Feasibility of measles and rubella vaccination programmes for disease elimination: a 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:
10 2022
Historique:
received: 16 09 2021
revised: 21 06 2022
accepted: 18 07 2022
pubmed: 17 9 2022
medline: 21 9 2022
entrez: 16 9 2022
Statut: ppublish

Résumé

Marked reductions in the incidence of measles and rubella have been observed since the widespread use of the measles and rubella vaccines. Although no global goal for measles eradication has been established, all six WHO regions have set measles elimination targets. However, a gap remains between current control levels and elimination targets, as shown by large measles outbreaks between 2017 and 2019. We aimed to model the potential for measles and rubella elimination globally to inform a WHO report to the 73rd World Health Assembly on the feasibility of measles and rubella eradication. In this study, we modelled the probability of measles and rubella elimination between 2020 and 2100 under different vaccination scenarios in 93 countries of interest. We evaluated measles and rubella burden and elimination across two national transmission models each (Dynamic Measles Immunisation Calculation Engine [DynaMICE], Pennsylvania State University [PSU], Johns Hopkins University, and Public Health England models), and one subnational measles transmission model (Institute for Disease Modeling model). The vaccination scenarios included a so-called business as usual approach, which continues present vaccination coverage, and an intensified investment approach, which increases coverage into the future. The annual numbers of infections projected by each model, country, and vaccination scenario were used to explore if, when, and for how long the infections would be below a threshold for elimination. The intensified investment scenario led to large reductions in measles and rubella incidence and burden. Rubella elimination is likely to be achievable in all countries and measles elimination is likely in some countries, but not all. The PSU and DynaMICE national measles models estimated that by 2050, the probability of elimination would exceed 75% in 14 (16%) and 36 (39%) of 93 modelled countries, respectively. The subnational model of measles transmission highlighted inequity in routine coverage as a likely driver of the continuance of endemic measles transmission in a subset of countries. To reach regional elimination goals, it will be necessary to innovate vaccination strategies and technologies that increase spatial equity of routine vaccination, in addition to investing in existing surveillance and outbreak response programmes. WHO, Gavi, the Vaccine Alliance, US Centers for Disease Control and Prevention, and the Bill & Melinda Gates Foundation.

Sections du résumé

BACKGROUND
Marked reductions in the incidence of measles and rubella have been observed since the widespread use of the measles and rubella vaccines. Although no global goal for measles eradication has been established, all six WHO regions have set measles elimination targets. However, a gap remains between current control levels and elimination targets, as shown by large measles outbreaks between 2017 and 2019. We aimed to model the potential for measles and rubella elimination globally to inform a WHO report to the 73rd World Health Assembly on the feasibility of measles and rubella eradication.
METHODS
In this study, we modelled the probability of measles and rubella elimination between 2020 and 2100 under different vaccination scenarios in 93 countries of interest. We evaluated measles and rubella burden and elimination across two national transmission models each (Dynamic Measles Immunisation Calculation Engine [DynaMICE], Pennsylvania State University [PSU], Johns Hopkins University, and Public Health England models), and one subnational measles transmission model (Institute for Disease Modeling model). The vaccination scenarios included a so-called business as usual approach, which continues present vaccination coverage, and an intensified investment approach, which increases coverage into the future. The annual numbers of infections projected by each model, country, and vaccination scenario were used to explore if, when, and for how long the infections would be below a threshold for elimination.
FINDINGS
The intensified investment scenario led to large reductions in measles and rubella incidence and burden. Rubella elimination is likely to be achievable in all countries and measles elimination is likely in some countries, but not all. The PSU and DynaMICE national measles models estimated that by 2050, the probability of elimination would exceed 75% in 14 (16%) and 36 (39%) of 93 modelled countries, respectively. The subnational model of measles transmission highlighted inequity in routine coverage as a likely driver of the continuance of endemic measles transmission in a subset of countries.
INTERPRETATION
To reach regional elimination goals, it will be necessary to innovate vaccination strategies and technologies that increase spatial equity of routine vaccination, in addition to investing in existing surveillance and outbreak response programmes.
FUNDING
WHO, Gavi, the Vaccine Alliance, US Centers for Disease Control and Prevention, and the Bill & Melinda Gates Foundation.

Identifiants

pubmed: 36113527
pii: S2214-109X(22)00335-7
doi: 10.1016/S2214-109X(22)00335-7
pmc: PMC9557212
mid: NIHMS1840853
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

e1412-e1422

Subventions

Organisme : World Health Organization
ID : 001
Pays : International
Organisme : Intramural CDC HHS
ID : CC999999
Pays : United States
Organisme : CDC HHS
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2022 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 MJ, MF, AKW, ST, and JL report grants from the Bill & Melinda Gates Foundation and Gavi, the Vaccine Alliance. EV reports grants from WHO. MJ and MF report grants from WHO. JL and MF report grants from the US Centers for Disease Control and Prevention (CDC) and National Institutes of Health. MF additionally receives grants from the National Science Foundation. SER and MJ are members of the WHO Strategic Group of Experts on Immunization (SAGE) working group on measles and rubella. SER is acting Chair of the Measles and Rubella Initiative and a member of the Measles and Rubella Post Elimination Regional Monitoring and Re-verification Commission of Pan American Health Organization and The Regional Verification Commission for Measles and Rubella Elimination in the Eastern Mediterranean Region. KM is an employee of the Institute of Disease Modeling and the Bill & Melinda Gates Foundation. CB reports grants from WHO, and is currently a contract employee of Diversant, on contract to Merck Research Laboratories. TP, DK, JKK, LKK, HS, SS, KK, PK, and BL declare no competing interests. The findings and conclusions in this Article are those of the authors and do not necessarily represent the views of the US CDC. The views expressed are those of the authors and not necessarily those of the Vaccine Impact Modelling Consortium or its funders.

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Auteurs

Amy K Winter (AK)

Department of Epidemiology and Biostatics and Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA, USA. Electronic address: awinter@uga.edu.

Brian Lambert (B)

Department of Biology, Pennsylvania State University, State College, PA, USA.

Daniel Klein (D)

Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, WA, USA.

Petra Klepac (P)

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.

Timos Papadopoulos (T)

Department of Statistics Modelling and Economics, UK Health Security Agency, London, UK; Institute of Sound and Vibration Research, University of Southampton, Southampton, UK.

Shaun Truelove (S)

Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Colleen Burgess (C)

Ramboll Health Sciences, Copenhagen, Denmark.

Heather Santos (H)

Department of Biology, Pennsylvania State University, State College, PA, USA.

Jennifer K Knapp (JK)

Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Susan E Reef (SE)

Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Lidia K Kayembe (LK)

Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Stephanie Shendale (S)

Department of Immunization, Vaccines and Biologicals, WHO, Geneva, Switzerland.

Katrina Kretsinger (K)

Department of Immunization, Vaccines and Biologicals, WHO, Geneva, Switzerland.

Justin Lessler (J)

Department of Epidemiology, Gillings School of Global Public Health and Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA.

Emilia Vynnycky (E)

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK; TB Modelling Group, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Statistics Modelling and Economics, UK Health Security Agency, London, UK.

Kevin McCarthy (K)

Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, WA, USA.

Matthew Ferrari (M)

Department of Biology, Pennsylvania State University, State College, PA, USA.

Mark Jit (M)

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK.

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