Evidence map›Paper›PMID 39989916›Full record

ArticleHealth systems (Basingstoke, England)2025

Improving COVID-19 vaccination centre operation through computer modelling and simulation.

Richard M Wood, Simon J Moss, Ben J Murch, Chris Davies, Christos Vasilakis

Abstract read
In one paragraph

Article in Health systems (Basingstoke, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Richard M WoodModelling and Analytics, UK National Health Service (BNSSG ICB), Bristol, UK.ORCID https://orcid.org/0000-0002-3476-395X
Simon J MossModelling and Analytics, UK National Health Service (BNSSG ICB), Bristol, UK.ORCID https://orcid.org/0000-0003-3220-1838
Ben J MurchModelling and Analytics, UK National Health Service (BNSSG ICB), Bristol, UK.ORCID https://orcid.org/0000-0002-3925-9939
Chris DaviesModelling and Analytics, UK National Health Service (BNSSG ICB), Bristol, UK.
Christos VasilakisSchool of Management, University of Bath, Bath, UK.ORCID https://orcid.org/0000-0002-0391-0910

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mass vaccination has provided a route out of the COVID-19 pandemic in a way that social restrictions can be safely eased. For many countries, dedicated vaccination centres have been key to that effort. However, with no directly comparable historical experience there has been little information to guide the operational management and initial configuration of these sites. This paper provides an account of how, early in the mass vaccination effort, Operational Research has been a valuable asset in supporting management decisions at two major vaccination centres in the UK. We first describe a conceptual pathway model representing the key stages of the vaccination process, from registration to clinical assessment, vaccination, and observation. An approximation using discrete event simulation is then presented. On application, we report on its use in influencing the initial setup of one site, with model outputs directly setting the daily number of patient bookings. For the same site, we reveal how analysis has informed a significant operational shift in combining two key activities on the vaccination pathway (clinical assessment and vaccination). Finally, we describe how, at a second site, modelling has examined pathway stability, in terms of resilience to unforeseen "shocks" such as delayed arrivals and staff unavailability.

Indexed as

CoronavirusCOVID-19mass vaccinationsimulation modellingvaccination centre

Identifiers

PMID39989916
PMCPMC11843651

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.