Using seroprevalence and immunisation coverage data to estimate the global burden of Congenital Rubella Syndrome, 1996-2010: A systematic review

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Abstract

Background: The burden of Congenital Rubella Syndrome (CRS) is typically underestimated in routine surveillance. Updated estimates are needed following the recent WHO position paper on rubella and recent GAVI initiatives, funding rubella vaccination in eligible countries. Previous estimates considered the year 1996 and only 78 (developing) countries. Methods: We reviewed the literature to identify rubella seroprevalence studies conducted before countries introduced rubella-containing vaccination (RCV). These data and the estimated vaccination coverage in the routine schedule and mass campaigns were incorporated in mathematical models to estimate the CRS incidence in 1996 and 2000-2010 for each country, region and globally. Results: The estimated CRS decreased in the three regions (Americas, Europe and Eastern Mediterranean) which had introduced widespread RCV by 2010, reaching <2 per 100,000 live births (the Americas and Europe) and 25 (95% CI 4-61) per 100,000 live births (the Eastern Mediterranean). The estimated incidence in 2010 ranged from 90 (95% CI: 46-195) in the Western Pacific, excluding China, to 116 (95% CI: 56-235) and 121 (95% CI: 31-238) per 100,000 live births in Africa and SE Asia respectively. Highest numbers of cases were predicted in Africa (39,000, 95% CI: 18,000-80,000) and SE Asia (49,000, 95% CI: 11,000-97,000). In 2010, 105,000 (95% CI: 54,000-158,000) CRS cases were estimated globally, compared to 119,000 (95% CI: 72,000-169,000) in 1996. Conclusions: Whilst falling dramatically in the Americas, Europe and the Eastern Mediterranean after vaccination, the estimated CRS incidence remains high elsewhere. Well-conducted seroprevalence studies can help to improve the reliability of these estimates and monitor the impact of rubella vaccination.

Figures

  • Table 1. Literature search strategy and inclusion criteria for datasets.
  • Table 2. Summary of the catalytic models used in the analyses of serological data. Note that the lower case letter “a” in the equations below refers to the single year band, whereas “A” (see Eq 1 in the main text) refers to those in the age group of interest, A.
  • Fig 1. Results of the literature search for age-specific serological data collected before the introduction of rubella vaccination.
  • Table 3. Summary of the serological datasets collected before the introduction of vaccination which were used to estimate the global burden of CRS.
  • Fig 2. Examples of the fit of catalytic models to the data sets.Comparison between model predictions of the percentage susceptible and the percentage seronegative to rubella obtained using the four types of catalytic model (denoted by the lines labelled A, B, C and D), and that observed in various settings. The crosses show the observed percentage seronegative together with 95% (exact) confidence intervals.
  • Table 4. Examples of the results obtained by fitting the catalytic models to data. The best-fitting values for the force of infection and (where appropriate) the sensitivity of the antibody assay, and the CRS incidence per 100,000 live births for each catalytic model The values in parentheses reflect the 95% confidence intervals, obtained by bootstrapping. To facilitate comparisons, the infection and CRS incidence is not weighted by the number of live births.
  • Fig 3. Estimates of the number of CRS cases per 100,000 live births among women aged 15–44 years obtained using datasets from countries in which RCV had not been introduced at the time of collection. The red bars reflect countries which had not introduced RCV by 2010; the white bars indicate countries which had introduced RCV by 2010. The estimates have been weighted by the number of live births in the corresponding country in 2010. Labels on the x-axis denote the year of data collection; uncertain dates of collection are indicated using a question mark. The countries are grouped byWHO regions (AFRO = African, EMRO = Eastern Mediterranean, SEARO = South East Asian, WPRO =Western Pacific).
  • Fig 4. Estimates of the median incidence of CRS per 100,000 live births by country in 2010.

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Vynnycky, E., Adams, E. J., Cutts, F. T., Reef, S. E., Navar, A. M., Simons, E., … Dabbagh, A. J. (2016, March 1). Using seroprevalence and immunisation coverage data to estimate the global burden of Congenital Rubella Syndrome, 1996-2010: A systematic review. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0149160

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