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Epidemiology and Infection logoLink to Epidemiology and Infection
. 2000 Dec;125(3):635–650. doi: 10.1017/s0950268800004672

The pre-vaccination epidemiology of measles, mumps and rubella in Europe: implications for modelling studies.

W J Edmunds 1, N J Gay 1, M Kretzschmar 1, R G Pebody 1, H Wachmann 1; ESEN Project. European Sero-epidemiology Network1
PMCID: PMC2869647  PMID: 11218214

Abstract

Data on the pre-vaccination patterns of infection for measles, mumps and rubella are collated from a number of European countries in order to compare the epidemiology of the three viruses. Key epidemiological parameters, such as the age-specific force of infection and the basic reproduction number (R0) are estimated from case notification or serological data using standard techniques. A method is described to compare force of infection estimates derived from serological data. Analysis suggests that the pre-vaccination patterns of measles and mumps infection in the different countries were similar. In contrast, the epidemiology of rubella was highly variable between countries. This suggests that it may be acceptable to use parameter values estimated from other countries to model measles and mumps transmission, but that this approach to modelling rubella transmission requires more caution. Estimates of R0 depend on underlying mixing assumptions. Constraints were placed on R0 estimates by utilising knowledge of likely mixing patterns. The estimates for R0 were highest for measles, intermediate for mumps, and generally lowest for rubella. Analysis of within- and between-age-group transmission rates suggested that mumps transmission tends to be more concentrated within young children than the other two viruses. The implications for the design of immunization programmes are that mumps may be the easiest to control via infant immunization since it is predominantly transmitted between the very young and the variability in rubella epidemiology requires that careful consideration of the possible effects of vaccination options should be made using local data when planning rubella immunization programmes.

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