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Measles in developing countries. Part II. The predicted impact of mass vaccination

Published online by Cambridge University Press:  19 October 2009

A. R. Mclean  and
R. M. Anderson
A. R. Mclean
Affiliation:
Parasite Epidemiology Research Group, Department of Pure and Applied Biology, Imperial College, London University, London SW7 2BB
R. M. Anderson
Affiliation:
Parasite Epidemiology Research Group, Department of Pure and Applied Biology, Imperial College, London University, London SW7 2BB
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A mathematical model is developed to mimic the transmission dynamics of the measles virus in communities in the developing world with high population growth rates and high case fatality rates. The model is used to compare the impacts of different mass vaccination programmes upon morbidity and mortality arising from infection by measles virus. Analyses identify three conclusions of practical significance to the design of optimal vaccination programmes. First, there is no single optimum age at which to vaccinate children for all urban and rural communities in developing countries. For a given community the best age at which to vaccinate depends critically on the age distribution of cases of infection prior to the introduction of control measures. Second, numerical studies predict that the introduction of mass vaccination will induce a temporary phase of very low incidence of infection before the system settles to a new pattern of recurrent epidemics. Mass vaccination acts to lengthen the inter-epidemic period in the postvaccination period when compared with that prevailing prior to control. Third, numerical simulations suggest that two-phase and two-stage vaccination programmes are of less benefit than one-stage programmes (achieving comparable coverage) aimed at young children. The paper ends with a discussion of the needs for: improved programmes of data collection; monitoring of the impact of current vaccination programmes; and the development of models that take account of viral transmission dynamics, host demography and economic factors.

Type
Research Article
Information
Epidemiology & Infection , Volume 100 , Issue 3 , June 1988 , pp. 419 - 442
Copyright
Copyright © Cambridge University Press 1988

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