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Bastien Reyné 1 ; Quentin Richard 1 ; Christian Selinger 1, 2 ; Mircea T. Sofonea 1 ; Ramsès Djidjou-Demasse 1 ; Samuel Alizon 1, 3
@article{MMNP_2022_17_a1, author = {Bastien Reyn\'e and Quentin Richard and Christian Selinger and Mircea T. Sofonea and Rams\`es Djidjou-Demasse and Samuel Alizon}, title = {Non-Markovian modelling highlights the importance of age structure on {Covid-19} epidemiological dynamics}, journal = {Mathematical modelling of natural phenomena}, eid = {7}, publisher = {mathdoc}, volume = {17}, year = {2022}, doi = {10.1051/mmnp/2022008}, language = {en}, url = {http://geodesic.mathdoc.fr/articles/10.1051/mmnp/2022008/} }
TY - JOUR AU - Bastien Reyné AU - Quentin Richard AU - Christian Selinger AU - Mircea T. Sofonea AU - Ramsès Djidjou-Demasse AU - Samuel Alizon TI - Non-Markovian modelling highlights the importance of age structure on Covid-19 epidemiological dynamics JO - Mathematical modelling of natural phenomena PY - 2022 VL - 17 PB - mathdoc UR - http://geodesic.mathdoc.fr/articles/10.1051/mmnp/2022008/ DO - 10.1051/mmnp/2022008 LA - en ID - MMNP_2022_17_a1 ER -
%0 Journal Article %A Bastien Reyné %A Quentin Richard %A Christian Selinger %A Mircea T. Sofonea %A Ramsès Djidjou-Demasse %A Samuel Alizon %T Non-Markovian modelling highlights the importance of age structure on Covid-19 epidemiological dynamics %J Mathematical modelling of natural phenomena %D 2022 %V 17 %I mathdoc %U http://geodesic.mathdoc.fr/articles/10.1051/mmnp/2022008/ %R 10.1051/mmnp/2022008 %G en %F MMNP_2022_17_a1
Bastien Reyné; Quentin Richard; Christian Selinger; Mircea T. Sofonea; Ramsès Djidjou-Demasse; Samuel Alizon. Non-Markovian modelling highlights the importance of age structure on Covid-19 epidemiological dynamics. Mathematical modelling of natural phenomena, Tome 17 (2022), article no. 7. doi : 10.1051/mmnp/2022008. http://geodesic.mathdoc.fr/articles/10.1051/mmnp/2022008/
[1] Rapid spread of the SARS-CoV-2 Delta variant in some French regions, June 2021 Eurosurveillance 2021 2100573
, , , , , , ,[2] SARS-CoV-2 virulence evolution: Avirulence theory, immunity and trade-offs Journal of Evolutionary Biology 2021 1867 1877
,[3] R.M. Anderson and R.M. May, Infectious diseases of humans: dynamics and control. Oxford University Press (1992).
[4] Positive network assortativity of influenza vaccination at a high school: implications for outbreak risk and herd immunity PLOS ONE 2014 e87042
, , , , , , ,[5] Estimating dates of origin and end of COVID-19 epidemics Peer Community Journal 2021 e70
, , ,[6] multisensi: Multivariate Sensitivity Analysis 2018 R package version 2.1-1
, ,[7] The French connection: the first large population-based contact survey in France relevant for the spread of infectiousdiseases PLOS ONE 2015 e0133203
, , , , , , , , ,[8] F. Brauer, C. Castillo-Chavez and Z. Feng, vol. 32 of Mathematical models in epidemiology. Springer (2019).
[9] lhs: Latin Hypercube Samples 2020 R package version 1.1.1
[10] Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study BMJ 2021 n579
, , , , ,[11] Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England Science 2021 eabg3055
, , , , , , , , , , , , , , , , , , , , , ,[12] Increased mortality in community-tested cases of SARS-CoV-2 lineage B.1.1.7. Nature 2021 270 274
, , , , ,[13] Age-dependent effects in the transmission and control of COVID-19 epidemics Nat. Med 2020 1205 1211
, , , , ,[14] On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations J. Math. Biol 1990 365 382
, ,[15] Rcpp: Seamless R and C++ integration J. Stat. Softw 2011 1 18
,[16] SIR-based mathematical modeling of infectious diseases with vaccination and waning immunity J. Comput. Sci 2019 101027
, ,[17] Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing Science 2020 eabb6936
, , , , , , , ,[18] Spatial heterogeneity and the persistence of infectious diseases J. Theor. Biol 2004 349 359
, ,[19] Detecting rapid spread of sars-CoV-2 variants Emerg. Infectious Dis 2021 eid2705.210397
, , , , , , , , ,[20] Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts Lancet Global Health 2020 e488 e496
, , , , , , , , , , , , , , , , , , , , ,[21] The mathematics of infectious diseases SIAM Rev 2000 599 653
[22] Mathematical theories of populations: demographics, genetics and epidemics SIAM 1975
[23] Monitoring the proportion of the population infected by SARS-CoV-2 using age-stratified hospitalisation and serological data: a modelling study Lancet Public Health 2021 e408 e415
, , , , , , , , , , ,[24] On a new perspective of the basic reproduction number in heterogeneous environments J. Math. Biol 2012 309 348
[25] H. Inaba, Age-structured population dynamics in demography and epidemiology. Springer (2017).
[26] sensitivity: Global Sensitivity Analysis of Model Outputs 2021 R package version 1.25.0
, , , , , , , , , , , , , , , , , , , , , , , , ,[27] Predictions of COVID-19 dynamics in the UK: Short-term forecasting and analysis of potential exit strategies PLOS Comput. Biol 2021 e1008619
, , , , , , , , , ,[28] M.J. Keeling and P. Rohani, Modeling Infectious Diseases in Humans and Animals. Princeton University Press (2008).
[29] A contribution to the mathematical theory of epidemics Proc. Roy. Soc. London A 1927 700 721
,[30] A modelling study investigating short and medium-term challenges for COVID-19 vaccination: From prioritisation to the relaxation of measures EClinicalMedicine 2021 101001
, , , , , , , , , , , ,[31] Early dynamics of transmission and control of COVID-19: a mathematical modelling study Lancet Infect. Diseases 2020 553 558
, , , , , , , , , , , , , , , , , , , , ,[32] Evolution of outcomes for patients hospitalised during the first 9 months of the SARS-CoV-2 pandemic in France: a retrospective national surveillance data analysis Lancet Regl. Health 2021 100087
, , , , , , , , ,[33] Destabilization of epidemic models with the inclusion of realistic distributions of infectious periods Proc. Royal Soc. Lond. Ser B: Biol. Sci 2001 985 993
[34] Spatial heterogeneity in epidemic models J. Theor. Biol 1996 1 11
,[35] Role of meteorological factors in the transmission of SARS-CoV-2 in the United States Nat. Commun 2021 3602
, , , ,[36] P. Magal, Compact attractors for time-periodic age-structured populationmodels (2001).
[37] First-dose mRNA vaccination is sufficient to reactivate immunological memory to SARS-CoV-2 in subjects who have recovered from COVID-19 J. Clin. Invest 2021 e149150
, , , , , , , , , , , , , , , , , , , , ,[38] Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study Lancet Infect. Dis 2021 793 802
, , , ,[39] Time variations in the generation time of an infectious disease: Implications for sampling to appropriately quantify transmission potential Math. Biosci. Eng 2010 851 869
[40] A. Pazy, Vol. 44 of Semigroups of linear operators and applications to partial differential equations. Springer Science Business Media (2012).
[41] Public Health England, COVID-19 vaccine surveillance report - week 23. Tech. rep. Public Health England (2021).
[42] R Core Team, R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria (2021).
[43] Age-structured non-pharmaceutical interventions for optimal control of COVID-19 epidemic PLOS Comput. Biol 2021 e1008776
, , , ,[44] Human-vector malaria transmission model structured by age, time since infection and waning immunity Nonlinear Anal.: Real World Appl 2022 103393
, , ,[45] Philosophical Transactions of the Royal Society B 2021
[46] Estimating the burden of SARS-CoV-2 in France Science 2020 208 211
, , , , , , , , , , , , , , , ,[47] A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Saisana and S. Tarantola, Global sensitivity analysis: the primer. Wiley (2008).
[48] SARS-CoV-2 Delta VOC in Scotland: demographics, risk of hospital admission, and vaccine effectiveness The Lancet 2021 2461 2462
, , ,[49] Memory is key in capturing COVID-19 epidemiological dynamics Epidemics 2021 100459
, , , , , ,[50] Mathematical models of contact patterns between age groups for predicting the spread of infectious diseases Math. Biosci. Eng 2013 1475
, ,[51] Estimates of the severity of coronavirus disease 2019: a model-based analysis Lancet Infect. Dis. 2020 669 677
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,[52] Simulating the spread of COVID-19 via a spatially-resolved susceptible–exposed–infected–recovered–deceased (SEIRD) model with heterogeneous diffusion Appl. Math. Lett 2021 106617
, , , , , , , ,[53] How generation intervals shape the relationship between growth rates and reproductive numbers Proc. Roy. Soc. B: Biol. Sci 2007 599 604
,[54] Using data on social contacts to estimate age-specific transmission parameters for respiratory-spread infectious agents Am. J. Epidemiol 2006 936 944
, ,[55] Using a partial differential equation with Google Mobility data to predict COVID-19 in Arizona Math. Biosci. Eng. 2020 4891 4904
, , ,[56] A global assessment of the impact of school closure in reducing COVID-19 spread Philos. Trans. Royal Soc. A 2022 20210124
, , , , , , , , , , , , ,[57] Vaccination against SARS-CoV-2 and disease enhancement – knowns and unknowns Exp. Rev. Vaccines 2020 691 698
, , , ,[58] Transmission dynamics of an outbreak of the COVID-19 Delta Variant B.1.617.2 – Guangdong Province, China, May–June 2021 China CDC Weekly 2021 584 586
, , , , , , , , , , , , , , , , , , , , , , , ,Cité par Sources :