Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.9
2.1
Journals
Entropy
Special Issues
Modeling and Control of Epidemic Spreading in Complex Societies
entropy-logo
Submit to Entropy Review for Entropy Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Modeling and Control of Epidemic Spreading in Complex Societies

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: closed (31 August 2024) | Viewed by 9648

Special Issue Editors

Dr. Marcelo Oliveira

E-Mail Website
Guest Editor
Physics and Mathematics Department, Universidade Federal de Sao Joao del-Rei, Sete Lagoas 35702-031, Brazil
Interests: nonequilibrium phase transitions; complex systems; epidemics; complex networks; sociophysics
Dr. Marco Antonio Amaral

E-Mail Website
Guest Editor
Institute of Humanities Arts and Sciences, Universidade Federal do Sul da Bahia, Teixeira de Freitas 41820-500, Brazil
Interests: statistical physics; game theory; complex systems; sociophysics; complex networks

Special Issue Information

Dear Colleagues,

Modeling and predicting epidemic spreading in human societies is a challenge connecting epidemiology and sociology. The complexity arises in many forms: individuals are known to interact in a complex network of connections; the flux and the nature of the information among the individuals affect their attitude towards prophylactic and/or non-farmaceutical measures, etc. In addition, complexity also emerges from the individuals' response to the environment, which can be based on their risk perception, optimistic bias, social condition or even political persuasion.

On the other hand, nowadays, several technological advances, such as contact-tracing apps and GPS, can help to identify and follow epidemics' spatial and temporal evolutions. This can lead to better parameter fitting and to optimize control strategies. 

Therefore, considering the recent advances in the fields of epidemic modeling and sociophysics, this Special Issue aims to collect new methods, models, and data-driven studies that contribute to a better understanding of the epidemic spreading in human societies.

Dr. Marcelo Oliveira
Dr. Marco Antonio Amaral
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • epidemic spreading
  • game theory
  • vaccination
  • complex networks
  • cooperative epidemics
  • data-driven modeling
  • rumour spreading

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

15 pages, 2660 KiB  
Article
Role of Vaccination Strategies to Host-Pathogen Dynamics in Social Interactions
by Marlon Nunes Gonzaga, Marcelo Martins de Oliveira and Allbens Picardi Faria Atman
Entropy 2024, 26(9), 739; https://doi.org/10.3390/e26090739 - 30 Aug 2024
Viewed by 715
Abstract
This study presents extended Immunity Agent-Based Model (IABM) simulations to evaluate vaccination strategies in controlling the spread of infectious diseases. The application of IABM in the analysis of vaccination configurations is innovative, as a vaccinated individual can be infected depending on how their [...] Read more.
This study presents extended Immunity Agent-Based Model (IABM) simulations to evaluate vaccination strategies in controlling the spread of infectious diseases. The application of IABM in the analysis of vaccination configurations is innovative, as a vaccinated individual can be infected depending on how their immune system acts against the invading pathogen, without a pre-established infection rate. Analysis at the microscopic level demonstrates the impact of vaccination on individual immune responses and infection outcomes, providing a more realistic representation of how the humoral response caused by vaccination affects the individual’s immune defense. At the macroscopic level, the effects of different population-wide vaccination strategies are explored, including random vaccination, targeted vaccination of specific demographic groups, and spatially focused vaccination. The results indicate that increased vaccination rates are correlated with decreased infection and mortality rates, highlighting the importance of achieving herd immunity. Furthermore, strategies focused on vulnerable populations or densely populated regions prove to be more effective in reducing disease transmission compared to randomly distributed vaccination. The results presented in this work show that vaccination strategies focused on highly crowded regions are more efficient in controlling epidemics and outbreaks. Results suggest that applying vaccination only in the densest region resulted in the suppression of infection in that region, with less intense viral spread in areas with lower population densities. Strategies focused on specific regions, in addition to being more efficient in reducing the number of infected and dead people, reduce costs related to transportation, storage, and distribution of doses compared to the random vaccination strategy. Considering that, despite scientific efforts to consolidate the use of mass vaccination, the accessibility, affordability, and acceptability of vaccines are problems that persist, investing in the study of strategies that mitigate such issues is crucial in the development and application of government policies that make immunization systems more efficient and robust. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
►▼ Show Figures

Figure 1

20 pages, 3627 KiB  
Article
A Networked Meta-Population Epidemic Model with Population Flow and Its Application to the Prediction of the COVID-19 Pandemic
by Dong Xue, Naichao Liu, Xinyi Chen and Fangzhou Liu
Entropy 2024, 26(8), 654; https://doi.org/10.3390/e26080654 - 30 Jul 2024
Viewed by 1053
Abstract
This article addresses the crucial issues of how asymptomatic individuals and population movements influence the spread of epidemics. Specifically, a discrete-time networked Susceptible-Asymptomatic-Infected-Recovered (SAIR) model that integrates population flow is introduced to investigate the dynamics of epidemic transmission among individuals. In contrast to [...] Read more.
This article addresses the crucial issues of how asymptomatic individuals and population movements influence the spread of epidemics. Specifically, a discrete-time networked Susceptible-Asymptomatic-Infected-Recovered (SAIR) model that integrates population flow is introduced to investigate the dynamics of epidemic transmission among individuals. In contrast to existing data-driven system identification approaches that identify the network structure or system parameters separately, a joint estimation framework is developed in this study. The joint framework incorporates historical measurements and enables the simultaneous estimation of transmission topology and epidemic factors. The use of the joint estimation scheme reduces the estimation error. The stability of equilibria and convergence behaviors of proposed dynamics are then analyzed. Furthermore, the sensitivity of the proposed model to population movements is evaluated in terms of the basic reproduction number. This article also rigorously investigates the effectiveness of non-pharmaceutical interventions via distributively controlling population flow in curbing virus transmission. It is found that the population flow control strategy reduces the number of infections during the epidemic. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
►▼ Show Figures

Figure 1

21 pages, 1835 KiB  
Article
On an Aggregated Estimate for Human Mobility Regularities through Movement Trends and Population Density
by Fabio Vanni and David Lambert
Entropy 2024, 26(5), 398; https://doi.org/10.3390/e26050398 - 30 Apr 2024
Viewed by 1322
Abstract
This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, [...] Read more.
This article introduces an analytical framework that interprets individual measures of entropy-based mobility derived from mobile phone data. We explore and analyze two widely recognized entropy metrics: random entropy and uncorrelated Shannon entropy. These metrics are estimated through collective variables of human mobility, including movement trends and population density. By employing a collisional model, we establish statistical relationships between entropy measures and mobility variables. Furthermore, our research addresses three primary objectives: firstly, validating the model; secondly, exploring correlations between aggregated mobility and entropy measures in comparison to five economic indicators; and finally, demonstrating the utility of entropy measures. Specifically, we provide an effective population density estimate that offers a more realistic understanding of social interactions. This estimation takes into account both movement regularities and intensity, utilizing real-time data analysis conducted during the peak period of the COVID-19 pandemic. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
►▼ Show Figures

Figure 1

16 pages, 2536 KiB  
Article
Dynamic Analysis of an Epidemic Model Considering Personal Alert on a Complex Network
by Fengling Jia, Ziyu Gu and Lixin Yang
Entropy 2023, 25(10), 1437; https://doi.org/10.3390/e25101437 - 11 Oct 2023
Cited by 1 | Viewed by 1223
Abstract
This paper proposes a SIQRS epidemic model with birth and death on a complex network, considering individual alertness. In particular, we investigate the influence of the individual behavior in the transmission of epidemics and derive the basic reproduction number depending on birth rate, [...] Read more.
This paper proposes a SIQRS epidemic model with birth and death on a complex network, considering individual alertness. In particular, we investigate the influence of the individual behavior in the transmission of epidemics and derive the basic reproduction number depending on birth rate, death rate, alertness rate, quarantine rate. In addition, the stabilities of the disease-free equilibrium point and endemic equilibrium point are analyzed via stability theory. It is found that the emergence of individual behavior can influence the process of transmission of epidemics. Our results show that individual alertness rate is negatively correlated with basic reproduction number, while the impact of individual alertness on infectious factor is positively correlated with basic reproduction number. When the basic reproduction number is less than one, the system is stable and the disease is eventually eradicated. Nevertheless, there is an endemic equilibrium point under the condition that the basic reproduction number is more than one. Finally, numerical simulations are carried out to illustrate theoretical results. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
►▼ Show Figures

Figure 1

20 pages, 349 KiB  
Article
A Local Analysis of a Mathematical Pattern for Interactions between the Human Immune System and a Pathogenic Agent
by Florian Munteanu
Entropy 2023, 25(10), 1392; https://doi.org/10.3390/e25101392 - 28 Sep 2023
Cited by 1 | Viewed by 1514
Abstract
In the present study, we introduce a four-dimensional deterministic mathematical pattern in order to study the interactions between the human immune system and a virus. The model is based on a system with four first-order ordinary differential equations, and the main aim of [...] Read more.
In the present study, we introduce a four-dimensional deterministic mathematical pattern in order to study the interactions between the human immune system and a virus. The model is based on a system with four first-order ordinary differential equations, and the main aim of the paper is to perform a mathematical analysis of the local behavior of the associated dynamical system using the tools of the qualitative theory of dynamical systems. Moreover, two types of patterns with controls were introduced; consequently, some very interesting theoretical conclusions with medical relevance were obtained. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
17 pages, 1459 KiB  
Article
Stochastic Stabilization of Dual-Layer Rumor Propagation Model with Multiple Channels and Rumor-Detection Mechanism
by Xiaojing Zhong, Chaolong Luo, Xiaowu Dong, Dingyong Bai, Guiyun Liu, Ying Xie and Yuqing Peng
Entropy 2023, 25(8), 1192; https://doi.org/10.3390/e25081192 - 10 Aug 2023
Cited by 1 | Viewed by 1536
Abstract
With the development of information technology, individuals are able to receive rumor information through various channels and subsequently act based on their own perceptions. The significance of the disparity between media and individual cognition in the propagation of rumors cannot be underestimated. In [...] Read more.
With the development of information technology, individuals are able to receive rumor information through various channels and subsequently act based on their own perceptions. The significance of the disparity between media and individual cognition in the propagation of rumors cannot be underestimated. In this paper, we establish a dual-layer rumor propagation model considering the differences in individual cognition to study the propagation behavior of rumors in multiple channels. Firstly, we obtain the threshold for rumor disappearance or persistence by solving the equilibrium points and their stability. The threshold is related to the number of media outlets and the number of rumor debunkers. Moreover, we have innovatively designed a class of non-periodic intermittent noise stabilization methods to suppress rumor propagation. This method can effectively control rumor propagation based on a flexible control scheme, and we provide specific expressions for the control intensity. Finally, we have validated the accuracy of the theoretical proofs through experimental simulations. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
►▼ Show Figures

Figure 1

13 pages, 343 KiB  
Article
A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
by Chuanbo Zhou, Jiaohong Fang and Mingzhi Mao
Entropy 2023, 25(7), 1028; https://doi.org/10.3390/e25071028 - 6 Jul 2023
Cited by 1 | Viewed by 1106
Abstract
Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates [...] Read more.
Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates of multiple groups were equal during the epidemic period. In light of large-scale simulation studies, the proposed test method can accurately identify the differences between different groups and display satisfactory performance. We apply the proposed method to the real dataset of the COVID-19 epidemic in mainland China (excluding Hubei), Hubei Province (excluding Wuhan), and Wuhan from 31 January 2020 to 30 March 2020. By comparing the differences in the disease severity for differential cities, we show that the severity of the early disease of COVID-19 may be related to the effectiveness of interventions and the improvement in medical resources. Full article
(This article belongs to the Special Issue Modeling and Control of Epidemic Spreading in Complex Societies)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop