1 Department of Infectious Disease Epidemiology, Imperial College London, W2 1PG, UK
2 Dipartimento di Statistica e Matematica Applicata all'Economia, Università di Pisa, Via C Ridolfi 10, 56124 Pisa, Italy
Correspondence: Department of Infectious Disease Epidemiology, Division of Primary Care and Population Health Sciences, Faculty of Medicine, Imperial College London, Norfolk Place, London W2 1PG, UK. E-mail: jr.williams{at}imperial.ac.uk
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Abstract |
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Methods A transmission dynamics model incorporating realistic demography is used to investigate the possible impact of population decline and ageing and suboptimal vaccination uptake on the age distribution of incidence of measles infection and of consequent mortality. Data from Italy is used to parameterize the model.
Results Population ageing in the absence of vaccination is shown to reduce per capita incidence of infection but also to increase average and upper quartile ages at infection. The effect is substantially enhanced by significantly suboptimal vaccination uptake, when disease-induced mortality has, for a period, the potential to exceed that in the absence of vaccination.
Conclusions Although a substantially increased burden from chronic non-infectious disease has frequently been proposed as a consequence of population decline, there is also potential for an increase in morbidity and mortality from measles and other childhood infectious diseases, particularly where vaccine uptake is substantially below the optimum. Rubella is highlighted as a particular cause for concern. This work also has implications for less-developed countries.
Accepted 17 December 2003
A widespread fall in fertility has been observed in many so-called industrialized developed countries (IDC) with consequent population decline and ageing.1 As is well recognized, this presages increased prevalence of chronic non-infectious diseases (e.g. ref. 2). To date, however, it appears that little regard has been paid to the impact of this phenomenon (sometimes termed the second demographic transition3) upon incidence of childhood infections and corresponding morbidity.
It has been argued that the drop in fertility associated with the first demographic transition from rapidly growing to approximately constant population size was, through a consequential increase in average age at infection, associated with decreased mortality from childhood infections.4 It may seem strange, therefore, to consider an ageing population as a potential cause for concern in relation to such infections. However, it should be recalled that the description childhood infectious diseases was acquired simply as a result of historic average ages at infection resulting from interactions at the time between demography, the epidemiology or ecology of these infections, and their inducement of lasting immunity following recovery.5 The present onset of a period of significant demographic change in IDC and other countries has the potential to strongly influence these interactions and warrants further investigation.
For a specific disease the age-related per capita incidence of infection among susceptible individuals (i.e. the force of infection [FOI]), may vary over time. It is strongly influenced by patterns of contact between age groups and by population age distribution.5 Using the example of measles in Italy, the question addressed here is to what extent age distribution of infection is influenced by the process of population ageing. This is an important issue because of the observed linkage between increasing age on infection and measles morbidity and mortality, so with more infections in higher age groups increased numbers of deaths and serious disease may follow (Figure 1 shows age-related measles mortality data (diamond markers) from Black6 and a fitted curve, combining initial exponential decay with a logistic curve; c.f. also Eichner7). Although here measles is considered, the conclusions apply with similar force to other childhood infections, mutatis mutandis.
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Among IDC, Italy has experienced one of the most dramatic declines in fertility and potentially a very rapidly ageing population (Figure 2) (other examples are Spain and some Central and Eastern European countries3). Thus Italy serves as a useful laboratory for considering epidemiological effects of these processes. Here we investigate their potential influence on age at infection using a transmission dynamics model incorporating age structure5 and which is capable of realistic representation of Italian demography. We demonstrate, both in the particular case of Italy and more generally, that potential effects on age distribution of infection are quite dramatic, with consequent significant increases in morbidity and mortality. It is anticipated that similar, more or less dramatic, effects would be shown for other infections, with or without the presence of vaccination programmes. Additionally, important effects resulting from changing demography may also be expected to be observed in so-called developing or less developed countries (LDC).
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Materials and Methods |
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Model
A standard compartmental and age-structured deterministic transmission dynamics model5,11 was employed incorporating natural history of measles, and the flow of susceptibles to the exposed class was governed by the FOI and the specified contact pattern (Appendix). The model also incorporated realistic demography in terms of Italian initial age distribution, yearly changes in age-related fertility rates, and age-related mortality. By this means observed numbers of births in Italy since 1950 (Figure 2a) were closely mirrored by model outputs (not shown).
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Results |
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Discussion |
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Distinct patterns of fertility well below replacement are now widespread in Europe. These first became evident in Southern Europe, i.e. Italy, Spain, and Greece, in the 1980s and later, in the late 1990s, were seen in Central and Eastern Europe, where decline has been more sudden and rapid. The continuation of this process is likely to lead to population ageing, whose effects are already apparent. One effect of this process is increased skewing of the population age distribution towards higher ages. The endpoint of this process, assuming fertility remains broadly unchanged from current levels, is that the shape of the age distribution tends to stabilize over a period of some decades at which point the population would be expected to decline exponentially. The present work mainly considers epidemiological effects of population ageing. It may be that in due course fertility will recover to replacement level and thereby maintain population numbers, or indeed it may recover sufficiently to bring about positive growth.17 In both cases a further change in age distribution will result. All these changes will impact upon the dynamics of infection.
Such considerations also have a bearing on future dynamics of infection in developing countries (which may well also experience vaccine uptake substantially below optimum).18 Most such countries are experiencing a change in age distribution,1,19 as a consequence of the first demographic transition. This implies some consequent impact on transmission dynamics over a similar time scale. Moreover, it has recently been argued that this first transition may now be relatively quickly followed by a further transition to population decline,20 mirroring that described above, with further consequences for measles dynamics, and those of other infections. These issues will be dealt with in more detail in a forthcoming publication.
In addition to fertility, migration and mortality are the other demographic processes affecting population size and composition. Patterns of mortality in the developed world correspond reasonably well to the constant age-related Italian rates used here, so that applying rates applicable to other European countries would not be expected to influence results significantly. However, in the case of the developing world, where reductions in mortality arising from improvements in health care may interact in many cases with increasing premature mortality resulting from human immunodeficiency virus (HIV)/AIDS,21 models using mortality rates that do not change over time may not suffice. Here net mortality may evolve in a much more complex way, necessitating more realistic representation if demographic patterns are to be mirrored satisfactorily. In contrast to mortality, the potential impact of migration on European demographic patterns is less clear and the degree to which migration may influence age distribution of measles infection is a question that warrants further research. However, unless both age distribution and that of infection within the immigrant population were markedly different from those in the host population, it would be expected that quite substantial population movements would be needed to affect its age distribution of infection.
Clearly the pattern and magnitude of trends in specific demographic processes, i.e. fertility, mortality, and migration, will influence the age distribution of infection. Additionally, assumptions about contact patterns between age groups and changes in FOI with age which are intrinsic to a given model will also determine the evolution of age distribution of infection through time. Here the change in FOI with age has been estimated from Italian data and the contact pattern is one used elsewhere for modelling European childhood infections (e.g. refs 5, 22). However, the possibility remains that changes in population age distribution with time may themselves influence epidemiological contact patterns. Although the contact pattern employed here provides a satisfactory starting point, this also warrants further investigation. Qualitatively the projected changes in age distribution of infection described here are fully consistent with theory,5,11 although their magnitude may at first sight appear somewhat surprising. (Similar changes were observed, albeit to a lesser degree, when simulations were repeated with a higher FOI corresponding to that described in Edmunds et al.22 [not shown].)
Continued circulation of measles infection relies on a sufficiently large pool of susceptibles to sustain it. Thus, rather than annual variations in vaccine uptake, it is the cumulative build-up of vaccine-based immunity (in combination with the level of infection-based immunity) which is important as a determinant of age distribution of susceptibility, and hence of infection over the longer term. Although a specific vaccination scenario has been employed here, to a greater or lesser degree, comparable results would be obtained from a wide range of cohort vaccination profiles. This is of course subject to the proviso that vaccination was significantly below uptake levels for elimination; these are notoriously difficult to achieve through cohort vaccination alone. Additional vaccine-based immunity may be achieved through delivery of a second dose later in childhood, or by supplementing cohort vaccination with campaign programmes, either on a single (catch up) or a repeated (pulse) basis.23 The Italian MEP comprises a programme combining some of these additional measures. The potential influence of the population ageing scenarios described here on the likely success of the MEP will be considered in a subsequent publication.
While age-structured models of the type used in this work provide a reasonably satisfactory representation of epidemic trends, to achieve more precise representation suitable for informing detailed policy decisions, more sophisticated models are desirable (e.g. those of Babad,24 Ferguson et al.25 etc). Nevertheless it is argued that the results described above do provide a valid qualitative description of the impact of population decline on the age distribution of infection.
This work specifically focuses on the effect of population decline and sub-optimal vaccination on the age distribution of measles infection, and highlights a consequent risk of an increase in measles-related morbidity and mortality. However, the work also constitutes a more general warning of the need not to lose sight of the implications of population decline for other infectious diseases in which mortality and morbidity increase with age. Varicella is one example,26 but rubella, in particular, stands out as posing a particular threat, with the potential for a large proportion of cases to occur in the fertile age range with a consequent substantial increase in cases of congenital rubella syndrome; this issue needs to be urgently addressed.
The onset of population decline and ageing has led, quite rightly, to increasing emphasis on chronic non-infectious disease. However, this emphasis should not be at the expense of overlooking the potential dangers posed by these processes in relation to age-related morbidity arising from infectious diseases. Such dangers must increase the urgency and importance of monitoring age-related experience of infection through seroprevalence surveys and, where vaccines do exist, of achieving and maintaining high levels of vaccination cover.
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Appendix |
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The state variables represent respectively the numbers (at any given age a and time t) with maternal antibody (M), susceptible to infection (X), latently infected (H), infectious (Y), recovered (Z), and immunised (V). Model rate parameters are d (decay of maternal antibody), µ(a) (age-related mortality), v (vaccination), (incubation), and
(recovery), with age-specific fertility
(a) (Source: MacLean & Anderson11)
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KEY MESSAGES
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Acknowledgments |
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References |
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