Dynamical systems running on the top of complex networks have been extensively investigated for decades. But this topic still remains among the most relevant issues in complex network theory due to its range of applicability. The contact process (CP) and the susceptible–infected–susceptible (SIS) model are used quite often to describe epidemic dynamics. Despite their simplicity, these models are robust to predict the kernel of real situations. In this work, we review concisely both processes that are well-known and very applied examples of models that exhibit absorbing-state phase transitions. In the epidemic scenario, individuals can be infected or susceptible. A phase transition between a disease-free (absorbing) state and an active stationary phase (where a fraction of the population is infected) are separated by an epidemic threshold. For the SIS model, the central issue is to determine this epidemic threshold on heterogeneous networks. For the CP model, the main interest is to relate critical exponents with statistical properties of the network.

1.
M.
Henkel
,
H.
Hinrichsen
,
S.
Lübeck
, and
M.
Pleimling
,
Non-equilibrium Phase Transitions
(
Springer
,
Dordrecht, Netherlands
,
2008
), Vol. 1.
2.
J.
Marro
and
R.
Dickman
,
Nonequilibrium Phase Transitions in Lattice Models
(
Cambridge University Press
,
Cambridge
,
1999
).
3.
O.
Diekmann
and
J.
Heesterbeek
,
Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation
(
John Wiley & Sons
,
New York
,
2000
).
4.
R. M.
Anderson
and
R. M.
May
,
Infectious Diseases in Humans
(
Oxford University Press
,
Oxford
,
1992
).
5.
T. E.
Harris
, “
Contact interactions on a lattice
,”
Ann. Prob.
2
,
969
988
(
1974
).
6.
Once a set of models share the same symmetry properties, irrespective of the microscopic details of their dynamical rules, they belong to a single universality class and they should have the same critical exponents and scaling functions.
7.
S. R.
Broadbent
and
J. M.
Hammersley
, “
Percolation processes: I. Crystals and mazes
,”
Proc. Camb. Phil. Soc.
53
,
629
(
1957
).
8.
S. N.
Dorogovtsev
,
A. V.
Goltsev
, and
J. F. F.
Mendes
, “
Critical phenomena in complex networks
,”
Rev. Mod. Phys.
80
,
1275
1335
(
2008
).
9.
R.
Pastor-Satorras
and
A.
Vespignani
, “
Epidemic spreading in scale-free networks
,”
Phys. Rev. Lett.
86
,
3200
3203
(
2001
).
10.
C.
Castellano
and
R.
Pastor-Satorras
, “
Thresholds for epidemic spreading in networks
,”
Phys. Rev. Lett.
105
,
218701
(
2010
).
11.
A. V.
Goltsev
,
S. N.
Dorogovtsev
,
J. G.
Oliveira
, and
J. F. F.
Mendes
, “
Localization and spreading of diseases in complex networks
,”
Phys. Rev. Lett.
109
,
128702
(
2012
).
12.
S. C.
Ferreira
,
C.
Castellano
, and
R.
Pastor-Satorras
, “
Epidemic thresholds of the susceptible-infected-susceptible model on networks: A comparison of numerical and theoretical results
,”
Phys. Rev. E
86
,
041125
(
2012
).
13.
J. P.
Gleeson
, “
High-accuracy approximation of binary-state dynamics on networks
,”
Phys. Rev. Lett.
107
,
068701
(
2011
).
14.
H. K.
Lee
,
P.-S.
Shim
, and
J. D.
Noh
, “
Epidemic threshold of the susceptible-infected-susceptible model on complex networks
,”
Phys. Rev. E
87
,
062812
(
2013
).
15.
E.
Cator
and
P.
Van Mieghem
, “
Second-order mean-field susceptible-infected-susceptible epidemic threshold
,”
Phys. Rev. E
85
,
056111
(
2012
).
16.
A. S.
Mata
and
S. C.
Ferreira
, “
Pair quenched mean-field theory for the susceptible-infected-susceptible model on complex networks
,”
Eur. Lett.
103
,
48003
(
2013
).
17.
G.
Ódor
, “
Spectral analysis and slow spreading dynamics on complex networks
,”
Phys. Rev. E
88
,
032109
(
2013
).
18.
M.
Boguñá
,
C.
Castellano
, and
R.
Pastor-Satorras
, “
Nature of the epidemic threshold for the susceptible-infected-susceptible dynamics in networks
,”
Phys. Rev. Lett.
111
,
068701
(
2013
).
19.
C.
Castellano
and
R.
Pastor-Satorras
, “
Routes to thermodynamic limit on scale-free networks
,”
Phys. Rev. Lett.
100
,
148701
(
2008
).
20.
H.
Hong
,
M.
Ha
, and
H.
Park
, “
Finite-size scaling in complex networks
,”
Phys. Rev. Lett.
98
,
258701
(
2007
).
21.
M.
Boguñá
,
C.
Castellano
, and
R.
Pastor-Satorras
, “
Langevin approach for the dynamics of the contact process on annealed scale-free networks
,”
Phys. Rev. E
79
,
036110
(
2009
).
22.
S. C.
Ferreira
,
R. S.
Ferreira
, and
R.
Pastor-Satorras
, “
Quasistationary analysis of the contact process on annealed scale-free networks
,”
Phys. Rev. E
83
,
066113
(
2011
).
23.
S. C.
Ferreira
,
R. S.
Ferreira
,
C.
Castellano
, and
R.
Pastor-Satorras
, “
Quasistationary simulations of the contact process on quenched networks
,”
Phys. Rev. E
84
,
066102
(
2011
).
24.
C.
Castellano
and
R.
Pastor-Satorras
, “
Non-mean-field behavior of the contact process on scale-free networks
,”
Phys. Rev. Lett.
96
,
038701
(
2006
).
25.
M.
Catanzaro
,
M.
Boguñá
, and
R.
Pastor-Satorras
, “
Generation of uncorrelated random scale-free networks
,”
Phys. Rev. E
71
,
027103
(
2005
).
26.
G.
Caldarelli
,
Scale-Free Networks: Complex Webs in Nature and Technology
(
Oxford University Press
,
Oxford
,
2007
).
27.
A.
Barrat
,
M.
Barthélemy
, and
A.
Vespignani
,
Dynamical Processes on Complex Networks
(
Cambridge University Press
,
Cambridge
,
2008
).
28.
R.
Albert
and
A.-L.
Barabási
, “
Statistical mechanics of complex networks
,”
Rev. Mod. Phys.
74
,
47
97
(
2002
).
29.
S. N.
Dorogovtsev
and
J. F. F.
Mendes
, “
Evolution of networks
,”
Adv. Phys.
51
,
1079
1187
(
2002
).
30.
M.
Boguñá
,
R.
Pastor-Satorras
, and
A.
Vespignani
, “
Cut-offs and finite size effects in scale-free networks
,”
Eur. Phys. J. B
38
,
205
210
(
2004
).
31.
R.
Dickman
and
R.
Vidigal
, “
Quasi-stationary distributions for stochastic processes with an absorbing state
,”
J. Phys. A: Math. Gen.
35
,
1147
1166
(
2002
).
32.
M. M.
de Oliveira
and
R.
Dickman
, “
How to simulate the quasistationary state
,”
Phys. Rev. E
71
,
016129
(
2005
).
33.
E.
Pugliese
and
C.
Castellano
, “
Heterogeneous pair approximation for voter models on networks
,”
Europhys. Lett.
88
,
58004
(
2009
).
34.
S.
Gómez
,
A.
Arenas
,
J.
Borge-Holthoefer
,
S.
Meloni
, and
Y.
Moreno
, “
Discrete-time Markov chain approach to contact-based disease spreading in complex networks
,”
Eur. Lett.
89
,
38009
(
2010
).
35.
S.
Gómez
,
J.
Gómez-Gardeñes
,
Y.
Moreno
, and
A.
Arenas
, “
Nonperturbative heterogeneous mean-field approach to epidemic spreading in complex networks
,”
Phys. Rev. E
84
,
036105
(
2011
).
36.
R.
Juhász
,
G.
Ódor
,
C.
Castellano
, and
M. A.
Muñoz
, “
Rare-region effects in the contact process on networks
,”
Phys. Rev. E
85
,
066125
(
2012
).
37.
A. S.
Mata
and
S. C.
Ferreira
, “
Multiple transitions of the susceptible-infected-susceptible epidemic model on complex networks
,”
Phys. Rev. E
91
,
012816
(
2015
).
38.
C.-R.
Cai
,
Z.-X.
Wu
,
M. Z. Q.
Chen
,
P.
Holme
, and
J.-Y.
Guan
, “
Solving the dynamic correlation problem of the susceptible-infected-susceptible model on networks
,”
Phys. Rev. Lett.
116
,
258301
(
2016
).
39.
C.
Castellano
and
R.
Pastor-Satorras
, “
Cumulative merging percolation and the epidemic transition of the susceptible-infected-susceptible model in networks
,”
Phys. Rev. X
10
,
011070
(
2020
).
40.
T.
Mountford
,
D.
Valesin
, and
Q.
Yao
, “
Metastable densities for the contact process on power law random graphs
,”
Electron. J. Probab.
18
,
36
(
2013
).
41.
D. H.
Silva
,
S. C.
Ferreira
,
W.
Cota
,
R.
Pastor-Satorras
, and
C.
Castellano
, “
Spectral properties and the accuracy of mean-field approaches for epidemics on correlated power-law networks
,”
Phys. Rev. Res.
1
,
033024
(
2019
).
42.
S.
Chatterjee
and
R.
Durrett
, “
Contact processes on random graphs with power law degree distributions have critical value 0
,”
Ann. Probab.
37
,
2332
2356
(
2009
).
43.
N. T. J.
Bailey
,
The Mathematical Theory of Infectious Diseases and Its Applications
(
Charles Griffin Company Limited
,
London
,
1975
).
44.
M.
Newman
,
Networks: An Introduction
(
Oxford University Press, Inc.
,
New York, NY
,
2010
).
45.
R. C.
Hilborn
,
Chaos and Nonlinear Dynamics: An Introduction for Scientists and Engineers
(
Oxford University Press
,
2000
).
46.
F.
Chung
,
L.
Lu
, and
V.
Vu
, “
Spectra of random graphs with given expected degrees
,”
Proc. Natl. Acad. Sci. U.S.A.
100
,
6313
6318
(
2003
).
47.
C.
Castellano
and
R.
Pastor-Satorras
, “
Competing activation mechanisms in epidemics on networks
,”
Sci. Rep.
2
,
371
(
2012
).
48.
C.
Castellano
and
R.
Pastor-Satorras
, “
Relating topological determinants of complex networks to their spectral properties: Structural and dynamical effects
,”
Phys. Rev. X
7
,
041024
(
2017
).
49.
G.
St-Onge
,
J.-G.
Young
,
E.
Laurence
,
C.
Murphy
, and
L. J.
Dubé
, “
Phase transition of the susceptible-infected-susceptible dynamics on time-varying configuration model networks
,”
Phys. Rev. E
97
,
022305
(
2018
).
50.
W.
Cota
,
A. S.
Mata
, and
S. C.
Ferreira
, “
Robustness and fragility of the susceptible-infected-susceptible epidemic models on complex networks
,”
Phys. Rev. E
98
,
012310
(
2018
).
51.
C.
Castellano
and
R.
Pastor-Satorras
, “
Castellano and Pastor-Satorras reply
,”
Phys. Rev. Lett.
98
,
029802
(
2007
).
52.
M.
Ha
,
H.
Hong
, and
H.
Park
, “
Comment on “Non-mean-field behavior of the contact process on scale-free networks”
,”
Phys. Rev. Lett.
98
,
029801
(
2007
).
53.
D.
ben Avraham
and
J.
Köhler
, “
Mean-field (n, m)-cluster approximation for lattice models
,”
Phys. Rev. A
45
,
8358
8370
(
1992
).
54.
A. S.
Mata
,
R. S.
Ferreira
, and
S. C.
Ferreira
, “
Heterogeneous pair-approximation for the contact process on complex networks
,”
New J. Phys.
16
,
053006
(
2014
).
55.
D. T.
Gillespie
, “
A general method for numerically simulating the stochastic time evolution of coupled chemical reactions
,”
J. Comput. Phys.
22
,
403
434
(
1976
).
56.
W.
Cota
and
S. C.
Ferreira
, “
Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks
,”
Comput. Phys. Commun.
219
,
303
312
(
2017
).
57.
R. S.
Sander
,
S. C.
Ferreira
, and
R.
Pastor-Satorras
, “
Phase transitions with infinitely many absorbing states in complex networks
,”
Phys. Rev. E
87
,
022820
(
2013
).
58.
U. C.
Täuber
,
Critical Dynamics
(
Cambridge University Press
,
Cambridge
,
2014
).
59.
Finite Size Scaling, edited by J. L. Cardy, Current Physics—Sources and Comments (North-Holland, Amsterdam, 1988), Vol. 2.
60.
R.
Dickman
, “
Critical exponents for the restricted sandpile
,”
Phys. Rev. E
73
,
036131
(
2006
).
61.
D. J.
Watts
and
S. H.
Strogatz
, “
Collective dynamics of ’small-world’ networks
,”
Nature
393
,
440
442
(
1998
).
62.
R. S.
Ferreira
and
S. C.
Ferreira
, “
Critical behavior of the contact process on small-world networks
,”
Eur. Phys. J. B
86
,
462
(
2013
).
63.
K.
Binder
and
D.
Heermann
,
Monte Carlo Simulation in Statistical Physics: An Introduction
(
Springer
,
2010
).
64.
R.
Pastor-Satorras
,
C.
Castellano
,
P.
Van Mieghem
, and
A.
Vespignani
, “
Epidemic processes in complex networks
,”
Rev. Mod. Phys.
87
,
925
979
(
2015
).
65.
M.
Boguñá
,
C.
Castellano
, and
R.
Pastor-Satorras
, “
Supplementary information: Nature of the epidemic threshold for the susceptible-infected-susceptible dynamics in networks
,”
Phys. Rev. Lett.
111
,
068701
(
2013
).
66.
A. S.
Mata
,
M.
Boguñá
,
C.
Castellano
, and
R.
Pastor-Satorras
, “
Lifespan method as a tool to study criticality in absorbing-state phase transitions
,”
Phys. Rev. E
91
,
052117
(
2015
).
67.
R. S.
Sander
,
G. S.
Costa
, and
S. C.
Ferreira
, “
Sampling methods for the quasistationary regime of epidemic processes on regular and complex networks
,”
Phys. Rev. E
94
,
042308
(
2016
).
68.
R.
Dickman
,
T.
Tomé
, and
M. J.
de Oliveira
, “
Sandpiles with height restrictions
,”
Phys. Rev. E
66
,
016111
(
2002
).
69.
G.
Pruessner
, “
Equivalence of conditional and external field ensembles in absorbing-state phase transitions
,”
Phys. Rev. E
76
,
061103
(
2007
).
70.
N.
Van Kampen
,
Stochastic Processes in Physics and Chemistry
(
Elsevier
,
2007
).
71.
This was shown in Ref. 22 for annealed networks, but this can also be applied for quenched large systems.23 In annealed networks, the vertex degrees are fixed, while the edges are completely rewired between successive dynamics steps, implying that dynamical correlations are absent and the HMF theory becomes an exact prescription in the thermodynamic limit.21 
72.
D.
Chakrabarti
,
Y.
Wang
,
C.
Wang
,
J.
Leskovec
, and
C.
Faloutsos
, “
Epidemic thresholds in real networks
,”
ACM Trans. Inf. Syst. Secur.
10
,
1
(
2008
).
73.
R.
Pastor-Satorras
and
A.
Vespignani
, “
Epidemic dynamics and endemic states in complex networks
,”
Phys. Rev. E
63
,
066117
(
2001
).
74.
G.
Ódor
, “
Localization transition, Lifschitz tails, and rare-region effects in network models
,”
Phys. Rev. E
90
,
032110
(
2014
).
75.
A. J.
Noest
, “
New universality for spatially disordered cellular automata and directed percolation
,”
Phys. Rev. Lett.
57
,
90
93
(
1986
).
76.
R. B.
Griffiths
, “
Nonanalytic behavior above the critical point in a random Ising ferromagnet
,”
Phys. Rev. Lett.
23
,
17
19
(
1969
).
77.
M. A.
Muñoz
,
R.
Juhász
,
C.
Castellano
, and
G.
Ódor
, “
Griffiths phases on complex networks
,”
Phys. Rev. Lett.
105
,
128701
(
2010
).
78.
W.
Cota
,
S. C.
Ferreira
, and
G.
Ódor
, “
Griffiths effects of the susceptible-infected-susceptible epidemic model on random power-law networks
,”
Phys. Rev. E
93
,
032322
(
2016
).
79.
L. M.
Ménard
and
A.
Singh
, “
Percolation by cumulative merging and phase transition for the contact process on random graphs
,”
Ann. Sci. l’Ecole Norm. Sup.
49
,
1189
1238
(
2016
).
80.
X.
Huang
and
R.
Durrett
, “
The contact process on random graphs and Galton Watson trees
,”
Latin Am. J. Probab. Math. Stat.
17
,
159
(
2020
).
81.
G. F.
de Arruda
,
G.
Petri
, and
Y.
Moreno
, “
Social contagion models on hypergraphs
,”
Phys. Rev. Res.
2
,
023032
(
2020
).
82.
F. V.
Surano
,
C.
Bongiorno
,
L.
Zino
,
M.
Porfiri
, and
A.
Rizzo
, “
Backbone reconstruction in temporal networks from epidemic data
,”
Phys. Rev. E
100
,
042306
(
2019
).
83.
E.
Lee
,
S.
Emmons
,
R.
Gibson
,
J.
Moody
, and
P. J.
Mucha
, “
Concurrency and reachability in treelike temporal networks
,”
Phys. Rev. E
100
,
062305
(
2019
).
84.
A.
Koher
,
H. H. K.
Lentz
,
J. P.
Gleeson
, and
P.
Hövel
, “
Contact-based model for epidemic spreading on temporal networks
,”
Phys. Rev. X
9
,
031017
(
2019
).
85.
D.
Soriano-Paños
,
L.
Lotero
,
A.
Arenas
, and
J.
Gómez-Gardeñes
, “
Spreading processes in multiplex metapopulations containing different mobility networks
,”
Phys. Rev. X
8
,
031039
(
2018
).
86.
A.
Matsuki
and
G.
Tanaka
, “
Intervention threshold for epidemic control in susceptible-infected-recovered metapopulation models
,”
Phys. Rev. E
100
,
022302
(
2019
).
87.
P. C. V.
da Silva
,
F.
Velásquez-Rojas
,
C.
Connaughton
,
F.
Vazquez
,
Y.
Moreno
, and
F. A.
Rodrigues
, “
Epidemic spreading with awareness and different timescales in multiplex networks
,”
Phys. Rev. E
100
,
032313
(
2019
).
88.
J.
Chen
,
M.-B.
Hu
, and
M.
Li
, “
Traffic-driven epidemic spreading in multiplex networks
,”
Phys. Rev. E
101
,
012301
(
2020
).
89.
G. F.
de Arruda
,
G.
Petri
,
F. A.
Rodrigues
, and
Y.
Moreno
, “
Impact of the distribution of recovery rates on disease spreading in complex networks
,”
Phys. Rev. Res.
2
,
013046
(
2020
).
90.
R. R.
Wilkinson
and
K. J.
Sharkey
, “
Impact of the infectious period on epidemics
,”
Phys. Rev. E
97
,
052403
(
2018
).
91.
A.
Darbon
,
D.
Colombi
,
E.
Valdano
,
L.
Savini
,
A.
Giovannini
, and
V.
Colizza
, “
Disease persistence on temporal contact networks accounting for heterogeneous infectious periods
,”
R. Soc. Open Sci.
6
,
181404
(
2019
).
92.
S.
Moore
and
T.
Rogers
, “
Predicting the speed of epidemics spreading in networks
,”
Phys. Rev. Lett.
124
,
068301
(
2020
).
93.
C.
Metcalf
,
W.
Edmunds
, and
J.
Lessler
, “
Six challenges in modelling for public health policy
,”
Epidemics
10
,
93
96
(
2015
).
94.
T.
Britton
,
T.
House
,
A. L.
Lloyd
,
D.
Mollison
,
S.
Riley
, and
P.
Trapman
, “
Five challenges for stochastic epidemic models involving global transmission
,”
Epidemics
10
,
54
57
(
2015
).
95.
E.
Brooks-Pollock
,
M.
de Jong
,
M.
Keeling
,
D.
Klinkenberg
, and
J.
Wood
, “
Eight challenges in modelling infectious livestock diseases
,”
Epidemics
10
,
1
5
(
2015
).
96.
T. D.
Hollingsworth
,
J. R.
Pulliam
,
S.
Funk
,
J. E.
Truscott
,
V.
Isham
, and
A. L.
Lloyd
, “
Seven challenges for modelling indirect transmission: Vector-borne diseases, macroparasites and neglected tropical diseases
,”
Epidemics
10
,
16
20
(
2015
).
97.
P.
Klepac
,
A. J.
Kucharski
,
A. J.
Conlan
,
S.
Kissler
,
M.
Tang
,
H.
Fry
, and
J. R.
Gog
, “
Contacts in context: Large-scale setting-specific social mixing matrices from the BBC Pandemic project
,”
medRxiv
(
2020
).
98.
A.
Arenas
,
W.
Cota
,
J.
Gomez-Gardenes
,
S.
Gómez
,
C.
Granell
,
J. T.
Matamalas
,
D.
Soriano-Panos
, and
B.
Steinegger
, “
A mathematical model for the spatiotemporal epidemic spreading of COVID19
,”
medRxiv
(
2020
).
99.
F.
Ganem
,
F. M.
Mendes
,
S. B.
Oliveira
,
V. B. G.
Porto
,
W.
Araujo
,
H.
Nakaya
,
F. A.
Diaz-Quijano
, and
J.
Croda
, “
The impact of early social distancing at COVID-19 outbreak in the largest metropolitan area of Brazil
,”
medRxiv
(
2020
).
You do not currently have access to this content.