Related Experiment Video
Updated: Apr 7, 2026
16:14
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
14.3K
Traffic-driven epidemic spreading in correlated networks
Han-Xin Yang1, Ming Tang2, Ying-Cheng Lai3
1Department of Physics, Fuzhou University, Fuzhou 350108, China.
Summary
This study reveals that network correlation can minimize epidemic thresholds in traffic-driven spreading. The epidemic threshold depends non-monotonically on network assortativity, offering insights for epidemic control.
Area of Science:
- Complex Networks
- Epidemiology
- Network Science
Background:
- Previous research has explored traffic dynamics and epidemic spreading in complex networks.
- However, the interplay of traffic-driven epidemic spreading on correlated networks remains unaddressed.
Purpose of the Study:
- To investigate the phenomenon of traffic-driven epidemic spreading on correlated complex networks.
- To analyze the impact of network correlation, specifically assortativity, on epidemic thresholds.
Main Methods:
- Utilized degree-based mean-field theory to model traffic-driven epidemic spreading.
- Calculated the epidemic threshold for correlated networks considering packet-generation rate and network structure.
- Validated theoretical predictions through numerical simulations.
Main Results:
- Discovered a non-monotonic behavior in the epidemic threshold concerning the assortativity coefficient.
- Identified a critical assortativity value that minimizes the epidemic threshold.
- The epidemic threshold is inversely proportional to packet-generation rate and the largest eigenvalue of the betweenness matrix.
Conclusions:
- Network correlation plays a crucial role in modulating epidemic spreading dynamics.
- Findings provide a theoretical framework for understanding and potentially controlling epidemics driven by traffic flows in real-world networks.
Related Concept Videos
01:21Causality in Epidemiology
2.1K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
2.1K
01:18Steps in Outbreak Investigation
705
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
705
01:28Infectious Diseases and Their Occurrence
58
Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable...
58
01:23Investigation of Disease Outbreaks
51
Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
51
01:20Infection
14.4K
When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
14.4K
01:26Principles of Disease Surveillance
797
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
797