62 citations · 313 across the 18 of their papers we have counts for
6 papers · 1 filter
Adaptive Sequential Surveillance of Infectious Diseases Under Limited Sampling Capacity
Minghua Xiao, Anne M. Presanis, David S. Robertson +2
This paper develops a closed-loop adaptive sequential surveillance framework for infectious disease monitoring with limited surveillance resources. In this framework, we use a Baye…
GENIE: Generative Neural Inference for Epidemics
Laura M. Guzmán-Rincón, George R. E. Bradley, Joel Kandiah +5
The SARS-CoV-2 pandemic highlighted the ongoing risk infectious diseases pose to society and the value of reliable information on the likely future burden. When forecasting an epid…
A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19
Christopher Jackson, Brian Tom, Peter Kirwan +5
We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are a…
Joining and splitting models with Markov melding
Robert J. B. Goudie, Anne M. Presanis, David Lunn +2
Analysing multiple evidence sources is often feasible only via a modular approach, with separate submodels specified for smaller components of the available evidence. Here we intro…
Estimation of HIV Burden through Bayesian Evidence Synthesis
Daniela De Angelis, Anne M. Presanis, Stefano Conti +1
Planning, implementation and evaluation of public health policies to control the human immunodeficiency virus (HIV) epidemic require regular monitoring of disease burden. This incl…
Conflict Diagnostics in Directed Acyclic Graphs, with Applications in Bayesian Evidence Synthesis
Anne M. Presanis, David Ohlssen, David J. Spiegelhalter +1
Complex stochastic models represented by directed acyclic graphs (DAGs) are increasingly employed to synthesise multiple, imperfect and disparate sources of evidence, to estimate q…