  Disaggregation modelling, or downscaling, has become an important discipline
in epidemiology. Surveillance data, aggregated over large regions, is becoming
more common, leading to an increasing demand for modelling frameworks that can
deal with this data to understand spatial patterns. Disaggregation regression
models use response data aggregated over large heterogenous regions to make
predictions at fine-scale over the region by using fine-scale covariates to
inform the heterogeneity. This paper presents the R package disaggregation,
which provides functionality to streamline the process of running a
disaggregation model for fine-scale predictions.
