39 citations · 230 across the 21 of their papers we have counts for
22 papers
Detecting Conflicts in Evidence Synthesis Models Using Score Discrepancies
Fuming Yang, David J. Nott, Anne M. Presanis
Evidence synthesis models combine multiple data sources to estimate latent quantities of interest, enabling reliable inference on parameters that are difficult to measure directly.…
Doubly robust integration of nonprobability and probability survey data
Shaun R Seaman, Tommy Nyberg, Anne M Presanis +10
Doubly robust (DR) estimators of the population mean of an outcome have been proposed for integrating outcome and covariate data from a nonprobability sample with covariate data fr…
A standardised protocol for assessment of relative SARS-CoV-2 variant severity, with application to severity risk for COVID-19 cases infected with Omicron BA.1 compared to Delta variants in six European countries
Tommy Nyberg, Peter Bager, Ingrid Bech Svalgaard +17
Several SARS-CoV-2 variants that evolved during the COVID-19 pandemic have appeared to differ in severity, based on analyses of single-country datasets. With decreased SARS-CoV-2 t…
The Lifebelt Particle Filter for robust estimation from low-valued count data
Alice Corbella, Trevelyan J. McKinley, Paul J. Birrell +4
Particle filtering methods can be applied to estimation problems in discrete spaces on bounded domains, to sample from and marginalise over unknown hidden states. As in continuous…
Inferring Epidemics from Multiple Dependent Data via Pseudo-Marginal Methods
Alice Corbella, Anne M Presanis, Paul J Birrell +1
Health-policy planning requires evidence on the burden that epidemics place on healthcare systems. Multiple, often dependent, datasets provide a noisy and fragmented signal from th…
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…
Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study
Peter Kirwan, Andre Charlett, Paul Birrell +5
Widespread vaccination campaigns have changed the landscape for COVID-19, vastly altering symptoms and reducing morbidity and mortality. We estimate trends in mortality by month of…
Quantifying efficiency gains of innovative designs of two-arm vaccine trials for COVID-19 using an epidemic simulation model
Rob Johnson, Chris Jackson, Anne Presanis +2
Clinical trials of a vaccine during an epidemic face particular challenges, such as the pressure to identify an effective vaccine quickly to control the epidemic, and the effect th…
Trends in risks of severe events and lengths of stay for COVID-19 hospitalisations in England over the pre-vaccination era: results from the Public Health England SARI-Watch surveillance scheme
Peter D. Kirwan, Suzanne Elgohari, Christopher H. Jackson +4
Background: Trends in hospitalised case-fatality risk (HFR), risk of intensive care unit (ICU) admission and lengths of stay for patients hospitalised for COVID-19 in England over…
Implications for HIV elimination by 2030 of recent trends in undiagnosed infection in England: an evidence synthesis
Anne M Presanis, Peter Kirwan, Ada Miltz +9
A target to eliminate Human Immuno-deficiency Virus (HIV) transmission in England by 2030 was set in early 2019. Estimates of recent trends in HIV prevalence, particularly the numb…
Analysing Multiple Epidemic Data Sources
Daniela De Angelis, Anne M. Presanis
Evidence-based knowledge of infectious disease burden, including prevalence, incidence, severity and transmission, in different population strata and locations, and possibly in rea…
Assessing the causal effect of binary interventions from observational panel data with few treated units
Pantelis Samartsidis, Shaun R. Seaman, Anne M. Presanis +2
Researchers are often challenged with assessing the impact of an intervention on an outcome of interest in situations where the intervention is non-randomised, the intervention is…
Evidence synthesis for stochastic epidemic models
Paul J Birrell, Daniela De Angelis, Anne M Presanis
In recent years the role of epidemic models in informing public health policies has progressively grown. Models have become increasingly realistic and more complex, requiring the u…
Quantifying the recency of HIV infection using multiple longitudinal biomarkers
Loumpiana Koulai, Anne Presanis, Gary Murphy +2
Knowledge of the time at which an HIV-infected individual seroconverts, when the immune system starts responding to HIV infection, plays a vital role in the design and implementati…
Exploiting routinely collected severe case data to monitor and predict influenza outbreaks
Alice Corbella, Xu-Sheng Zhang, Paul J. Birrell +4
Influenza remains a significant burden on health systems. Effective responses rely on the timely understanding of the magnitude and the evolution of an outbreak. For monitoring pur…
Value of Information: Sensitivity Analysis and Research Design in Bayesian Evidence Synthesis
Christopher Jackson, Anne Presanis, Stefano Conti +1
Suppose we have a Bayesian model which combines evidence from several different sources. We want to know which model parameters most affect the estimate or decision from the model,…
Conflict diagnostics for evidence synthesis in a multiple testing framework
Anne M. Presanis, David Ohlssen, Kai Cui +2
Evidence synthesis models that combine multiple datasets of varying design, to estimate quantities that cannot be directly observed, require the formulation of complex probabilisti…
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…
Synthesising evidence to estimate pandemic (2009) A/H1N1 influenza severity in 2009-2011
Anne M. Presanis, Richard G. Pebody, Paul J. Birrell +5
Knowledge of the severity of an influenza outbreak is crucial for informing and monitoring appropriate public health responses, both during and after an epidemic. However, case-fat…
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…
Modeling of the HIV infection epidemic in the Netherlands: A multi-parameter evidence synthesis approach
Stefano Conti, Anne M. Presanis, Maaike G. van Veen +4
Multi-parameter evidence synthesis (MPES) is receiving growing attention from the epidemiological community as a coherent and flexible analytical framework to accommodate a dispara…