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Pieter Trapman

Showing results (11-20 of 25) with videos related to

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Mathematical Biosciences|February 24, 2009
A useful relationship between epidemiology and queueing theory: the distribution of the number of infectives at the moment of the first detectionPieter Trapman, Martinus Christoffel Jozef Bootsma
Royal Society Open Science|August 5, 2021
The risk for a new COVID-19 wave and how it depends on <i>R</i> <sub>0</sub>, the current immunity level and current restrictionsTom Britton, Pieter Trapman, Frank Ball
Mathematical Biosciences|November 17, 2011
Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of R0Lorenzo Pellis, Frank Ball, Pieter Trapman
Mathematical Biosciences|February 5, 2016
Reproduction numbers for epidemic models with households and other social structures II: Comparisons and implications for vaccinationFrank Ball, Lorenzo Pellis, Pieter Trapman
Science (New York, N.Y.)|June 25, 2020
A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2Tom Britton, Frank Ball, Pieter Trapman
Mathematical Biosciences|April 15, 2018
Who is the infector? Epidemic models with symptomatic and asymptomatic casesKa Yin Leung, Pieter Trapman, Tom Britton
Journal of Mathematical Biology|April 23, 2025
Modelling the spread of two successive SIR epidemics on a configuration model networkFrank Ball, Abid Ali Lashari, David Sirl, et al.
Epidemics|April 7, 2015
Five challenges for spatial epidemic modelsSteven Riley, Ken Eames, Valerie Isham, et al.
Epidemics|April 7, 2015
Five challenges for stochastic epidemic models involving global transmissionTom Britton, Thomas House, Alun L Lloyd, et al.
Journal of the Royal Society, Interface|September 2, 2016
Inferring R0 in emerging epidemics-the effect of common population structure is smallPieter Trapman, Frank Ball, Jean-Stéphane Dhersin, et al.
Pageof 3

Showing results (11-20 of 25) with videos related to

Sort By:
Pageof 3
Mathematical Biosciences|February 24, 2009
A useful relationship between epidemiology and queueing theory: the distribution of the number of infectives at the moment of the first detectionPieter Trapman, Martinus Christoffel Jozef Bootsma
Royal Society Open Science|August 5, 2021
The risk for a new COVID-19 wave and how it depends on <i>R</i> <sub>0</sub>, the current immunity level and current restrictionsTom Britton, Pieter Trapman, Frank Ball
Mathematical Biosciences|November 17, 2011
Reproduction numbers for epidemic models with households and other social structures. I. Definition and calculation of R0Lorenzo Pellis, Frank Ball, Pieter Trapman
Mathematical Biosciences|February 5, 2016
Reproduction numbers for epidemic models with households and other social structures II: Comparisons and implications for vaccinationFrank Ball, Lorenzo Pellis, Pieter Trapman
Science (New York, N.Y.)|June 25, 2020
A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2Tom Britton, Frank Ball, Pieter Trapman
Mathematical Biosciences|April 15, 2018
Who is the infector? Epidemic models with symptomatic and asymptomatic casesKa Yin Leung, Pieter Trapman, Tom Britton
Journal of Mathematical Biology|April 23, 2025
Modelling the spread of two successive SIR epidemics on a configuration model networkFrank Ball, Abid Ali Lashari, David Sirl, et al.
Epidemics|April 7, 2015
Five challenges for spatial epidemic modelsSteven Riley, Ken Eames, Valerie Isham, et al.
Epidemics|April 7, 2015
Five challenges for stochastic epidemic models involving global transmissionTom Britton, Thomas House, Alun L Lloyd, et al.
Journal of the Royal Society, Interface|September 2, 2016
Inferring R0 in emerging epidemics-the effect of common population structure is smallPieter Trapman, Frank Ball, Jean-Stéphane Dhersin, et al.
Pageof 3