Pieter Trapman
Pieter Trapman
Verified email at math.su.se - Homepage
Cited by
Cited by
A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2
T Britton, F Ball, P Trapman
Science 369 (6505), 846-849, 2020
The abundance threshold for plague as a critical percolation phenomenon
S Davis, P Trapman, H Leirs, M Begon, JAP Heesterbeek
Nature 454 (7204), 634-637, 2008
Analysis of a stochastic SIR epidemic on a random network incorporating household structure
F Ball, D Sirl, P Trapman
Mathematical Biosciences 224 (2), 53-73, 2010
Eight challenges for network epidemic models
L Pellis, F Ball, S Bansal, K Eames, T House, V Isham, P Trapman
Epidemics 10, 58-62, 2015
Five challenges for spatial epidemic models
S Riley, K Eames, V Isham, D Mollison, P Trapman
Epidemics 10, 68-71, 2015
On analytical approaches to epidemics on networks
P Trapman
Theoretical population biology 71 (2), 160-173, 2007
The nosocomial transmission rate of animal-associated ST398 meticillin-resistant Staphylococcus aureus
MCJ Bootsma, MWM Wassenberg, P Trapman, MJM Bonten
Journal of the Royal Society Interface 8 (57), 578-584, 2011
Threshold behaviour and final outcome of an epidemic on a random network with household structure
F Ball, D Sirl, P Trapman
Advances in Applied Probability 41 (3), 765-796, 2009
Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of R0
L Pellis, F Ball, P Trapman
Mathematical biosciences 235 (1), 85-97, 2012
Epidemics on random intersection graphs
FG Ball, DJ Sirl, P Trapman
Annals of Applied Probability 24 (3), 1081-1128, 2014
Five challenges for stochastic epidemic models involving global transmission
T Britton, T House, AL Lloyd, D Mollison, S Riley, P Trapman
Epidemics 10, 54-57, 2015
The growth of the infinite long-range percolation cluster
P Trapman
Annals of probability 38 (4), 1583-1608, 2010
The disease-induced herd immunity level for Covid-19 is substantially lower than the classical herd immunity level
T Britton, F Ball, P Trapman
arXiv preprint arXiv:2005.03085, 2020
A useful relationship between epidemiology and queueing theory: the distribution of the number of infectives at the moment of the first detection
P Trapman, MCJ Bootsma
Mathematical biosciences 219 (1), 15-22, 2009
Key questions for modelling COVID-19 exit strategies
RN Thompson, TD Hollingsworth, V Isham, D Arribas-Bel, B Ashby, ...
Proceedings of the Royal Society B 287 (1932), 20201405, 2020
Reproduction numbers for epidemic models with households and other social structures II: comparisons and implications for vaccination
F Ball, L Pellis, P Trapman
Mathematical biosciences 274, 108-139, 2016
A branching model for the spread of infectious animal diseases in varying environments
P Trapman, R Meester, H Heesterbeek
Journal of mathematical biology 49 (6), 553-576, 2004
Inferring R0 in emerging epidemics—the effect of common population structure is small
P Trapman, F Ball, JS Dhersin, VC Tran, J Wallinga, T Britton
Journal of the Royal Society Interface 13 (121), 20160288, 2016
Reproduction numbers for epidemics on networks using pair approximation
P Trapman
Mathematical biosciences 210 (2), 464-489, 2007
Bounding basic characteristics of spatial epidemics with a new percolation model
R Meester, P Trapman
Advances in Applied Probability 43 (2), 335-347, 2011
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