Speaker
Description
Households represent a key unit of interest in infectious disease epidemiology, in both empirical studies and mathematical modelling. The within-household transmission potential of an infectious disease is often summarised in terms of a secondary attack ratio. Despite their widespread use, estimates of secondary attack ratio depend on the distribution of household compositions seen during the study period, making them poor indicators of transmission potential in new populations and future epidemic phases. Extending estimates of transmission potential to new populations instead requires estimates of person-to-person transmission rates which can be convoluted with data on population structure to parameterise mechanistic transmission models.
This talk will present a new inference method for estimating the transmission intensity by imputing the unreported household structure underlying the epidemic dynamics with MCMC. This method can be run on household epidemiological data reported at varying levels of resolution. The algorithm was able to reliably recover parameters from synthetic data and provide estimates of transmission rates from existing datasets that could not otherwise be used to directly parameterise transmission models. These results also aim to encourage the reporting of higher resolution outputs in future epidemiological field work as the transmission parameters were not identifiable from low resolution datasets, which are commonly reported.
