Revolutionise Your Approach
Geospatial models
Leverage modern geospatial models like high-resolution street network data to model epidemics in real populations.
Optimisation approaches
Respond to outbreaks better by using mathematical optimisation for resource allocation in response to pathogen models.
Complex ABMs
Simulate realistic large populations and complex behaviours using agent-based modeling.
About the Author
I'm a computational epidemiologist/data scientist working at the intersection of computational science, public health and AI. Board certified in public health, my work on COVID-19 has been featured in national media and television, and I'm the author of a number of peer-reviewed papers on the subject. I'm passionate about the power of computational models to change the world of epidemiology for the better and help us respond faster to epidemic threats. You can read more about me here.
Chris von Csefalvay
CPH FRSPH FRSA MTOPRA
Learn Cutting-Edge Techniques
Spatial distribution models
Predict spatial spread using flow networks.
Multi-risk modeling
Determine optimal vaccination strategies in risk-stratified populations.
Lyapunov exponents
Calculate the exposure of a model to non-linearities in its initial parameters using Lyapunov exponents.
CWT
Use Continuous Wavelet Transforms to identify how periodicities change over time.
Equilibria
Computationally estimate equilibria of analytically intractable models.
Random Walks
Simulate stochastic and Lévy flight behaviours over real-world networks.
Computational Modeling of Infectious Disease is now available on Amazon, Elsevier and all good booksellers.