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Pieter TrapmanDocent


1. P. Trapman, R. Meester and J.A.P. Heesterbeek, “A branching model for the spread of infectious animal diseases in varying environments,” Journal of Mathematical Biology 49 553-576, 2004.
2. R. Meester and P. Trapman, “Estimation in branching processes with restricted observations,” Advances in Applied Probability 38 1098-1115, 2006.
3. P. Trapman, “On analytical approaches to epidemics on networks,” Theor. Popul. Biol. 71 160–173, 2007.
4. P. Trapman, “Reproduction numbers for epidemics on networks using pair approximation,” Math. Biosci. 210 464–489, 2007.
5. S. Davis, P. Trapman, H. Leirs, M. Begon, and J. Heesterbeek, “The abundance threshold for plague as a critical percolation phenomenon,” Nature 454 634–637, 2008.
6. P. Trapman and M. Bootsma, “A useful relationship between epidemiology and queueing theory: the distribution of the number of infectives at the moment of the first detection,” Math. Biosci. 219 15–22, 2009.
7. F. Ball, D. Sirl, and P. Trapman, “Threshold behaviour and final outcome of an epidemic on a random network with household structure,” Adv. in Appl. Probab. 41 765-796, 2009.
8. F. Ball, D. Sirl, and P. Trapman, “Analysis of a stochastic sir epidemic on a random network incorporating household structure,” Math. Biosci. 224 53–73, 2010.
9. P. Trapman, “The growth of the infinite long-range percolation cluster,” The Annals of Probability 38 1583–1608, 2010.
10. M. Bootsma, M. Wassenberg, P. Trapman, and M. Bonten, “The nosocomial transmission rate of animal-associated st398 meticillin-resistant staphylococcus aureus,” Journal of The Royal Society Interface 8 578–584, 2011.
11. R. Meester and P. Trapman, “Bounding basic characteristics of spatial epidemics with a new percolation model,” Adv. in Appl. Probab. 43 335–347, 2011.
12. V. Koval, R. Meester, and P. Trapman, “Long-range percolation on the hierarchical lattice,” Elect. J. Probab 17 2012.
13. L. Pellis, F. Ball, and P. Trapman, “Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of R0,” Math. Biosci. 235 85–97, 2012.
14. T. Britton, P. Trapman, “Maximizing the size of the giant,” J. Appl. Probab. 49 1156-1165, 2012.
15. A. Lambert, P. Trapman, “Splitting trees stopped when the first clock rings and vervaat’s transformation,” J. Appl. Probab. 50 208–227, 2013.
16. T. Britton and P. Trapman, “Inferring global network properties from egocentric data with applications to epidemics,” Mathematical Medicine and Biology, 2013.
17. F. Ball, D. Sirl, and P. Trapman, “Epidemics on random intersection graphs,” The Annals of Applied Probability 24 1081–1128, 2014.
18. T. Britton and P. Trapman, “Stochastic epidemics in growing populations,” Bulletin of mathematical biology 76 985–996, 2014.
19. T. Britton, T. House, A. Lloyd, D. Mollison, S. Riley, and P. Trapman, “Eight challenges for stochastic epidemic models involving global transmission,” Epidemics 10 54-57,  2015.
20. L. Pellis, F. Ball, S. Bansal, K. Eames, T. House, V. Isham, and P. Trapman, “Eight challenges for network epidemic models,” Epidemics 10 58-62, 2015.
21. S. Riley, K. Eames, V. Isham, D. Mollison, and P. Trapman, “Five challenges for spatial epidemic models,”  Epidemics 10 68-71, 2015.
22. H. Heesterbeek, R. M. Anderson, V. Andreasen, S. Bansal, D. De Angelis, C. Dye, K. T. Eames, W. J. Edmunds, S. D. Frost, S. Funk, et al., “Modeling infectious disease dynamics in the complex landscape of global health,” Science 347 4339, 2015.
23. T. Ouboter, R. Meester, and P. Trapman, “Stochastic SIR epidemics in a population with households and schools,” Journal of mathematical biology 72(5) 1177-1193, 2016.
24. F. Ball, L. Pellis, and P. Trapman, “Reproduction numbers for epidemic models with households and other social structures II: comparisons and implications for vaccination,” Mathematical Biosciences 274 108-139, 2016.
25. P. Trapman, F. Ball, J.S. Dhersin, V.C.Tran, J. Wallinga and T. Britton, "Inferring R0 in emerging epidemics—the effect of common population structure is small," Journal of The Royal Society Interface, 13(121) 20160288, 2016.
26. F. Ball, T. Britton and P. Trapman, "An epidemic in a dynamic population with importation of infectives,"  The Annals of Applied Probability 27(1) 242-274, 2017.
27. A.A. Lashari and P. Trapman, "Branching process approach for epidemics in dynamic partnership network." Journal of mathematical biology 76(1-2) 265-294, 2018.
28. K.Y. Leung, P. Trapman and T. Britton, "Who is the infector? Epidemic models with symptomatic and asymptomatic cases." Mathematical biosciences 301 190-198, 2018.
29. M. Deijfen, S. Rosengren, and P. Trapman. "The Tail does not Determine the Size of the Giant." Journal of Statistical Physics 173(3-4) 736-745, 2018.
30. K. Spricer, and P. Trapman. "Characterizing the Initial Phase of Epidemic Growth on Some Empirical." in Stochastic Processes and Applications: SPAS2017, Västerås and Stockholm, Sweden, October 4–6, 2017, 315-334, 2018.
31. S. Rosengren and P. Trapman. "a dynamic Erdős-Rényi graph model," Markov Processes and Related Fields 25(2) 275-301 , 2019.
32. C. Fransson and P. Trapman. "SIR epidemics and vaccination on random graphs with clustering,"  Journal of mathematical biology 78(7) 2369-2398, 2019.
33. T. Britton, K.Y. Leung, and P. Trapman. "Who is the infector? General multi-type epidemics and real-time susceptibility processes." Advances in Applied Probability 51(2) 606-631, 2019.
34. T. Britton, F. Ball, and P. Trapman. "A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2." Science 369.6505: 846-849, 2020.
35. R.N. Thompson et al. "Key questions for modelling COVID-19 exit strategies." Proceedings of the Royal Society B 287.1932,  20201405, 2020.
36. A.A. Lashari,  A. Serafimović, and P. Trapman. "The duration of an $ SIR $ epidemic on a configuration model." arXiv preprint arXiv:1805.05117 (2018).