Quantification of the time-varying epidemic growth rate and of the delays between symptom onset and presenting to healthcare for the mpox epidemic in the UK in 2022.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
26 08 2024
Historique:
received: 04 11 2023
accepted: 19 07 2024
medline: 27 8 2024
pubmed: 27 8 2024
entrez: 26 8 2024
Statut: epublish

Résumé

The mpox epidemic in the UK began in May 2022, with rates of new cases unexpectedly and rapidly declining during August 2022. Interpreting trends in infection requires disentangling the underlying growth rate of cases from the delay from symptom onset to presenting to healthcare. We developed a nowcasting Bayesian method which incorporates time-varying delays (EpiLine) to quantify the changes in the delay from symptom onset to healthcare presentation and the underlying mpox growth rate over the period May-August 2022 in the UK. We show that the mean delay between symptom onset and healthcare presentation for mpox in the UK decreased from 22 days in early May 2022 to 10 days by early June and 8 days in August 2022. When we account for these dynamic delays, the time-varying growth rate declined gradually and continuously in the UK during the May-August 2022 period. Not accounting for varying time delays would have incorrectly characterised the growth rate by a sharp increase followed by a rapid decline in mpox cases. Our results highlight the importance of correctly quantifying the delay between symptom onset to healthcare presentation when characterising the epidemic growth of mpox in the UK. The gradual reduction in the rate of epidemic spread, which pre-dated the vaccine roll-out, is consistent with gradual risk reduction or acquired immunity amongst the highest risk individuals. Our study highlights the need for public health agencies to record the delays from symptom onset to healthcare presentation early in an outbreak.

Identifiants

pubmed: 39187529
doi: 10.1038/s41598-024-68154-8
pii: 10.1038/s41598-024-68154-8
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

19755

Informations de copyright

© 2024. The Author(s).

Références

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Auteurs

Robert Hinch (R)

The Big Data Institute and the Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.

Jasmina Panovska-Griffiths (J)

The Big Data Institute and the Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK. jasmina.panovska-griffiths@ndph.ox.ac.uk.
The Queen's College, University of Oxford, Oxford, UK. jasmina.panovska-griffiths@ndph.ox.ac.uk.
UK Health Security Agency, London, UK. jasmina.panovska-griffiths@ndph.ox.ac.uk.

Thomas Ward (T)

UK Health Security Agency, London, UK.

Andre Charlett (A)

UK Health Security Agency, London, UK.

Nicholas Watkins (N)

UK Health Security Agency, London, UK.

Christophe Fraser (C)

The Big Data Institute and the Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.

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