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Interpretation of serological surveillance data for measles using mathematical models: implications for vaccine

N J Gay1, L M Hesketh, P Morgan-Capner

  • 1Immunisation Division, PHLS Communicable Disease Surveillance Centre, London, UK.

Insights

Measles immunity surveillance in England showed increasing susceptibility in children after the measles, mumps, and rubella vaccine introduction. Mathematical models predicted a potential measles epidemic, prompting a vaccination campaign.

Area of Science:

  • Epidemiology
  • Immunology
  • Public Health

Background:

  • Serological surveillance of measles immunity in England began in 1986/7.
  • The measles, mumps, and rubella (MMR) vaccination program was introduced in October 1988.

Purpose of the Study:

  • To analyze trends in measles immunity following the MMR vaccine introduction.
  • To predict potential measles resurgence using mathematical modeling.
  • To inform public health strategies for disease control.

Main Methods:

  • Serological data from England (1989-91) were analyzed.
  • Mathematical models were employed to interpret immunity data.
  • The reproduction number (R) was used to quantify herd immunity.

Main Results:

  • An increasing proportion of school-aged children were susceptible to measles post-MMR introduction.
  • Mathematical models indicated a high likelihood of a measles epidemic (over 100,000 cases) in 1995/6.
  • Predictions aligned with observed incidence and age distribution trends.

Conclusions:

  • Rising measles susceptibility poses a significant public health concern.
  • Predictive modeling is crucial for anticipating disease outbreaks.
  • These findings supported the planning of a large-scale vaccination campaign to prevent a measles resurgence.

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