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

Abstract

SummaryA 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.

The dynamics of measles in sub-Saharan Africa

“…The epidemic dynamics of measles are the best understood among acute infections 2,[13][14][15][16][17][18][19][20][21] . Powerful herd immunity leads to a tendency for multi-annual outbreaks, forced mainly by seasonal variations in infection rate (owing to schooling patterns in industrialized countries), and generating large, characteristically biennial, epidemics in the pre-vaccination era 13,16,22 .…”

Epidemiology of measles in Taiwan: dynamics of transmission and timeliness of reporting during an epidemic in 1988–9

“…The different peak month of June-July 1988 and January 1989 coincided with the summer vacation and New Year holidays and spread measles island-wide. Furthermore, mass immunization programmes tend to raise the age of susceptibles from preschool to school-children [19][20]. More cases appeared among 10-14-year-old children in 1988-9 (20%) than in 1976-85 (1-2 %) [2] and signified that the problems of a 'honeymoon period' after mass immunization occurred in Taiwan [20].…”

“…Furthermore, mass immunization programmes tend to raise the age of susceptibles from preschool to school-children [19][20]. More cases appeared among 10-14-year-old children in 1988-9 (20%) than in 1976-85 (1-2 %) [2] and signified that the problems of a 'honeymoon period' after mass immunization occurred in Taiwan [20]. Infants had a significantly increased risk of measles infection after 9 months of age, implying the urgent need to immunize them at 9 or 6 months once a measles outbreak occurs [21].…”

Age-specific mixing generates transient outbreak risk following critical-level vaccination

“…If vaccination is maintainted at high levels, then these sporadic outbreaks are unlikely to persist. In the time between these sporadic outbreaks, unvaccinated susceptible individuals will age, leading to a progressive increase in the mean age of the susceptible population [24]. This shift in the size and age distribution of the susceptible population over time following the introduction of vaccination leads to a transient regimen between the endemic and disease-free equilibrium during which outbreak risk, the expected size of an outbreak, and the age distribution of the susceptible population at risk are dynamic in time.…”