Evidence map›Paper›PMID 37061313›Full record

ArticleThe Lancet. Global health2023

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

Daniel J Laydon, Simon Cauchemez, Wes R Hinsley, Samir Bhatt, Neil M Ferguson

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Global health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 3 countries.

Daniel J LaydonMRC 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 CauchemezMathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Université Paris Cité, CNRS UMR2000, Paris, France.
Wes R HinsleyMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK.
Samir BhattMRC 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 FergusonMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London, London, UK.
Imperial College London · GBInstitut Pasteur · FRLondon Centre for Neglected Tropical Disease Research · GB

Funding

Department of Health NIHR200908Department of Health PR-OD-1017-20002Medical Research Council MR/R015600/1
6 · The paper itself

Abstract

backgroundSeveral 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.

methodsUsing 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.

findingsThe 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.

interpretationSubstantial 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.

fundingUK 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.

Indexed as

EpidemicsMiddle East Respiratory Syndrome CoronavirusDisease OutbreaksHealth PersonnelHumansVaccination

Identifiers

PMID37061313
PMCPMC10101755
OpenAlexW4365519901

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.