PUBLISHED OR ACCEPTED IN
REFEREED JOURNALS (inverse chronological order)
J118. D Zhang,
T Britton
(2024+). Epidemic models with manual and digital contact tracing
allowing delays. (2024). To appear in
Math
Biosciences.
ArXiv preprint.
J117. P Gerlee, H Thoreén, A S Joöud, T Lundh, ASpreco, A
Nordlund, T Brezicka,
T Britton, M Kjellberg, H
Kaöllberg, A Tegnell, L Brouwers, T Timpka. (2024).
The
Lancet Digital Health. 6:8, E543-E544.
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(24)00144-4/fulltext
J116. D Zhang,
T Britton (2024+). Epidemic models with
digital and manual contact tracing. Conditionally accepted
J.
Appl. Prob.. https://arxiv.org/abs/2211.12869
J115. M El Khalifi, T Britton (2023). SIRS epidemics with
individual heterogeneity of immunity waning.
J
Theor Biol.
J114. ME Khalifi,
T Britton (2022). Extending SIRS
epidemics to allow for gradual waning of immunity.
J Roy Soc Interface 20 (206).
https://doi.org/10.1098/rsif.2023.0042
J113. F Bergström, F Gunther, M Höhle,
T Britton.
(2022). Bayesian Nowcasting with leading indicators applied to
COVID-19 fatalities in Sweden.
PLoS Comp Biol, 18:12.
https://doi.org/10.1371/journal.pcbi.1010767
J112. Y Zhang,
T Britton, X Zhou (2022). Monitoring
real-time transmission heterogeneity from incidence data.
PLoS
Comp Biol, 18:12,
https://doi.org/10.1371/journal.pcbi.1010078.
MedRxiv
J111.
Britton T and Leskelä L (2023). Optoimal
intervention strategies for minimizing total incidence during an
epidemic.
SIAM
J Appl Math, 83:354-375,
https://doi.org/10.1137/22M1504433.
ArXiv.
J109. D Zhang,
T Britton (2022). Analysing the effect of
Test-and-Trace strategy in an SIR Epidemic model.
Bull Math.
Biol. 84:105.
https://doi.org/10.1007/s11538-022-01065-9
ArXiv.
J108. Ball F and
Britton T (2021).
Epidemics
on networks with preventive rewiring.
Rand Str Alg.
2021:1-48.
J107.
Britton T (2021). Quantifying the preventive effect
of wearing face masks.
Proc Roy Soc A,
477:
20210151.
J106. Britton, T, Ball F, Trapman P. (2021). The risk
for a new epidemic wave - and how it depends on R0, the
current immunity level and current restrictions. Royal
Society Open Science.
https://doi.org/10.1098/rsos.210386
MedRxiv.
Technical
report.
J105.
Britton, T. (2020). Reproduktionstal, immunitet
och vaccination.
Svepet,
38, 4:8-9 (in Swedish, klick nr 4, 2020).
J104. Thompson R N, Hollingsworth T D, Isham V, Arribas-Bel D ,
Ashby B,
Britton T,
et al. (2020)
J103. Malmberg H. and Britton, T. (2020). Inflow
restrictions can prevent epidemics when contact tracing
efforts are effective but have limited capacity. Journal
Royal Society: Interface, 17:170,
https://doi.org/10.1098/rsif.2020.0351. MedRxiv.
J102. Britton, T, Ball F, Trapman P. (2020). A
mathematical model reveals the influence of population
heterogeneity on herd immunityto SARS-CoV2. Science.
369
(6505), pp. 846-849.
DOI: 10.1126/science.abc6810
J101. Zhang, Y., Leitner, T., Albert, J., Britton, T.
(2020). Inferring transmission heterogeneity using virus
genealogies: estimation and targeted prevention.
PLoS Comp
Biol,
https://doi.org/10.1371/journal.pcbi.1008122
J100. Ronquist, F., M. Forshage, S. Häggqvist, D. Karlsson, R. Hovmöller, J. Bergsten, K. Holston, T. Britton, J. Abenius, et al. (2018).
Completing Linnaeus's inventory of the Swedish insect fauna:
Only 5000 species left.
PLoS One,
15(3):
e0228561.
J99. Hanson, D., Strömdahl, S., Leung, K-Y.,
Britton, T.
(2020). Introducing pre-exposure prophylaxis to prevent HIV
acquisition among men who have sex with men in Sweden: insights
from a mathematical pair-formation model.
Submitted.
British Medical Journal (BMJ
Open),
10:2,
http://dx.doi.org/10.1136/bmjopen-2019-033852
J98.
Britton, T. Epidemic models on social networks -
with inference. (2020). To appear in
Statistica
Neerlandica (invited for special
issue on Network modelling and analysis),
74:3, 222-241,
https://doi.org/10.1111/stan.12203.
Arxiv.
Technical
report. I have without success tried to publish an Errata:
It is the sentence
appearing just
below the second displayed formula of Result 2 ("The basic
..."). It should be replaced by: "The basic reproduction number for
the two models also having random global contacts is as
above but adding the term 𝛽G in the Reed-Frost model and the term
𝛽G∕𝛾 in the Markov model."
J97.
Britton, T. (2019). Directed preferential
attachment models.
J. Appl. Prob.
57(1): 122-136, https://doi.org/10.1017/jpr.2019.80 .
ArXiv.
Technical
report.
J96. Stocks, T., Martin, L., Kuhlmann-Berenzon, S,
Britton,
T. (2020). Dynamic modelling of hepatitis C transmission
among people who inject drugs.
Epidemics, 30:
100378.
BioRxiv.
J95.
Britton, T. (2020). Basic stochastic transmission
models and their inference. In
Handbook of Infectious
Disease Data Analysis. CRC Press.
Arxiv.
Technical
report.
J94. Spricer, K. and
Britton, T. (2019). An epidemic
model on a weighted network.
Network
Science,
J93.
Britton, T. and Pardoux, E. (2019). Stochastic
epidemics in homogeneous communities. Chapter 1 (143 pages) in
Britton, T. and Pardoux, E. (Eds.).
Stochastic epidemic
models with inference.
Springer
Lecture Notes in Mathematics 2255 (see also M5 above).
ArXiv.
J92. Giardina, F., Romero-Severson E.O., Axelsson, M., Svedhem,
V., Leitner T.K.,
Britton T., and Albert J.
(2019). Decreasing HIV-1 incidence and undiagnosed HIV-1 cases
in Sweden based on multiple biomarker estimate of infection
times.
Int. J. Epid,
48: 1795-1803
J91.
Britton, T., Leung, K. and Trapman, P. (2019). Who
is the infector? General multi-type epidemics and real-time
susceptibility processes.
Adv. Appl. Prob.
51: 606-631.
Arxiv.
Technical
report.
J90. Hansson, D., Leung, K.,
Britton, T. and Strömdahl,
S. (2019). A dynamic network model to disentangle the roles of
steady partnerships and casual contacts for HIV transmission
among MSM.
Epidemics,
https://doi.org/10.1016/j.epidem.2019.02.001.
Technical
report.
J89. Ball, F.,
Britton, T., Leung, K. and Sirl, D.
(2019). A stochastic SIR epidemic model with preventive dropping
of edges.
J.
Math. Biol.
78:1875-1951. ArXiv.
J88.
Britton, T. and Scalia Tomba G. (2019). Estimation
in emerging epidemics: biases and remedies.
Journal Royal
Society: Interface. 16:20180670,
https://doi.org/10.1098/rsif.2018.0670.
Arxiv.
J87. Hansson, D., Fridlund, V., Stenqvist, V.,
Britton, T.
and Liljeros, F. (2018). Inferring individual sexual action
dispositions from egocentric network data on dyadic sexual
outcomes.
PLoS
One, 13:e0207116,
https://doi.org/10.1371/journal.pone.0207116.
Technical
report.
J86. Leung, K., Ball, F., Sirl, D. and
Britton, T.
(2018). Individual preventive social distancing during an
epidemic may have negative population-level outcomes.
Journal Royal
Society: Interface, 15:20180296.
https://doi.org/10.1098/rsif.2018.0296.
Arxiv.
J85. Stocks, T.,
Britton, T. and Höhle, M. (2020). Model
selection and parameter estimation for dynamic epidemic models
via iterated filtering: application to rotavirus in Germany.
Biostatistics,
21(3): 400-416. kxy057,
https://doi.org/10.1093/biostatistics/kxy057.
J84. Leung, K, Trapman, P. and
Britton, T. (2018). Who
is the infector? Epidemic models with symptomatic and
asymptomatic cases.
Math. Biosci. 301:
190-198.
Arxiv.
J83. Ouedraogo, D. and
Britton, T. (2017). SEIRS
epidemics with disease fatalities in growing populations.
Math. Biosci.
298:45-59.
Arxiv.
J82.
Britton, T, Deijfen, M and Lopes, F. (2018). A
spatial epidemic model with site contamination.
Markov proc. rel. fields,
24: 25-38.
Arxiv.
J81. Traoré, A. and
Britton, T. (2017). A stochastic
vector-borne epidemic model: quasi-stationarity and
extinction.
Math. Biosci.
289: 89-95.
J80. Giardina, F., Romero-Severson E.O., Albert J.,
Britton
T., and Leitner T.K. (2017). Inference of
transmission network structure from HIV phylogenetic trees.
PLoS Comp
Biol. 13:e1005316.
J79.
Britton T., Juher, D. and Saldana, J. (2016): A
network model with preventive rewiring: comparative analysis of
the initial phase.
Bull Math Biol. 78:2427-2454.
ArXiv pdf.
Technical
report.
Erratum:
Bull Math Biol. 79:1687-1689.
J78. Ball F.G.,
Britton T., Trapman P. (2017): An
epidemic in a dynamic population with importation of infectives.
Ann. Appl. Prob. 27:242-274.
ArXiv pdf.
Technical
report.
J77. E. Kenah,
T. Britton, M. E. Halloran, and I. M.
Longini, Jr. (2016). Molecular infectious disease epidemiology:
Survival analysis and algorithms linking phylogenies to
transmission trees.
PLoS
Computational Biology 12(4):
e1004869.
ArXiv pdf.
J76. Trapman P., Ball F., Dhersin J-S, Tran V. C., Wallinga J.
and
Britton, T. (2016). Inferring R_0 in emerging
epidemics - the effect of common population structure is small.
J. of Roy.
Soc Interface., 13:20160288.
J75. Britton, S. and
Britton, T. (2016): Ebola - få
smittade men många drabbade (in Swedish).
Läkartidningen
2016;113:DUWX
J74. Spricer K. and
Britton, T. (2015): The
configuration model for partially directed graphs.
J. Stat.
Phys. 161:965-985.
ArXiv pdf.
J73. J. Malmros, N. Masuda &
T. Britton (2016): Random Walks on Directed
Networks: Inference and Respondent-driven Sampling.
J. Official
Statistics,
32:433-459.
ArXiv pdf.
Technical
report.
J72
Britton, T. and Giardina, F. (2016): Introduction to
statistical inference for infectious diseases.
Journal de
la Société Francaise de Statistique (special invited
issue on inference for infectious diseases).
157:53-70.
ArXiv pdf.
Technical
report.
J71 Malmros, J., Liljeros F. and
Britton, T. (2015):
Respondent driven sampling and an unusual epidemic.
J. Appl. Prob.
53:518-530.
ArXiv pdf.
Technical
report.
J70 L. Matrajt,
T. Britton,
M. E. Halloran and I.M. Longini Jr. (2015). One versus two
doses: what is the best use of vaccine in an influenza pandemic?
Epidemics,
13:
17-27.
J69 Y Yang, E Kenah, L Fang, Y Zhang, E Halloran, M Ma, S Liang,
T Britton, D Chao, K
Liu, X Li, W Cao, Z Feng, I Longini. (2015). Household
transmissibility of Avian Influenza A(H7N9) Virus, China,
February to May 2013 and October 2013 to March 2014.
Eurosurveillance, 20(10):
21056. Available online:
http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=21056
J68 Ball, F.G.,
Britton, T
and Neal, P. (2016). On expected durations of birth-death
processes, with applications to branching processes and
SIS-epidemics.
J. Appl. Prob.
53:203-215.
ArXiv
pdf.
J67 F.G. Ball;
T. Britton;
T. House; V. Isham; D. Mollison; L. Pellis; G. Scalia-Tomba.
(2015). Seven challenges for metapopulation models of epidemics,
including households models.
Epidemics,
10:
63-67.
J66
T. Britton, T.
House, A.L. Lloyd, D. Mollison, S. Riley and P.Trapman. (2015).
Eight challenges for stochastic epidemic models involving global
transmission. To appear in
Epidemics,
10:
54-57.
J65
T. Britton and P.
Trapman (2014): Stochastic epidemics in growing populations.
Bull Math Biol.
76:985-996.
ArXiv pdf.
Technical
report.
J64. J.E. Björnberg,
T.
Britton, E.I. Broman and E. Nathan (2014): A stochastic
model for virus growth in a cell population.
J. Appl. Prob,
51: 599-612.
J63
. T. Britton and P.
Trapman (2014): Inferring global network properties from
egocentric data with applications to epidemics.
Math. Med. Biol.
32: 101-114.
ArXiv
pdf.
Technical
report
J62. X. Lu; J. Malmros; F. Liljeros;
T. Britton (2013): Respondent-driven Sampling on
Directed Networks.
Electr. J. Stat. 7: 292-322.
J61. F. Ball, T Britton and Dave Sirl. (2013) A network with
tunable clustering, degree correlation and degree distribution,
and an epidemic thereon.
J.
Math. Biol.
66:
979-1019.
ArXiv pdf,
Technical
report.
J60
T. Britton and P.
Trapman: Maximizing the size of the giant. (2012).
J. Appl. Prob.
49:1156-1165
. ArXiv pdf.
J59
T. Britton and D.
Lindenstrand: Inhomogeneous epidemics on weighted networks.
(2012).
Math. Biosci.
240:124-131
. ArXiv pdf.
J58
T. Britton, M.
Deijfen and F. Liljeros. (2011):
A weighted configuration model and inhomogeneous
epidemics.
J.
Stat. Phys. 145:1368-1384.
ArXiv pdf.
J57.
T. Britton,
M. Lindholm and T. Turova. (2011). A dynamic network in a
dynamic population: asymptotic properties.
J. Appl. Prob.
48: 1163-1178.
ArXiv pdf.
J56. S. Höhna, T. Stadler, F. Ronquist &
T. Britton. (2011).
Inferring speciation and extinction rates under different
species sampling schemes.
Molecular Biology and Evolution. 28:2577-2589
.
J55. X. Lu, L.
Bengtsson,
T. Britton,
M. Camitz, B Kim, A. Thorson & F Liljeros. (2012): The
sensitivity of respondent-driven sampling method.
J. Roy. Stat. Soc, Ser A.
175:
191–216.
J54.
Britton, T.
Kypraios T. and O'Neill P.D. (2011), Statistical models for
epidemic models with three levels of mixing.
Scandinavian Journal of
Statistics. 38:578-599.
ArXiv
pdf.
J53. Linder, M.,
Britton, T.,
Sennblad,
B.: Evaluation of Bayesian Models of Substitution Rate Evolution
-- Parental guidance vs. Mutual Independence. (2011).
Systematic
Biology,
60: 1-14.
J52. Ball, F.,
Britton, T.
and Sirl, D. (2011). Household epidemic models with varying
infection response.
J.
Math. Biol.
63:
309-337. pdf
J51.
Britton, T. and
Lindholm, M.: Dynamic random networks in dynamic populations.
(2010)
J. Stat.
Phys. 139:
518-535. preprint