Statistical Physics Of Vaccination
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Date
2016-12-09
Authors
Wang, Zhen
Bauch, Chris T.
Bhattacharyya, Samit
d'Onofrio, Alberto
Manfredi, Piero
Perc, Matjaz
Perra, Nicola
Salathe, Marcel
Zhao, Dawei
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination one of the most important preventive measures of modern times is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research.
Description
The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.physrep.2016.10.006 © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
Epidemiology, Vaccination, Human behavior, Complex networks, Data