ArticlePLoS computational biology2010
Untangling the Interplay between Epidemic Spread and Transmission Network Dynamics.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Review of Network Models for HIV Spread.Journal of acquired immune deficiency syndromes (1999) · 2025Pooled it
- Emerging infectious disease surveillance using a hierarchical diagnosis model and the Knox algorithm.Scientific reports · 2023Article
- The illusion of personal health decisions for infectious disease management: disease spread in social contact networks.Royal Society open science · 2023Article
- The spatiotemporal transmission dynamics of COVID-19 among multiple regions: a modeling study in Chinese provinces.Nonlinear dynamics · 2022Article
- Concurrency measures in the era of temporal network epidemiology: a review.Journal of the Royal Society, Interface · 2021Review
- Measles dynamics on network models with optimal control strategies.Advances in difference equations · 2021Article
- Predicting and analyzing the COVID-19 epidemic in China: Based on SEIRD, LSTM and GWR models.PloS one · 2020Article
- Quantifying the propagation of distress and mental disorders in social networks.Scientific reports · 2018Article
- Spread of competing viruses on heterogeneous networks.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2017Article
- Stochastic Models of Emerging Infectious Disease Transmission on Adaptive Random Networks.Computational and mathematical methods in medicine · 2017Article
- Article
- Systematic Approximations to Susceptible-Infectious-Susceptible Dynamics on Networks.PLoS computational biology · 2016Article
- Prevention of infectious diseases by public vaccination and individual protection.Journal of mathematical biology · 2016Article
- The Impact of Heterogeneity and Awareness in Modeling Epidemic Spreading on Multiplex Networks.Scientific reports · 2016Article
- SI infection on a dynamic partnership network: characterization of R0.Journal of mathematical biology · 2015Article
- New technologies in predicting, preventing and controlling emerging infectious diseases.Virulence · 2015Review
- Network epidemiology and plant trade networks.AoB PLANTS · 2014Article
- Epidemic spread on weighted networks.PLoS computational biology · 2013Article
- Bursts of vertex activation and epidemics in evolving networks.PLoS computational biology · 2013Article
- Influence of network dynamics on the spread of sexually transmitted diseases.Journal of the Royal Society, Interface · 2012Article
Corrections and comments
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1 author.
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No grant is acknowledged in the PubMed record.
Abstract
The epidemic spread of infectious diseases is ubiquitous and often has a considerable impact on public health and economic wealth. The large variability in the spatio-temporal patterns of epidemics prohibits simple interventions and requires a detailed analysis of each epidemic with respect to its infectious agent and the corresponding routes of transmission. To facilitate this analysis, we introduce a mathematical framework which links epidemic patterns to the topology and dynamics of the underlying transmission network. The evolution, both in disease prevalence and transmission network topology, is derived from a closed set of partial differential equations for infections without allowing for recovery. The predictions are in excellent agreement with complementarily conducted agent-based simulations. The capacity of this new method is demonstrated in several case studies on HIV epidemics in synthetic populations: it allows us to monitor the evolution of contact behavior among healthy and infected individuals and the contributions of different disease stages to the spreading of the epidemic. This gives both direction to and a test bed for targeted intervention strategies for epidemic control. In conclusion, this mathematical framework provides a capable toolbox for the analysis of epidemics from first principles. This allows for fast, in silico modeling--and manipulation--of epidemics and is especially powerful if complemented with adequate empirical data for parameterization.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.