Zobrazeno 1 - 10
of 1 224
pro vyhledávání: '"Epidemic spreading"'
Autor:
Zong-Kai Liu, Dong-Sheng Ding, Yi-Chen Yu, Hannes Busche, Bao-Sen Shi, Guang-Can Guo, C. Stuart Adams, Franco Nori
Publikováno v:
Quantum Frontiers, Vol 3, Iss 1, Pp 1-16 (2024)
Abstract It is increasingly important to understand the spatial dynamics of epidemics. While there are numerous mathematical models of epidemics, there is a scarcity of physical systems with sufficiently well-controlled parameters to allow quantitati
Externí odkaz:
https://doaj.org/article/8bc5556658a94ef3a2a6d21900712ef5
Autor:
Feng Li
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
In the real world, individuals may become infected with an epidemic after multiple exposures to the corresponding virus. This occurs because each individual possesses certain physical defenses and immune capabilities at the time of exposure to the vi
Externí odkaz:
https://doaj.org/article/6cf639dde5984ade969d4ce26e924967
Networked SIRS Epidemic Model With Opinion Evolutions: Stubborn Community and Maximum Infection Time
Publikováno v:
IEEE Access, Vol 12, Pp 43789-43795 (2024)
This paper is concerned with the co-evolution problem of epidemic and opinion over social networks. A networked SIRS epidemic model with opinion dynamics is proposed to analyze the impact of the community’s opinion on the epidemic spreading. By int
Externí odkaz:
https://doaj.org/article/e16e16f0171549cda1e0ae4ab43cb9c2
Publikováno v:
Entropy, Vol 26, Iss 9, p 760 (2024)
The diffusion phenomenon that exhibits intrinsic similarities is pervasive in cryptography and natural systems, evident in liquid diffusion, epidemic spread, animal migration, and encryption techniques. In cryptography, bytes are systematically diffu
Externí odkaz:
https://doaj.org/article/8aaa769447fb4109b4cd3a77c8c7bb1b
Autor:
Into Almiala, Vesa Kuikka
Publikováno v:
AIMS Biophysics, Vol 10, Iss 2, Pp 173-183 (2023)
The modelling of epidemic spreading is essential in understanding the mechanisms of outbreaks and pandemics. Many models for different kinds of spreading have been proposed throughout the history of modelling, each suited for a specific scenario and
Externí odkaz:
https://doaj.org/article/7fd3c27b34a847a5aab749834a910c03
Autor:
Téo Granger, Thomas M. Michelitsch, Michael Bestehorn, Alejandro P. Riascos, Bernard A. Collet
Publikováno v:
Entropy, Vol 26, Iss 5, p 362 (2024)
We study epidemic spreading in complex networks by a multiple random walker approach. Each walker performs an independent simple Markovian random walk on a complex undirected (ergodic) random graph where we focus on the Barabási–Albert (BA), Erdö
Externí odkaz:
https://doaj.org/article/562a0cf5ba3a419eacd6d9c73cfdddc1
Publikováno v:
Frontiers in Physics, Vol 11 (2023)
Pre-emptive vaccination has been proven to be the most effective measure to control influenza outbreaks. However, when vaccination behavior is voluntary, individuals may face the vaccination dilemma owing to the two sides of vaccines. In view of this
Externí odkaz:
https://doaj.org/article/a1399fcdd6964fdfa5537c752e2c67bc
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 2, Pp 3342-3354 (2023)
In this paper, an SAITS epidemic model based on a single layer static network is proposed and investigated. This model considers a combinational suppression control strategy to suppress the spread of epidemics, which includes transferring more indivi
Externí odkaz:
https://doaj.org/article/1c47213f4af94e85803db39fa9fa0b6e
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 10, Pp 9207-9215 (2022)
Epidemic-related information and resources have proven to have a significant impact on the spread of the epidemic during the Corona Virus Disease 2019 (COVID-19) pandemic. The various orientation role of information has different effects on the epide
Externí odkaz:
https://doaj.org/article/652811c4776f4c3aa943c001a5919d5e
Publikováno v:
Mathematics, Vol 12, Iss 6, p 792 (2024)
This review underscores the critical significance of incorporating networks science in epidemiology. Classic mathematical compartmental models (CMs) employed to describe epidemic spreading may fail to capture the intricacies of real disease dynamics.
Externí odkaz:
https://doaj.org/article/c6825ac3de94437888ab84394cea6d46