Abstract
The degree to which individual heterogeneity in the production of secondary cases ("superspreading") affects tuberculosis (TB) transmission has not been systematically studied. We searched for population-based or surveillance studies in which whole genome sequencing was used to estimate TB transmission and the size distributions of putative TB transmission clusters were enumerated. We fit cluster size distribution data to a negative binomial branching process model to jointly infer the transmission parameters $R$ (the reproductive number) and dispersion parameter, $k$, which quantifies the propensity of superspreading in a population (generally, lower values of $k$ ($<1.0$) suggest increased heterogeneity). Of 4,796 citations identified in our initial search, nine studies met inclusion criteria ($n=5$ all TB; $n=4$ drug resistant TB) from eight global settings. Estimated $R$ values (range: 0.10, 0.73) were below 1.0, consistent with declin ing epidemics in the included settings; estimated $k$ values were well below 1.0 (range: 0.02, 0.48), indicating the presence of substantial individual-level heterogeneity in transmission across all settings. We estimated that a minority of cases (range 2-31%) drive the majority (80%) of ongoing transmission at the population level. Identifying sources of heterogeneity and accounting for them in TB control may have a considerable impact on mitigating TB transmission.
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