Article
Biology
Brandon Lieberthal, Aiman Soliman, Shaowen Wang, Sandra De Urioste-Stone, Allison M. Gardner
Summary: Predicting and preparing for disease epidemics requires understanding the impact of environmental and socioeconomic factors on transmission rates. This article discusses the simulation of epidemic outbreaks in human metapopulation networks and highlights the importance of community structure in determining disease spread. The study shows that network modularity, community structure, and human diffusion rate are all interconnected and can be influenced by strategies such as movement restrictions and vaccination. The effectiveness of these strategies depends on the network structure and disease properties. Guidance on balancing accuracy and data collection costs is also provided.
MATHEMATICAL BIOSCIENCES
(2023)
Article
Engineering, Mechanical
Bing Wang, Min Gou, Yuexing Han
Summary: The study examines the interaction between epidemic and information transmission over separate migration routes. Information transmission has a limited impact on suppressing the epidemic, and further increase in transmission rate beyond a critical value does not affect the epidemic. Individual migration routes and frequencies play a crucial role in information transmission and epidemic spread, while the initial population distribution is also a fundamental factor influencing epidemic dynamics.
NONLINEAR DYNAMICS
(2021)
Article
Automation & Control Systems
Ashish R. Hota, Tanya Sneh, Kavish Gupta
Summary: This article investigates the evolution of epidemics over dynamical networks when nodes choose to interact with others in a selfish and decentralized manner. The authors propose activity-driven networks and a game-theoretic model to analyze the epidemic evolution. The numerical results provide compelling insights into the impact of game-theoretic activation on epidemic dynamics.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2022)
Article
Mathematics, Interdisciplinary Applications
Kebo Zhang, Xiao Hong, Yuexing Han, Bing Wang
Summary: Suppressing an epidemic in regions with limited medical resources is challenging but crucial. This study constructs a metapopulation network model to simulate the spatial evolution of the epidemic and adopts the Binary Particle Swarm Optimization (BPSO) algorithm to find the optimal resource deployment. Experimental results show that BPSO can effectively allocate resources and outperforms random allocation. In cases of low budget, vaccine resources are prioritized while curative resources are allocated sparingly. As the budget increases, more areas are filled with vaccine resources and curative resources are gradually allocated. Additionally, under a limited budget, resource allocation is scattered and the network's community structure has minimal impact on allocation, indicating the need to avoid over-concentration of resources.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Automation & Control Systems
Lintao Ye, Philip E. Pare, Shreyas Sundaram
Summary: The study focuses on the estimation of parameters governing the spread of epidemics in networks. The problem is formulated as an optimization problem, and approximation algorithms are proposed to provide solutions.
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2022)
Article
Mathematics, Applied
Xiao Hong, Yuexing Han, Bing Wang
Summary: In situations where vaccines are insufficient and the virus mutates rapidly, detection and contact tracing have been proven to be effective interventions. This study quantifies the effectiveness of these interventions in suppressing the epidemic in time-varying networks and explores possible contact tracing measures based on individuals' properties. The findings suggest that detection can effectively suppress the epidemic spread, while the effectiveness of contact tracing depends on the characteristics of the epidemic.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Yongqiang Zhang, Shuang Li, Xiaotian Li, Jinlong Ma
Summary: Traffic flow has a significant impact on the transmission and distribution of pathogens, especially in the context of global economic integration. This study adds new parameters to the traffic-driven Susceptible-Infected-Recovered (SIR) epidemic spread model to accurately represent the time characteristics of traffic-driven epidemic spread. By using a linear regression method on epidemic data in Hebei Province, the infection rate parameter is estimated, and an improved traffic-driven SIR epidemic spread dynamics model is established. The study investigates the effects of different link-closure rules, traffic flow, and network average degree on epidemic spread, finding that closing links between small-degree nodes is more effective in inhibiting the spread and reducing traffic flow and increasing network average degree can slow down the outbreak. The findings provide a practical scientific basis for traffic control measures during epidemic outbreaks.
INTERNATIONAL JOURNAL OF MODERN PHYSICS C
(2023)
Article
Public, Environmental & Occupational Health
Junqing Tang, Huali Lin, Xudong Fan, Xiong Yu, Qiuchen Lu
Summary: This paper proposes a simulation-based approach to investigate the resilience of urban road networks in response to different modes of epidemic spreading during severe public health crises, such as the global COVID-19 pandemic. The study shows that road networks exhibit comparatively worse resilient behavior under trajectory-based spreading mode, with recovery processes impacted by road density, centrality order, and regional geographical characteristics. The research emphasizes the importance of dynamic response and strategic recovery planning in post-COVID era for better managing urban road network resilience.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Virology
Xueke Zhao, Qingming Zhou, Anjing Wang, Fenping Zhu, Zeyang Meng, Chao Zuo
Summary: This study introduces a new SEIR/V-UA model to investigate the interaction between epidemic spreading and information diffusion. The model is validated using Monte Carlo method and numerical simulations on a two-layer scale-free network, showing that epidemic spread can be influenced by the effective transmission rate of awareness.
JOURNAL OF MEDICAL VIROLOGY
(2021)
Article
Mathematics, Applied
Giulia Bertaglia, Chuan Lu, Lorenzo Pareschi, Xueyu Zhu
Summary: When investigating epidemic dynamics through differential models, the parameters and forecast scenarios require delicate calibration due to the scarcity and uncertainty of official observed data. Physics-Informed Neural Networks (PINNs) can effectively address the inverse and forward problem of data-driven learning by embedding the knowledge of the differential model. However, in cases with multiple scales, a direct application of PINNs leads to poor results due to the multiscale nature of the differential model in the loss function. To address this, a new class of Asymptotic-Preservation Neural Networks (APNNs) is proposed for multiscale transport models of epidemic spread, which works uniformly at different scales thanks to the appropriate AP formulation of the loss function. Numerical tests confirm the validity of the approach for different epidemic scenarios, highlighting the importance of the AP property in neural networks for dealing with multiscale problems.
MATHEMATICAL MODELS & METHODS IN APPLIED SCIENCES
(2022)
Article
Mathematics, Interdisciplinary Applications
Xiao Hong, Yuexing Han, Bing Wang
Summary: As the government lifts restrictive interventions, self-initiated behavioral responses become crucial for coping with future epidemic waves. Two representative behavioral responses, self-protection and self-isolation, play significant roles. However, pandemic fatigue may affect the willingness of infected individuals to comply with self-isolation. Therefore, improving the willingness of susceptible individuals for self-protection and reducing the fatigue of infected individuals for self-isolation are important means to effectively inhibit the spread of emergent epidemics.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Computer Science, Artificial Intelligence
Bo-Lun Chen, Ben Yuan, Win-Xin Jiang, Yong-Tao Yu, Min Ji
Summary: This paper is based on the SEIR model of the new coronavirus pneumonia, considering the impact of cold chain input and re-positive on the spread of the virus in the COVID-19. The experimental results show that taking into account the cold chain input and re-positive can effectively simulate the spread of the epidemic. The research results have important research value and practical significance for the prevention and control of the COVID-19 and the prediction of important time nodes.
Article
Physics, Fluids & Plasmas
Evgeniy Khain
Summary: In the case of bistable dynamics, this study investigates the spatial spread of an epidemic and finds that the transmission rate depends on the fraction of infected individuals, with a linearly stable state of no epidemic. Numerical and theoretical analysis in a four-dimensional phase plane shows a good agreement between the front profiles and the speed of invasion. A novel phenomenon of front stoppage is discovered where the front solution ceases to exist, leading to a decay of the propagating pulse of infection despite the initial outbreak.
Article
Chemistry, Multidisciplinary
Ronald Manriquez, Camilo Guerrero-Nancuante, Carla Taramasco
Summary: Researchers in complex networks study problems like fake news, computer viruses, and infectious diseases, with immunization being a key solution. This paper evaluates the effectiveness of DIL-W-alpha ranking in immunization strategies against infectious diseases on edge-weighted graphs, showing benefits in real and scale-free networks.
APPLIED SCIENCES-BASEL
(2021)
Article
Multidisciplinary Sciences
Fatimah Abdul Razak, Zamira Hasanah Zamzuri
Summary: Malaysia is a multi-ethnic and diverse country with policies and social distancing measures based on daily infection data and R0. Models used to predict COVID-19 spread often assume homogeneity and symmetrical mixing, failing to capture super-spreading events caused by heterogeneity.
Article
Biology
Ramses Djidjou-Demasse, Samuel Alizon, Mircea T. Sofonea
Summary: The evolution and emergence of antibiotic resistance is a major public health concern. Understanding the within-host microbial dynamics, including mutational processes, horizontal gene transfer, and resource consumption, is key to solving this problem. By analyzing a generic model describing interactions dynamics of four bacterial strains with different resistance profiles, researchers have been able to define conditions for the existence of non-trivial stationary states and identify factors influencing the strains' thresholds for survival and coexistence. The model's qualitative dynamics range from strain extinction to coexistence of all strains at equilibrium, depending on the strains' interaction and the presence of drug action.
JOURNAL OF MATHEMATICAL BIOLOGY
(2021)
Editorial Material
Multidisciplinary Sciences
Samuel Alizon
Article
Infectious Diseases
Samuel Alizon, Christian Selinger, Mircea T. Sofonea, Stephanie Haim-Boukobza, Jean-Marc Giannoli, Laetitia Ninove, Sylvie Pillet, Vincent Thibault, Alexis de Rougemont, Camille Tumiotto, Morgane Solis, Robin Stephan, Celine Bressollette-Bodin, Maud Salmona, Anne-Sophie L'honneur, Sylvie Behillil, Caroline Lefeuvre, Julia Dina, Sebastien Hantz, Cedric Hartard, David Veyer, Heloise M. Delagreverie, Slim Fourati, Benoit Visseaux, Cecile Henquell, Bruno Lina, Vincent Foulongne, Sonia Burrel
Summary: This study explores the use of Cq values from SARS-CoV-2 screening tests to better understand the spread of an epidemic and the biology of the infection. The results show significant associations between Cq values and patient age, number of days after symptom onset, and the state of the epidemic. The study suggests that Cq values can improve short-term predictions for epidemic surveillance.
Article
Infectious Diseases
Christian Selinger, Marc Choisy, Samuel Alizon
Summary: Researchers developed predictive models of hospital incidence between July 2020 and April 2021 by incorporating human contact network analytics, which significantly improved predictions at both the national and subnational levels by more than 50%. This innovative use of network analytics from colocalization data opens new possibilities for epidemic forecasting and public health.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2021)
Article
Infectious Diseases
Benedicte Roquebert, Stephanie Haim-Boukobza, Sabine Trombert-Paolantoni, Emmanuel Lecorche, Laura Verdurme, Vincent Foulongne, Sonia Burrel, Samuel Alizon, Mircea T. Sofonea
Summary: The analysis of 88,375 cycle amplification (Ct) values revealed that the Alpha variant of SARS-CoV-2 had a transmission advantage over wild type strains, causing a rapid increase in infections. Additionally, tests positive for Alpha and Beta/Gamma variants showed significantly lower Ct values, indicating higher viral loads.
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2021)
Editorial Material
Ecology
Samuel Alizon, Paul E. Turner
JOURNAL OF EVOLUTIONARY BIOLOGY
(2021)
Article
Virology
Baptiste Elie, Benedicte Roquebert, Mircea T. Sofonea, Sabine Trombert-Paolantoni, Vincent Foulongne, Jeremie Guedj, Stpehanie Haim-Boukobza, Samuel Alizon
Summary: This study analyzed a longitudinal cohort in France and found that infections caused by the Alpha variant have a higher number of viral genome copies and a slower decay rate, leading to significantly higher transmission potentials, especially in older populations. There was no significant difference in peak viral copy number between infections caused by the Alpha and Delta variants.
JOURNAL OF MEDICAL VIROLOGY
(2022)
Article
Biology
Baptiste Elie, Christian Selinger, Samuel Alizon
Summary: There is heterogeneity in infectious disease transmission patterns between individuals, which can affect epidemiological dynamics. Studies have found that heterogeneity in the number of secondary cases decreases the probability of outbreak emergence, and more realistic infection duration distributions lead to faster outbreaks and higher epidemic peaks. The impact of heterogeneity depends on the underlying evolutionary model when parasites require adaptive mutations for large epidemics. These findings emphasize the importance of accounting for realistic distributions of transmission rates in epidemiological dynamics.
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2022)
Editorial Material
Anesthesiology
Pascal Crepey, Harold Noel, Samuel Alizon
ANAESTHESIA CRITICAL CARE & PAIN MEDICINE
(2022)
Article
Biochemistry & Molecular Biology
Nicolas Tessandier, Ilkay Basak Uysal, Baptiste Elie, Christian Selinger, Claire Bernat, Vanina Boue, Sophie Grasset, Soraya Groc, Massilva Rahmoun, Bastien Reyne, Noemi Bender, Marine Bonneau, Christelle Graf, Vincent Tribout, Vincent Foulongne, Jacques Ravel, Tim Waterboer, Christophe Hirtz, Ignacio G. Bravo, Jacques Reynes, Michel Segondy, Carmen Lia Murall, Nathalie Boulle, Tsukushi Kamiya, Samuel Alizon
Summary: The study examines the association between the use of different types of menstrual products and microbial, immunological, demographic, and behavioral indicators. The results suggest a potential link between the use of menstrual cups and fungal genital infection, highlighting the possible influence of menstrual products on menstrual health.
Article
Ecology
Gonche Danesh, Emma Saulnier, Olivier Gascuel, Marc Choisy, Samuel Alizon
Summary: Stochastic population dynamics simulations play a crucial role in ecological and epidemiological studies as they can generate time series and genealogies that capture the relatedness between individuals. However, current software packages for simulating phylogenetic trees often have simplified population dynamics models and are not suitable for simulating a large number of trees. To address these limitations, this study introduces TiPS, an R package that can generate trajectories and phylogenetic trees associated with a compartmental model. TiPS uses different simulation algorithms and a backwards-in-time approach to simulate trajectories and trees, respectively. It combines the flexibility of R for model definition and the speed of C++ for simulations execution. Benchmarking analyses show that TiPS is faster than existing packages and it is particularly useful for population genetics and phylodynamics studies that require a large number of phylogenies for population dynamics analysis.
METHODS IN ECOLOGY AND EVOLUTION
(2023)
Editorial Material
Biochemistry & Molecular Biology
Samuel Alizon
Summary: According to a new study in PLOS Biology, the virulence of a zoonotic virus in humans depends on its reservoir host. Physiology could be the key to anticipating viral threats lethality.
Article
Infectious Diseases
Ilkay Basak Uysal, Vanina Boue, Carmen Lia Murall, Christelle Graf, Christian Selinger, Christophe Hirtz, Claire Bernat, Jacques Ravel, Jacques Reynes, Marine Bonneau, Massilva Rahmoun, Michel Segondy, Nathalie Boulle, Sophie Grasset, Soraya Groc, Tim Waterboer, Vincent Tribout, Ignacio G. Bravo, Sonia Burrel, Vincent Foulongne, Samuel Alizon, Nicolas Tessandier
Summary: This study reports two cases of concomitant HSV-2 and HPV infections in young women. By analyzing their viral loads, immune responses, and vaginal microbiota, we gain a better understanding of the coinfection between these two viruses, highlighting the need for further research to confirm these interactions.
Article
Immunology
Mircea T. Sofonea, Benedicte Roquebert, Vincent Foulongne, David Morquin, Laura Verdurme, Sabine Trombert-Paolantoni, Mathilde Roussel, Jean-Christophe Bonetti, Judith Zerah, Stephanie Haim-Boukobza, Samuel Alizon
Summary: The study found that the Omicron variant has a greater growth advantage compared to the Delta variant and can generate significant COVID-19 activity in hospitals in France. Additionally, the magnitude of the BA.2 wave depends on the relaxation of control measures, but remains lower than that of BA.1 in median scenarios.
EMERGING INFECTIOUS DISEASES
(2022)
Article
Mathematical & Computational Biology
Bastien Reyne, Quentin Richard, Christian Selinger, Mircea T. Sofonea, Ramses Djidjou-Demasse, Samuel Alizon
Summary: This study proposes a non-Markovian alternative formalism based on partial differential equations for modeling the COVID-19 pandemic. It applies and analyzes the major factors contributing to hospital admissions in the 2021 epidemic in France, taking into account vaccine-induced and natural immunity. The findings suggest that vaccination rate alone is insufficient to control the epidemic, and there is significant uncertainty associated with the age-structured contact matrix.
MATHEMATICAL MODELLING OF NATURAL PHENOMENA
(2022)