD-1017-20002
Pays : United Kingdom
Organisme : Department of Health
ID : NIHR200908
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests DJL, WRH, SB, and NMF report grants from the UK Medical Research Council (MRC) and the Department for International Development. DJL, SB, and NMF report grants from the UK National Institute for Health and Care Research (NIHR). SC reports grant funding from the Investissement d'Avenir programme, Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases programme, and INCEPTION project, outside of the submitted work. SB reports grant funding from Novo Nordisk Foundation, the Danish National Research Foundation, and The Eric & Wendy Schmidt Fund for Strategic Innovation, outside of the submitted work. NMF reports grants from UK Research and Innovation; Community Jameel; Gavi, the Vaccine Alliance; Janssen Pharmaceuticals; and the Bill & Melinda Gates Foundation, outside of the submitted work. Additionally, NMF reports consulting fees for the World Bank Group (ceased in 2019); payment for sitting on a grant panel and an advisory board for the Wellcome Trust; travel expenses for WHO meetings; and sitting on an advisory board for Takeda in relation to their dengue vaccine, for which no honoraria, gifts, or expenses of any kind were received. NMF is a senior editor for the journal eLife. All other authors declare no competing interests.

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Auteurs

Daniel J Laydon (DJ)

MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK. Electronic address: d.laydon@imperial.ac.uk.

Simon Cauchemez (S)

Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR2000, Paris, France.

Wes R Hinsley (WR)

MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK.

Samir Bhatt (S)

MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK; Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.

Neil M Ferguson (NM)

MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK.

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Classifications MeSH