Systems Science

A system is set of things that are interconnected in ways that result in the generation of identifiable behavioral patterns over time. Systems Science is an interdisciplinary field that studies the complexity of systems in nature, social or any other scientific field. Some of the systems science methodologies include systems dynamics modeling, agent-based modeling, microsimulation, and Big Data techniques. Systems science thinking can help researchers to understand the factors influencing the distribution and determinants of health and disease in populations, by providing information on the broad picture on how individuals and other components of populations are interconnected in society in scenarios in which researchers cannot controlled the environment. Therefore, system science thinking can help researchers to find answers on how interventions may generate change in disease outcomes given the system multilevel factors present in populations.




The challenge of complexity in health care

Learning from evidence in a complex world

Estimating Neighborhood Health Effects: The Challenges of Causal Inference in a Complex World

Causal Thinking and Complex System Approaches in Epidemiology

Complexity, Simplicity and Epidemiology

Social network analysis and agent-based modeling in social epidemiology

Network analysis in public health: history, methods, 
and applications


Agent-based simulation platforms: review and development recommendations

Modeling and analysis of global epidemiology of avian influenza


Are network-based interventions a useful anti-obesity strategy? An illustration of agent-based counterfactual simulations for causal inference in epidemiology

Reducing social inequalities in health: the role of simulation modelling in chronic disease epidemiology to evaluate the impact of population health interventions

Assessing the impact on chronic disease of incorporating the societal cost of greenhouse gases into the price of food: an econometric and comparative risk assessment modelling study

System dynamics modeling for public health: background and opportunities

A simple model predicting individual weight change in humans

Epidemiology in the Big Data Era

You are what you Tweet: Analyzing Twitter for public health