In this section
@article{Howes:2026:10.1016/j.jtbi.2025.112290,
author = {Howes, A and Stringer, A and Flaxman, SR and ImaiEaton, JW},
doi = {10.1016/j.jtbi.2025.112290},
journal = {Journal of Theoretical Biology},
title = {Fast approximate Bayesian inference of HIV indicators using PCA adaptive Gauss-Hermite quadrature},
url = {http://dx.doi.org/10.1016/j.jtbi.2025.112290},
volume = {618},
year = {2026}
}
TY - JOUR
AB - Naomi is a spatial evidence synthesis model used to produce district-level HIV epidemic indicators in sub-Saharan Africa. Multiple outcomes of policy interest, including HIV prevalence, HIV incidence, and antiretroviral therapy 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 with during a yearly process supported by UNAIDS. Previously, inference has been conducted using empirical Bayes and a Gaussian approximation, implemented via the TMB R package. We propose a new inference method based on an extension of adaptive Gauss-Hermite quadrature to deal with more than 20 hyperparameters. Using data from Malawi, our method improves the accuracy of inferences for model parameters, while being substantially faster to run than Hamiltonian Monte Carlo with the No-U-Turn sampler. Our implementation leverages the existing TMB C++ template for the model’s log-posterior, and is compatible with any model with such a template.
AU - Howes,A
AU - Stringer,A
AU - Flaxman,SR
AU - ImaiEaton,JW
DO - 10.1016/j.jtbi.2025.112290
PY - 2026///
SN - 0022-5193
TI - Fast approximate Bayesian inference of HIV indicators using PCA adaptive Gauss-Hermite quadrature
T2 - Journal of Theoretical Biology
UR - http://dx.doi.org/10.1016/j.jtbi.2025.112290
UR - https://doi.org/10.1016/j.jtbi.2025.112290
VL - 618
ER -
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