ArticleScientific reports2020
Population mobility induced phase separation in SIS epidemic and social dynamics.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Emergence of shield immunity during spatial contagions.Npj complexity · 2025Article
- Model-inferred timing and infectious period of the chickenpox outbreak source.BMC infectious diseases · 2024Article
- Bounded risk disposition explains Turing patterns and tipping points during spatial contagions.Royal Society open science · 2024Article
- A Maximum Entropy Model of Bounded Rational Decision-Making with Prior Beliefs and Market Feedback.Entropy (Basel, Switzerland) · 2021Article
- COVID-19: A Comparative Study of Population Aggregation Patterns in the Central Urban Area of Tianjin, China.International journal of environmental research and public health · 2021Article
- The Polycentric Dynamics of Melbourne and Sydney: suburb attractiveness divides a city at the home ownership level.Proceedings. Mathematical, physical, and engineering sciences · 2021Article
- Modelling transmission and control of the COVID-19 pandemic in Australia.Nature communications · 2020Article
- Phase Transitions in Spatial Connectivity during Influenza Pandemics.Entropy (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Understanding the impact of behavior dependent mobility in the spread of epidemics and social disorders is an outstanding problem in computational epidemiology. We present a modelling approach for the study of mobility that adapts dynamically according to individual state, epidemic/social-contagion state and network topology in accordance with limited data and/or common behavioral models. We demonstrate that even for simple compartmental network processes, our approach leads to complex spatial patterns of infection in the endemic state dependent on individual behavior. Specifically, we characterize the resulting phenomena in terms of phase separation, highlighting phase transitions between distinct spatial states and determining the systems' phase diagram. The existence of such phases implies that small changes in the populations' perceptions could lead to drastic changes in the spatial extent and morphology of the epidemic/social phenomena.
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Registered trials
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