Title: Integrated nested Laplace approximations for extended latent Gaussian models with application to the Naomi HIV model
Title word count: 16.
Abstract: Naomi (Eaton et al, 2021) is a spatial
evidence synthesis model used to produce district-level HIV epidemic
indicators in sub-Saharan Africa. Multiple outcomes of interest,
including HIV prevalence, HIV incidence and treatment coverage are
jointly modelled using both household survey data and routinely reported
health system data. The model is provided as a tool for countries to
input their data to and generate estimates (see https://naomi.unaids.org/). In this setting,
computationally intensive inference methods like MCMC are impractical.
To enable fast and accurate inference for Naomi, and other extended
latent Gaussian models, we are developing a new inference method which
combines the simplified integrated nested Laplace approximation approach
of Wood (2020) with adaptive Gauss-Hermite quadrature. The new method
will be implemented as an extension of the aghq package
(Stringer, 2021), which will facilitate flexible and particularly easy
use when provided a TMB C++ template for the log-posterior.
In this talk, I’ll discuss progress towards this project, which I have
been working on with Alex Stringer here at Waterloo this term through
the International Visiting Graduate Student program.
Abstract word count: 184/200.