| Abstract |
Many social and biological networks periodically change over time with daily, weekly, and other cycles. Thus motivated, we formulate and analyze susceptible-infectious-susceptible (SIS) epidemic models over temporal networks with periodic schedules. More specifically, we assume that the temporal network consists of a cycle of alternately used static networks, each with a given duration. We observe a phenomenon in which two static networks are individually above the epidemic threshold but the alternating network composed of them renders the dynamics below the epidemic threshold, which we refer to as a Parrondo paradox for epidemics. We find that network structure plays an important role in shaping this phenomenon, and we study its dependence on the connectivity between and number of subpopulations in the network. We associate such paradoxical behavior with anti-phase oscillatory dynamics of the number of infectious individuals in different subpopulations. |
| Authors |
Maisha Islam Sejunti  , Dane Taylor  , Naoki Masuda
|
| Journal Info |
Elsevier BV | Mathematical Biosciences , vol: 378
, pages: 109336 - 109336
|
| Publication Date |
11/6/2024 |
| ISSN |
0025-5564 |
Type |
article |
| Open Access |
hybrid
|
| DOI |
https://doi.org/10.1016/j.mbs.2024.109336 |
| Keywords |
Dynamics (Score: 0.6557546)
|
