239 citations · 399 across the 11 of their papers we have counts for
11 papers
A primer on inference and prediction with epidemic renewal models and sequential Monte Carlo
Nicholas Steyn, Kris V. Parag, Robin N. Thompson +1
Renewal models are widely used in statistical epidemiology as semi-mechanistic models of disease transmission. While primarily used for estimating the instantaneous reproduction nu…
Generalised Bayesian distance-based phylogenetics for the genomics era
Matthew J. Penn, Neil Scheidwasser, Mark P. Khurana +3
As whole genomes become widely available, maximum likelihood and Bayesian phylogenetic methods are demonstrating their limits in meeting the escalating computational demands. Conve…
Renewal equations for vector-borne diseases
Cathal Mills, Tarek Alrefae, William S. Hart +5
During infectious disease outbreaks, estimates of time-varying pathogen transmissibility, such as the instantaneous reproduction number R(t) or epidemic growth rate r(t), are used…
Continuous football player tracking from discrete broadcast data
Matthew J. Penn, Christl A. Donnelly, Samir Bhatt
Player tracking data remains out of reach for many professional football teams as their video feeds are not sufficiently high quality for computer vision technologies to be used. T…
Leaping through tree space: continuous phylogenetic inference for rooted and unrooted trees
Matthew J Penn, Neil Scheidwasser, Joseph Penn +3
Phylogenetics is now fundamental in life sciences, providing insights into the earliest branches of life and the origins and spread of epidemics. However, finding suitable phylogen…
Phylo2Vec: a vector representation for binary trees
Matthew J Penn, Neil Scheidwasser, Mark P Khurana +3
Binary phylogenetic trees inferred from biological data are central to understanding the shared history among evolutionary units. However, inferring the placement of latent nodes i…
Intrinsic Randomness in Epidemic Modelling Beyond Statistical Uncertainty
Matthew J. Penn, Daniel J. Laydon, Joseph Penn +7
Uncertainty can be classified as either aleatoric (intrinsic randomness) or epistemic (imperfect knowledge of parameters). The majority of frameworks assessing infectious disease r…
Structural identifiability of compartmental models for infectious disease transmission is influenced by data type
Emmanuelle A. Dankwa, Andrew F. Brouwer, Christl A. Donnelly
If model identifiability is not confirmed, inferences from infectious disease transmission models may not be reliable, so they might lead to misleading recommendations. Structural…
COVID-19-Associated Orphanhood and Caregiver Death in the United States
Susan D. Hillis, Alexandra Blenkinsop, Andrés Villaveces +12
Background: Most COVID-19 deaths occur among adults, not children, and attention has focused on mitigating COVID-19 burden among adults. However, a tragic consequence of adult deat…
Inference of COVID-19 epidemiological distributions from Brazilian hospital data
Iwona Hawryluk, Thomas A. Mellan, Henrique H. Hoeltgebaum +8
Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreove…
Key Questions for Modelling COVID-19 Exit Strategies
Robin N Thompson, T Deirdre Hollingsworth, Valerie Isham +40
Combinations of intense non-pharmaceutical interventions ('lockdowns') were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to impl…