This report outlines the results of a small study that sought to examine whether interpolation methods, such as regression models, can be used to provide PDU prevalence estimates for years where prevalence estimates are not readily available. The aims of the study were to
explore routinely collected data which are potentially useful for the task in question
describe and critically assess the methods used in interpolation
describe any main problems if any and solutions
make recommendations for data collection and reporting
The purpose of this exercise was to explore the possibilities to improve trends analysis, as well as to see whether it would be possible to simplify the work of national focal points by suggesting less frequent indirect methods-based estimation studies of PDU, supplemented by annual interpolation of estimates based on routinely collected data from multiple indicators.
Within this study, interpolation is considered as an approach to interpolate across time, rather than the more commonly used method known as the multivariate indicator model (MIM) which extrapolates over geographical areas, for example to construct national prevalence estimates from local prevalence estimates.