Christl Ann Donnelly

A Bayesian modelling framework for inference of latent infection risk patterns from virus neutralisation assay titration data

The paper introduces a Bayesian framework to infer latent infection risk patterns from virus neutralisation assay titration data, revealing higher and more persistent antibody concentrations for EV-D68 compared to other viruses.

Ecology and environment predict spatially stratified risk of H5 highly pathogenic avian influenza clade 2.3.4.4b in wild birds across Europe

The paper uses machine learning to model the spread of H5N1 avian influenza in Europe, finding that ecological factors refine risk predictions beyond climate alone.

Deep learning from videography as a tool for measuring E. coli infection in poultry

This study uses deep learning-based tracking to detect behavioral changes in infected poultry, showing reduced activity in E. coli-infected chickens compared to controls.

Rapid spread of African Swine Fever across Borneo

This study tracks the rapid spread of African Swine Fever across Borneo using citizen science data and estimates the increasing speed of the virus's spread.

Bayesian inference of phylogenetic distances: revisiting the eigenvalue approach

The paper develops a Bayesian method to infer phylogenetic distances incorporating heterotachy and rate variation, finding evidence for a two-domain theory of eukaryotic origins.

Optimising Renewal Models for Real-Time Epidemic Prediction and Estimation

This paper optimizes the renewal model for real-time epidemic prediction by developing a principled method to select the optimal window length k using the accumulated prediction error metric.

Adaptive Estimation for Epidemic Renewal and Phylogenetic Skyline Models

This paper introduces a method to optimally select the number of parameters in epidemic renewal and phylogenetic skyline models using minimum description length to improve estimation accuracy.