Feasibility of measles and rubella vaccination programmes for disease elimination: a modelling study

Abstract

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.

Figure 1

Rubella burden Time series of the annual aggregate number of rubella infections (A) and congenital rubella syndrome cases (B) across 93 countries based on JHU and PHE models under business as usual and intensified investment vaccination scenarios; the line for each model and scenario (ie, colour and line type) represents the median across 200 stochastic runs. JHU=Johns Hopkins University. PHE=Public Health England.

Figure 2

Models of rubella elimination Time series of probability of rubella elimination by country (rows) between 2020 and 2100 for the JHU (A) and PHE (B) models. The probability of rubella elimination at 2050 by country for JHU (C) and PHE (D) models. The probability of achieving the elimination threshold of no more than five rubella infections per million people is shown as a proportion of 200 stochastic runs that would reach the threshold in the intensified investment vaccination scenario. (E) Time series of incident rubella infections for Ukraine, Ethiopia, Djibouti, and Papua New Guinea across 200 stochastic runs for JHU and PHE models; each line represents a different stochastic simulation. JHU=Johns Hopkins University. PHE=Public Health England.

Figure 3

Measles burden Time series of the annual number of measles infections (A) and deaths (B) across 93 countries based on the DynaMICE and PSU models under business as usual and intensified investment vaccination scenarios; the line for each model and scenario (ie, colour and line type) represents the median across 200 stochastic runs. DynaMICE=Dynamic Measles Immunisation Calculation Engine. PSU=Pennsylvania State University.

Figure 4

Models of measles elimination Time series of probability of measles elimination by country (rows) between 2020 and 2100 for the DynaMICE (A) and PSU (B) models. The probability of measles elimination by 2050 by country for the DynaMICE (C) and PSU (D) models. The probability of achieving the elimination threshold of no more than five measles infections per million people is shown as a proportion of 200 stochastic runs that would reach the threshold in the intensified investment vaccination scenario. (E) Time series of incident measles infections in Ukraine, Samoa, Nigeria, and Ethiopia across 200 stochastic runs (each line represents a different stochastic simulation) for DynaMice and PSU models. DynaMICE=Dynamic Measles Immunisation Calculation Engine. PSU=Pennsylvania State University.

Figure 5

Impacts of different spatial equity scenarios in vaccination and correlation between vaccine dosing opportunities on measles burden and probability of elimination using the Institute for Disease Modeling model for Nigeria Spatial distribution of improvements in routine immunisation coverage under different equity scenarios (A), the impact of spatial equity assumptions on mean annual burden of measles between 2032 and 2047 (B), and probability of measles elimination (C) in the intensified investments scenario. (D) Impact of correlation in access to MCV1, MCV2, and SIA dosing opportunities; for illustrative purposes, we assumed 60% coverage for MCV1, 50% coverage for MCV2, and 80% coverage for a single dose SIA. Impact of dose correlation on mean annual measles burden (E) and probability of elimination (F). In figure parts B and E, boxes show the IQR, whiskers represent 1·5 times the IQR, the horizontal lines show the median, and dots show outliers. MCV1=first dose of measles-containing vaccine. MCV2=two doses of measles-containing vaccine. SIAs=supplemental immunisation activities.