Such findings support policy and provide a basis to set routine immunization levels not only at country- but also at district level, or to recommend campaigns in under-immunized regions 9, 12.Īnother way in which individuals can be clustered is by age. One way of clustering, which has already received some attention, and which has turned out to have an impact on the risk for measles outbreaks, is clustering based on geographical proximity 9, 12, 13. Susceptible individuals in a population may be clustered in a number of ways. When susceptible individuals are clustered in a population, this may lead to a higher risk for measles outbreaks to occur, even when a high level of population immunity already exists 10, 11. This is, however, not realistic, and may lead to an underestimation of the herd immunity threshold 9. However, this formula is based on the assumption that susceptible individuals are evenly distributed throughout the population and that mixing occurs homogeneously. With an R 0 for measles between 12 and 18, a population immunity level of 95% should thus be enough to stop the disease from spreading 8. The traditional formula to estimate a threshold for herd immunity states that a fraction as large as 1 - ( 1 / R 0 ) should be immune to infection for herd immunity to be ensured.

In relation to the latter, one potentially contributing factor is that susceptible individuals might not be randomly distributed in a population, and that this may influence to which extent an overall high vaccination coverage avoids outbreaks from occurring or persisting. Such an explanation is undoubtedly multifaceted, relating to vaccination coverage and vaccine effectiveness over time, as well as to the intricacies of social interactions between individuals in populations. Finding the answer to this question might give us an indication of where the barriers for successful elimination of measles lie and enable us to make the final push for eradication of this disease. Increasing attention is being devoted to explain why outbreaks still occur in regions with high vaccination coverage 5– 7.

Nevertheless, outbreaks of measles still occur in these same regions 2– 4. Many regions are close to reaching this target, or have vaccination coverage levels that already exceed this threshold. To reach this goal by 2020, the WHO has set the target of 95% vaccination coverage, both at the country and district level. The global elimination of measles is an important goal of the WHO 1. Ignoring within-household clustering thus leads to underestimations of required measles elimination and outbreak mitigation efforts. We find that higher levels of within-household clustering of susceptible individuals increase the risk, size and persistence of measles outbreaks. Furthermore, we compare realistic scenarios regarding the distribution of susceptible individuals within households in terms of their impact on epidemiological measures for outbreak risk and persistence. We construct a metric to estimate the level of within-household susceptibility clustering in the population.

To this end, we apply an individual-based model, Stride, to a population of 600,000 individuals, using data from Flanders, Belgium. Here, we investigate to which extent different levels of within-household clustering of susceptible individuals may impact the risk and persistence of measles outbreaks. However, unvaccinated individuals may be clustered in a variety of ways, including by geographic location, by age, in schools, or in households. When estimating important measures such as the herd immunity threshold, and the corresponding efforts required to eliminate measles, it is often assumed that susceptible individuals are uniformly distributed throughout populations.

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