Structured models of infectious disease: inference with discrete data.

The usage of structured population models can make substantial contributions to public health, particularly for infections where clinical outcomes vary over age. There are three theoretical challenges in implementing such analyses: (i) developing an appropriate framework that models both demographic and epidemiological transitions; (ii) parameterizing the framework, where parameters may be based on data ranging from the biological course of infection, basic patterns of human demography, specific characteristics of population growth, and details of vaccination regimes implemented; (iii) evaluating public health strategies in the face of changing human demography. We illustrate the general approach by developing a model of rubella in Costa Rica. The demographic profile of this infection is a crucial aspect of its public health impact, and we use a transient perturbation analysis to explore the impact of changing human demography on immunization strategies implemented.

Rubella metapopulation dynamics and importance of spatial coupling to the risk of congenital rubella syndrome in Peru.

Rubella is generally a mild childhood disease, but infection during early pregnancy may cause spontaneous abortion or congenital rubella syndrome (CRS), which may entail a variety of birth defects. Consequently, understanding the age-structured dynamics of this infection has considerable public health value. Vaccination short of the threshold for local elimination of transmission will increase the average age of infection. Accordingly, the classic concern for this infection is the potential for vaccination to increase incidence in individuals of childbearing age. A neglected aspect of rubella dynamics is how age incidence patterns may be moulded by the spatial dynamics inherent to epidemic metapopulations. Here, we use a uniquely detailed dataset from Peru to explore the implications of this for the burden of CRS. Our results show that the risk of CRS may be particularly severe in small remote regions, a prediction at odds with expectations in the endemic situation, and with implications for the outcome of vaccination. This outcome results directly from the metapopulation context: specifically, extinction-re-colonization dynamics are crucial because they allow for significant leakage of susceptible individuals into the older age classes during inter-epidemic periods with the potential to increase CRS risk by as much as fivefold.

The epidemiology of rubella in Mexico: seasonality, stochasticity and regional variation.

The factors underlying the temporal dynamics of rubella outside of Europe and North America are not well known. Here we used 20 years of incidence reports from Mexico to identify variation in seasonal forcing and magnitude of transmission across the country and to explore determinants of inter-annual variability in epidemic magnitude in rubella. We found considerable regional variation in both magnitude of transmission and amplitude of seasonal variation in transmission. Several lines of evidence pointed to stochastic dynamics as an important driver of multi-annual cycles. Since average age of infection increased with the relative importance of stochastic dynamics, this conclusion has implications for the burden of congenital rubella syndrome. We discuss factors underlying regional variation, and implications of the importance of stochasticity for vaccination implementation.