Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases

<p>Behavioral epidemiology of infectious diseases: an overview (C.  Bauch et al.). -Part 1. Field data on behaviour. -Survey on the likely behavioural changes of the general public in 4 European countries during the 2009/2010 pandemic (C. Rizzo et al.). -Factors influencing infant and adolescent vaccine uptake in Flanders, Belgium (H. Theeten et al). -Part 2. Modeling behaviour change in response to epidemic threats. -Modeling the Impact of Behavior Changes on the Spread of Pandemic Influenza (S.Y. Del Valle et al.). -Uncoordinated human responses during epidemic outbreaks (P. Poletti et al.). -The talk of the town: modelling the spread of information and changes in behavior (S. Funk and V. Jansen). -Modeling contact and mobility based social response to the spreading of infectious diseases (N. Perra and A. Vespignani). -Incorporating human behaviour in epidemic dynamics: a modelling perspective (Istvan Z. Kiss). -Risk perception, heuristics and epidemic spread  (P. Liò et al.). -The mechanism and phenomena of adaptive human behavior during an epidemic and the role of information (E.P. Fenichel and X. Wang). -Part 3. Modeling vaccinating behaviour. -The Economic approach to modeling self-protective behaviour in epidemiology (F. Chen). -Mathematical epidemiology and welfare economics (M. Gersovitz). -Modeling influenza vaccination behaviour via inductive reasoning games (R. Vardavas and C.S. Marcum). -Modeling voluntary influenza vaccination using an age-structured inductive reasoning game (R. Breban). -Emergent dynamical features in behaviour-incidence models of vaccinating decisions (S. Bhattacharyya and C.T. Bauch). -Impact of vaccine behavior on the resurgence of measles  (E. Shim et al.). -Vaccinating behavior and the dynamics of vaccine preventable infections (A. d'Onofrio et al.). -The geometrical approach to global stability in behavioral epidemiology (B. Buonomo et al.). - "Capturing human behaviour: is it possible to bridge the gap between data and models?" (W.J. Edmunds et al.).</p>