Balancing evidence and uncertainty when considering rubella vaccine introduction

Abstract

Background: Despite a safe and effective vaccine, rubella vaccination programs with inadequate coverage can raise the average age of rubella infection; thereby increasing rubella cases among pregnant women and the resulting congenital rubella syndrome (CRS) in their newborns. The vaccination coverage necessary to reduce CRS depends on the birthrate in a country and the reproductive number, R0, a measure of how efficiently a disease transmits. While the birthrate within a country can be known with some accuracy, R0 varies between settings and can be difficult to measure. Here we aim to provide guidance on the safe introduction of rubella vaccine into countries in the face of substantial uncertainty in R0.

Methods: We estimated the distribution of R0 in African countries based on the age distribution of rubella infection using Bayesian hierarchical models. We developed an age specific model of rubella transmission to predict the level of R0 that would result in an increase in CRS burden for specific birth rates and coverage levels. Combining these results, we summarize the safety of introducing rubella vaccine across demographic and coverage contexts.

Findings: The median R0 of rubella in the African region is 5.2, with 90% of countries expected to have an R0 between 4.0 and 6.7. Overall, we predict that countries maintaining routine vaccination coverage of 80% or higher are can be confident in seeing a reduction in CRS over a 30 year time horizon.

Conclusions: Under realistic assumptions about human contact, our results suggest that even in low birth rate settings high vaccine coverage must be maintained to avoid an increase in CRS. These results lend further support to the WHO recommendation that countries reach 80% coverage for measles vaccine before introducing rubella vaccination, and highlight the importance of maintaining high levels of vaccination coverage once the vaccine is introduced.

Figure 1. Estimated R₀ distribution.

(A) Cumulative distribution function, the dotted line represents 95^th percentile. (B) Probability distribution. (C) Individual country estimates; points indicate point estimates, gaps between points and solid lines the inter quartile range, and the range of the solid lines indicates the 95% credible interval for each country.

Figure 2. Critical R₀ thresholds and confidence in seeing a reduction in CRS incidence for birthrate/vaccine coverage combinations.

(A) Routine vaccination only, assuming even mixing across all population age groups. (B) Routine vaccination only, assuming assortative mixing and heterogeneities in contact between age groups. (C) Routine vaccination supplemented with SIAs of 1–4 year olds with 60% coverage every 4 years (assortative mixing). (D) Routine vaccinations and SIAs supplemented with a catch-up campaign covering 1–14 year olds with 60% coverage conducted when rubella vaccine is introduced. White circle shows the cell most closely corresponding to Guinea-Bissau. The square shows the cell most closely corresponding to Guinea Bissau. The diamond indicates the cell most closely corresponding to Somalia.

Figure 3. WHO-UNICEF estimated first dose measles (MCV1) vaccination coverage (from [27]) for 2011, 2010 birth rate (from [28]), R0 point estimate and population age structure (0–80 years of age, from [29]) for 40 African countries used in the analysis.