Welcome to the Contagion Models module! This module explores how ideas, behaviors, diseases, and innovations spread through social networks and populations. We’ll examine both biological and social contagion processes using computational modeling approaches.
Overview¶
Contagion models help us understand how things spread - from infectious diseases to social movements, from rumors to technological innovations. Through agent-based modeling, we’ll explore different mechanisms of transmission, the role of network structure, and intervention strategies for controlling or promoting different types of contagion.
Student Learning Objectives (SLOs)¶
By the end of this module, students will be able to:
- Construct data-driven, mathematical, statistical, and/or software models, analyzing their results to answer questions, solve problems, support arguments, draw conclusions, make predictions, and/or identify possible causal relationships.
- Identify and use tools appropriate for solving a given problem, such as algebra, calculus, and other mathematical tools; spreadsheets, databases, and data-analysis software; domain-specific software; and/or writing one’s own software.
- Distinguish between different types of contagion (biological, social, behavioral)
- Explain the role of network structure in contagion processes
- Analyze the dynamics of epidemic curves and tipping points
- Understand concepts like basic reproduction number (R₀) and herd immunity
- Implement SIR and SEIR epidemiological models in NetLogo
- Model contagion on different network topologies
- Analyze the effects of intervention strategies on spread dynamics
- Visualize and interpret contagion simulation results
- Evaluate the effectiveness of public health interventions
- Assess the parallels and differences between biological and social contagion
- Critique assumptions in contagion models and their real-world applicability
- Analyze the ethical implications of contagion research and policy
- Present epidemiological concepts to diverse audiences
- Discuss the role of modeling in public health decision-making
- Communicate uncertainty and risk in contagion scenarios
- Engage with contemporary debates about disease control and social influence
📚 Slides and Readings¶
Required Readings¶
Core Reading Materials
Kermack, W. O., & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London, 115(772), 700-721.
- 📖 PDF Download
- 🎯 Focus on: The foundational SIR model
Pastor-Satorras, R., & Vespignani, A. (2001). Epidemic spreading in scale-free networks. Physical Review Letters, 86(14), 3200-3203.
- 📖 PDF Download
- 🎯 Focus on: Network topology effects on epidemic spread
Centola, D. (2010). The spread of behavior in an online social network experiment. Science, 329(5996), 1194-1197.
- 📖 PDF Download
- 🎯 Focus on: Experimental evidence of social contagion
Funk, S., et al. (2010). Modelling the influence of human behaviour on the spread of infectious diseases. Journal of the Royal Society Interface, 7(50), 1247-1256.
- 📖 PDF Download
- 🎯 Focus on: Behavioral responses to epidemic threats
📝 Homework¶
🌟 Extra Materials¶
Historical Context¶
The Evolution of Epidemic Modeling
Mathematical Foundations:
- Bernoulli, D. (1760). Essai d’une nouvelle analyse de la mortalité causée par la petite vérole.
- Ross, R. (1911). The prevention of malaria. John Murray.
- Bailey, N. T. J. (1975). The mathematical theory of infectious diseases. Griffin.
Modern Developments:
- Anderson, R. M., & May, R. M. (1991). Infectious diseases of humans. Oxford University Press.
- Keeling, M. J., & Rohani, P. (2007). Modeling infectious diseases in humans and animals. Princeton University Press.
Network Epidemiology:
- Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393(6684), 440-442.
- Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509-512.
Real-World Applications¶
Contagion Models in Practice
Public Health Applications:
- COVID-19 pandemic modeling and policy responses
- Seasonal influenza vaccination strategies
- HIV prevention and treatment programs
- Malaria control in endemic regions
Social Contagion Examples:
- Viral marketing and social media campaigns
- Political movement organization and spread
- Financial contagion and market crashes
- Behavioral interventions for health promotion
Discussion Questions:
- How do behavioral changes affect epidemic dynamics?
- What are the ethical considerations in epidemic modeling?
- How can we balance individual privacy with public health surveillance?
- What role should predictive models play in policy decisions?
Current Research:
- Digital contact tracing and privacy concerns
- Vaccine hesitancy and misinformation spread
- Climate change effects on disease emergence
- One Health approaches to pandemic prevention