Synergistic contagion in a networked system occurs in various forms in nature and human society. While the influence of network’s structural heterogeneity on synergistic contagion has been well studied, the impact of individual-based heterogeneity on synergistic contagion remains unclear. In this work, we introduce individual-based heterogeneity with a power-law form into the synergistic susceptible–infected–susceptible model by assuming the synergistic strength as a function of individuals’ degree and investigate this synergistic contagion process on complex networks. By employing the heterogeneous mean-field (HMF) approximation, we analytically show that the heterogeneous synergy significantly changes the critical threshold of synergistic strength σ c that is required for the occurrence of discontinuous phase transitions of contagion processes. Comparing to the synergy without individual-based heterogeneity, the value of σ c decreases with degree-enhanced synergy and increases with degree-suppressed synergy, which agrees well with Monte Carlo prediction. Next, we compare our heterogeneous synergistic contagion model with the simplicial contagion model [Iacopini et al., Nat. Commun. 10, 2485 (2019)], in which high-order interactions are introduced to describe complex contagion. Similarity of these two models are shown both analytically and numerically, confirming the ability of our model to statistically describe the simplest high-order interaction within HMF approximation.

1.
M.
Posfai
and
A.
Barabasi
,
Network Science
(
Cambridge University Press
,
2016
).
2.
M.
Newman
,
Networks
(
Oxford University Press
,
2018
).
3.
R.
Pastor-Satorras
,
C.
Castellano
,
P.
Van Mieghem
, and
A.
Vespignani
, “
Epidemic processes in complex networks
,”
Rev. Mod. Phys.
87
,
925
979
(
2015
).
4.
W.
Wang
,
M.
Tang
,
H. F.
Zhang
, and
Y. C.
Lai
, “
Dynamics of social contagions with memory of nonredundant information
,”
Phys. Rev. E
92
,
012820
(
2015
).
5.
C.
Stegehuis
,
R.
van der Hofstad
, and
J. S. H.
van Leeuwaarden
, “
Epidemic spreading on complex networks with community structures
,”
Sci. Rep.
6
,
29748
(
2016
).
6.
M.
Nadini
,
K.
Sun
,
E.
Ubaldi
,
M.
Starnini
,
A.
Rizzo
, and
N.
Perra
, “
Epidemic spreading in modular time-varying networks
,”
Sci. Rep.
8
,
2352
(
2018
).
7.
S.
Ma
,
L.
Feng
, and
C.
Lai
, “
Mechanistic modeling of viral spreading on empirical social network and popularity prediction
,”
Sci. Rep.
8
,
13126
(
2018
).
8.
X.
Wang
,
Y.
Lan
, and
J.
Xiao
, “
Anomalous structure and dynamics in news diffusion among heterogeneous individuals
,”
Nat. Hum. Behav.
3
,
709
718
(
2019
).
9.
J. T.
Davis
,
N.
Perra
,
Q.
Zhang
,
Y.
Moreno
, and
A.
Vespignani
, “
Phase transitions in information spreading on structured populations
,”
Nat. Phys.
16
,
590
596
(
2020
).
10.
J.
Grilli
,
G.
Barabás
,
M. J.
Michalska-Smith
, and
S.
Allesina
, “
Higher-order interactions stabilize dynamics in competitive network models
,”
Nature
548
,
210
213
(
2017
).
11.
J. R. C.
Piqueira
,
B. F.
Navarro
, and
L. H. A.
Monteiro
, “
Epidemiological models applied to viruses in computer networks
,”
J. Comput. Sci.
1
,
31
34
(
2005
).
12.
N.
Friedman
,
S.
Ito
,
B. A. W.
Brinkman
,
M.
Shimono
,
R. E. L.
DeVille
,
K. A.
Dahmen
,
J. M.
Beggs
, and
T. C.
Butler
, “
Universal critical dynamics in high resolution neuronal avalanche data
,”
Phys. Rev. Lett.
108
,
208102
(
2012
).
13.
P.
Moretti
and
M. A.
Muñoz
, “
Griffiths phases and the stretching of criticality in brain networks
,”
Nat. Commun.
4
,
2521
(
2013
).
14.
W. O.
Kermack
and
A. G.
McKendrick
, “
Contributions to the mathematical theory of epidemics—i
,”
Bull. Math. Biol.
53
,
33
55
(
1991
).
15.
X.
Zhang
,
Z.
Ruan
,
M.
Zheng
,
J.
Zhou
,
S.
Boccaletti
, and
B.
Barzel
, “
Epidemic spreading under mutually independent intra- and inter-host pathogen evolution
,”
Nat. Commun.
13
,
6218
(
2022
).
16.
G.
Poux-Médard
,
R.
Pastor-Satorras
, and
C.
Castellano
, “
Influential spreaders for recurrent epidemics on networks
,”
Phys. Rev. Res.
2
,
023332
(
2020
).
17.
G.
St-Onge
,
V.
Thibeault
,
A.
Allard
,
L. J.
Dubé
, and
L.
Hébert-Dufresne
, “
Social confinement and mesoscopic localization of epidemics on networks
,”
Phys. Rev. Lett.
126
,
098301
(
2021
).
18.
M.
Te Vrugt
,
J.
Bickmann
, and
R.
Wittkowski
, “
Effects of social distancing and isolation on epidemic spreading modeled via dynamical density functional theory
,”
Nat. Commun.
11
,
5576
(
2020
).
19.
X.
Wei
,
J.
Zhao
,
S.
Liu
, and
Y.
Wang
, “
Identifying influential spreaders in complex networks for disease spread and control
,”
Sci. Rep.
12
,
5550
(
2022
).
20.
D.
Centola
, “
The spread of behavior in an online social network experiment
,”
Science
329
,
1194
1197
(
2010
).
21.
J.
Ugander
,
L.
Backstrom
,
C.
Marlow
, and
J.
Kleinberg
, “
Structural diversity in social contagion
,”
Proc. Natl. Acad. Sci. U.S.A.
109
,
5962
5966
(
2012
).
22.
L.
Weng
,
A.
Flammini
,
A.
Vespignani
, and
F.
Menczer
, “
Competition among memes in a world with limited attention
,”
Sci. Rep.
2
,
335
(
2012
).
23.
B.
Mønsted
,
P.
Sapieżyński
,
E.
Ferrara
, and
S.
Lehmann
, “
Evidence of complex contagion of information in social media: An experiment using Twitter bots
,”
PLoS One
12
,
e0184148
(
2017
).
24.
D.
Guilbeault
,
J.
Becker
, and
D.
Centola
, “Complex contagions: A decade in review,” in Complex Spreading Phenomena in Social Systems: Influence and Contagion in Real-World Social Networks (Springer, 2018), pp. 3–25.
25.
L.
Hébert-Dufresne
,
S. V.
Scarpino
, and
J.
Young
, “
Macroscopic patterns of interacting contagions are indistinguishable from social reinforcement
,”
Nat. Phys.
16
,
426
431
(
2020
).
26.
J. J.
Ludlam
,
G. J.
Gibson
,
W.
Otten
, and
C. A.
Gilligan
, “
Applications of percolation theory to fungal spread with synergy
,”
J. R. Soc. Interface
9
,
949
956
(
2012
).
27.
N. O.
Hodas
and
K.
Lerman
, “
The simple rules of social contagion
,”
Sci. Rep.
4
,
4343
(
2014
).
28.
Q. H.
Liu
,
W.
Wang
,
M.
Tang
,
T.
Zhou
, and
Y. C.
Lai
, “
Explosive spreading on complex networks: The role of synergy
,”
Phys. Rev. E
95
,
042320
(
2017
).
29.
L. A.
Liotta
and
E. C.
Kohn
, “
The microenvironment of the tumour–host interface
,”
Nature
411
,
375
379
(
2001
).
30.
F. J.
Pérez-Reche
,
J. J.
Ludlam
,
S. N.
Taraskin
, and
C. A.
Gilligan
, “
Synergy in spreading processes: From exploitative to explorative foraging strategies
,”
Phys. Rev. Lett.
106
,
218701
(
2011
).
31.
S. N.
Taraskin
and
F. J.
Pérez-Reche
, “
Effects of variable-state neighborhoods for spreading synergistic processes on lattices
,”
Phys. Rev. E
88
,
062815
(
2013
).
32.
J.
Gómez-Gardeñes
,
L.
Lotero
,
S. N.
Taraskin
, and
F. J.
Pérez-Reche
, “
Explosive contagion in networks
,”
Sci. Rep.
6
,
19767
(
2016
).
33.
S. N.
Taraskin
and
F. J.
Pérez-Reche
, “
Bifurcations in synergistic epidemics on random regular graphs
,”
J. Phys. A: Math. Theor.
52
,
195101
(
2019
).
34.
S.
Mizutaka
,
K.
Mori
, and
T.
Hasegawa
, “
Synergistic epidemic spreading in correlated networks
,”
Phys. Rev. E
106
,
034305
(
2022
).
35.
C.
Lin
,
Z.
Yan
,
J.
Gao
, and
J.
Xiao
, “
From heterogeneous network to homogeneous network: The influence of structure on synergistic epidemic spreading
,”
J. Phys. A: Math. Theor.
56
,
215001
(
2023
).
36.
D.
Centola
, “
An experimental study of homophily in the adoption of health behavior
,”
Science
334
,
1269
1272
(
2011
).
37.
P.
Erdős
,
A.
Rényi
et al., “
On the evolution of random graphs
,”
Publ. Math. Inst. Hung. Acad. Sci.
5
,
17
60
(
1960
); available at http://refhub.elsevier.com/S0370-1573(20)30248-9/sb253.
38.
A.
Barabási
and
R.
Albert
, “
Emergence of scaling in random networks
,”
Science
286
,
509
512
(
1999
).
39.
I.
Iacopini
,
G.
Petri
,
A.
Barrat
, and
V.
Latora
, “
Simplicial models of social contagion
,”
Nat. Commun.
10
,
2485
(
2019
).
40.
R.
Pastor-Satorras
and
A.
Vespignani
, “
Epidemic spreading in scale-free networks
,”
Phys. Rev. Lett.
86
,
3200
3203
(
2001
).
41.
B.
Jhun
,
M.
Jo
, and
B.
Kahng
, “
Simplicial SIS model in scale-free uniform hypergraph
,”
J. Stat. Mech.
2019
(
12
),
123207
.
42.
X.
Peng
,
C.
Li
,
H.
Qi
,
G.
Sun
,
Z.
Wang
, and
Y.
Wu
, “
Competition between awareness and epidemic spreading in homogeneous networks with demography
,”
Appl. Math. Comput.
420
,
126875
(
2022
).
43.
S. H.
Strogatz
,
Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering
(
CRC Press
,
2018
).
44.
G. J.
Baxter
,
S. N.
Dorogovtsev
,
A. V.
Goltsev
, and
J. F. F.
Mendes
, “
Bootstrap percolation on complex networks
,”
Phys. Rev. E
82
,
011103
(
2010
).
45.
P. G.
Fennell
,
S.
Melnik
, and
J. P.
Gleeson
, “
Limitations of discrete-time approaches to continuous-time contagion dynamics
,”
Phys. Rev. E
94
,
052125
(
2016
).
46.
J. T.
Matamalas
,
S.
Gómez
, and
A.
Arenas
, “
Abrupt phase transition of epidemic spreading in simplicial complexes
,”
Phys. Rev. Res.
2
,
012049
(
2020
).
47.
N. W.
Landry
and
J. G.
Restrepo
, “
The effect of heterogeneity on hypergraph contagion models
,”
Chaos
30
,
103117
(
2020
).
48.
W.
Li
,
Y.
Nie
,
W.
Li
,
X.
Chen
,
S.
Su
, and
W.
Wang
, “
Two competing simplicial irreversible epidemics on simplicial complex
,”
Chaos
32
,
093135
(
2022
).
49.
Y.
Zhang
,
M.
Lucas
, and
F.
Battiston
, “
Higher-order interactions shape collective dynamics differently in hypergraphs and simplicial complexes
,”
Nat. Commun.
14
,
1605
(
2023
).
50.
S.
Adhikari
,
J. G.
Restrepo
, and
P. S.
Skardal
, “
Synchronization of phase oscillators on complex hypergraphs
,”
Chaos
33
,
033116
(
2023
).
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