Statistical physics of vaccination

@article{Wang2016StatisticalPO,
  title={Statistical physics of vaccination},
  author={Zhen Wang and Chris T. Bauch and Samit Bhattacharyya and Alberto d’Onofrio and Piero Manfredi and Matja{\vz} Perc and Nicola Perra and Marcel Salath{\'e} and Dawei Zhao},
  journal={ArXiv},
  year={2016},
  volume={abs/1608.09010}
}
The field theoretical ABC of epidemic dynamics
TLDR
This report goes at the heart of mathematical modelling of infectious disease diffusion by simultaneously investigating the underlying microscopic dynamics in terms of percolation models, effective description via compartmental models and the employment of temporal symmetries naturally encoded in the mathematical language of critical phenomena.
Statistical challenges and opportunities in modelling coupled behaviour-disease dynamics of vaccine refusal
TLDR
The study and modelling of vaccine refusal can greatly benefit from using mechanistic models informed by both traditional and state-of-the-art statistical methodologies.
Multiple epidemic waves as the outcome of stochastic SIR epidemics with behavioral responses: a hybrid modeling approach
In the behavioral epidemiology (BE) of infectious diseases, little theoretical effort seems to have been devoted to understand the possible effects of individuals’ behavioral responses during an
Individual risk perception and empirical social structures shape the dynamics of infectious disease outbreaks
The dynamics of a spreading disease and individual behavioral changes are entangled processes that have to be addressed together in order to effectively manage an outbreak. Here, we relate individual
Infection Percolation: A Dynamic Network Model of Disease Spreading
TLDR
This work presents a dynamic network model that provides a straightforward way to incorporate both disease transmission dynamics at the individual scale as well as the full spatiotemporal history of infection at the population scale and develops a scaling theory that predicts the dynamics of infection for diverse diseases and populations.
Pulsating campaigns of human prophylaxis driven by risk perception palliate oscillations of direct contact transmitted diseases
TLDR
Analytically, the interplay between the personal decision to protect oneself from infection and the spreading of an epidemic is explored, by coupling a decision game based on the perceived risk of infection with a Susceptible-Infected-Susceptible model.
Competition between vaccination and disease spreading.
TLDR
The interaction between epidemic spreading and a vaccination process is studied in the framework of mean-field theory finding a rich phase diagram and Numerical simulations for homogeneous random networks agree very well with analytical predictions.
...
...

References

SHOWING 1-10 OF 836 REFERENCES
Modeling infectious disease dynamics in the complex landscape of global health
TLDR
The development of mathematical models used in epidemiology are reviewed and how these can be harnessed to develop successful control strategies and inform public health policy, using the West African Ebola epidemic as an example.
Mathematical Models for Infectious Disease Statistics
TLDR
A new deterministic model is presented which takes into account increased infection transmission inside schools inside schools, which provides an explanation for one- and two-year periods of recurrent measles epidemics.
Behavioral Epidemiology of Infectious Diseases: An Overview
TLDR
An attempt to motivate the historical and cultural background underpinning the BE revolution, focusing on the issue of rational opposition to vaccines as a natural endpoint of the changed relation between man and disease in modern industrialized countries.
A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks
TLDR
For populations where infection can spread only through social contact network, relatively small differences in parameter values relating to perceived risk or vaccination behavior at the individual level can translate into large differences in population-level outcomes such as final size and final number vaccinated.
Coupled disease–behavior dynamics on complex networks: A review
Dynamics of interacting diseases
TLDR
This work characterize analytically the epidemic thresholds of the two diseases for different scenarios and also compute the temporal evolution characterizing the unfolding dynamics and finds that the secondary thresholds for the SIS and SIR models are different, which results directly from the interaction between both diseases.
Networks and epidemic models
TLDR
A variety of methods are described that allow the mixing network, or an approximation to the network, to be ascertained and how the two fields of network theory and epidemiological modelling can deliver an improved understanding of disease dynamics and better public health through effective disease control are suggested.
Pattern transitions in spatial epidemics: Mechanisms and emergent properties
Network theory and SARS: predicting outbreak diversity
Seasonnally forced disease dynamics explored as switching between attractors
...
...