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Table of contents
Introduction
1 Multi-pathogen Systems
1.1 Introduction
1.2 Interaction mechanisms
1.3 Implications for epidemiology and public health
1.4 Modeling multi-pathogen interactions
1.4.1 Compartmental models
1.4.2 Ecological insights from multi-strain models
1.5 Open challenges in modelling multi-strain dynamics
2 Epidemics on Networks
2.1 Introduction
2.2 Network data in epidemiology
2.3 Network analysis
2.3.1 Basic definitions
2.3.2 Topological properties
2.3.3 Temporal networks
2.3.4 Null models
2.3.5 Generative models
2.4 Epidemics on networks
2.4.1 Static networks
2.4.2 Temporal networks
2.5 Multi-strain dynamics on networks
2.5.1 Competitive interactions in SIS dynamics
2.5.2 Competitive interactions in SIR dynamics
2.5.3 Cooperative interactions in SIS dynamics
2.5.4 Cooperative interactions in SIR dynamics
2.5.5 Multiple pathogens on networks
3 Host Contact Dynamics and Diversity in Pathogen Strains
3.1 Introduction
3.2 Ecological modeling of multi-strain dynamics
3.2.1 Ecological characterization of multi-strain populations
3.3 Case study: S. aureus spread in hospitals
3.3.1 Overview of S. aureus ecology
3.3.2 The I-Bird experiment
3.4 First article: Host contact dynamics shapes richness and dominance of pathogen strains
3.5 Additional results: neutral dynamics
3.5.1 Domination time and attack rate
3.5.2 Impact of bursty contacts on strain diversity
3.6 Additional results: non-neutral dynamics
3.6.1 Simulation results
3.6.2 Analytical derivation of the condensation threshold
3.6.3 Numerical characterization of the s < sc regime
3.7 Conclusions
4 The Interplay of Cooperative and Competitive Interactions
4.1 Introduction
4.2 Pathogen-pathogen interactions and their impact on multi-strain ecosystems
4.3 Factors affecting co-existence between multiple strains
4.4 Second article: Interplay between competitive and cooperative interactions in a three-player pathogen system
4.5 Conclusions
5 Conclusions and Perspectives
A Multi-strain model
A.1 Model description
A.2 Simulating transmission
B Condensation threshold on networks
B.1 General framework
B.2 Analytical results


