Characterizing the impact of spatial clustering of susceptibility for measles elimination

Measles elimination efforts are primarily focused on achieving and maintaining national vaccination coverage goals, based on estimates of the critical vaccination threshold (V_c): the proportion of the population that must be immune to prevent sustained epidemics. Traditionally, V_c estimates assume evenly mixing populations, an invalid assumption. If susceptible individuals preferentially contact one another, communities may remain vulnerable to epidemics even when vaccination coverage targets are met at the national level. Here we present a simple method to estimate V_c and the effective reproductive number, R, while accounting for spatial clustering of susceptibility. For measles, assuming R₀ = 15 and 95% population immunity, adjustment for high clustering of susceptibility increases R from 0.75 to 1.29, V_c from 93% to 96%, and outbreak probability after a single introduction from <1% to 23%. The impact of clustering remains minimal until vaccination coverage nears elimination levels. We illustrate our approach using Demographic and Health Survey data from Tanzania and show how non-vaccination clustering potentially contributed to continued endemic transmission of measles virus during the last two decades. Our approach demonstrates why high national vaccination coverage sometimes fails to achieve measles elimination, and that a shift from national to subnational focus is needed as countries approach elimination.