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How mathematical modelling can inform outbreak response vaccination.
- Source :
-
BMC infectious diseases [BMC Infect Dis] 2024 Dec 01; Vol. 24 (1), pp. 1371. Date of Electronic Publication: 2024 Dec 01. - Publication Year :
- 2024
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Abstract
- Mathematical models are established tools to assist in outbreak response. They help characterise complex patterns in disease spread, simulate control options to assist public health authorities in decision-making, and longer-term operational and financial planning. In the context of vaccine-preventable diseases (VPDs), vaccines are one of the most-cost effective outbreak response interventions, with the potential to avert significant morbidity and mortality through timely delivery. Models can contribute to the design of vaccine response by investigating the importance of timeliness, identifying high-risk areas, prioritising the use of limited vaccine supply, highlighting surveillance gaps and reporting, and determining the short- and long-term benefits. In this review, we examine how models have been used to inform vaccine response for 10 VPDs, and provide additional insights into the challenges of outbreak response modelling, such as data gaps, key vaccine-specific considerations, and communication between modellers and stakeholders. We illustrate that while models are key to policy-oriented outbreak vaccine response, they can only be as good as the surveillance data that inform them.<br />Competing Interests: Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: KAMG reports speaker fees from Sanofi Pasteur outside the submitted work. All other authors have no conflicts of interest to declare. MS, A-MH, EG, HK, J-HK, HF, MJ, AP , CLT, and KAMG received funding from Gavi, BMGF and/or the Wellcome Trust via VIMC during the course of the study.<br /> (© 2024. The Author(s).)
Details
- Language :
- English
- ISSN :
- 1471-2334
- Volume :
- 24
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- BMC infectious diseases
- Publication Type :
- Academic Journal
- Accession number :
- 39617902
- Full Text :
- https://doi.org/10.1186/s12879-024-10243-0