ArticlePLoS computational biology2020
Data-driven contact structures: From homogeneous mixing to multilayer networks.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Characterizing the impact of incorporating spatially aggregated human mobility data into infectious disease models.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Mapping spatial colleague connectivity patterns from individual-level registry data to inform regional pandemic interventions.PLoS computational biology · 2026Article
- Coupled Dynamics of Information-Epidemic Spreading with Resource Allocation and Transmission on Multi-Layer Networks.Entropy (Basel, Switzerland) · 2025Article
- Infectious Disease Surveillance in the Era of Big Data and AI: Opportunities and Pitfalls.Cureus · 2025Review
- Multilayer networks describing urban interactions for building the digital twins of five cities in Spain.Scientific data · 2025Article
- Reconciling heterogeneous dengue virus infection risk estimates from different study designs.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Generalized contact matrices allow integrating socioeconomic variables into epidemic models.Science advances · 2024Article
- Reconciling heterogeneous dengue virus infection risk estimates from different study designs.medRxiv : the preprint server for health sciences · 2024Article
- Building a Simple Model to Assess the Impact of Case Investigation and Contact Tracing for Sexually Transmitted Diseases: Lessons From COVID-19.AJPM focus · 2024Article
- Sociodemographic Variables Can Guide Prioritized Testing Strategies for Epidemic Control in Resource-Limited Contexts.The Journal of infectious diseases · 2023Article
- Evaluating the impact of test-trace-isolate for COVID-19 management and alternative strategies.PLoS computational biology · 2023Article
- Impact of contact data resolution on the evaluation of interventions in mathematical models of infectious diseases.Journal of the Royal Society, Interface · 2022Article
- Quantifying human mixing patterns in Chinese provinces outside Hubei after the 2020 lockdown was lifted.BMC infectious diseases · 2022Article
- Assessing the role of multiple mechanisms increasing the age of dengue cases in Thailand.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Why Plasmodium vivax and Plasmodium falciparum are so different? A tale of two clades and their species diversities.Malaria journal · 2022Review
- Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics.PloS one · 2021Article
- Modeling partial lockdowns in multiplex networks using partition strategies.Applied network science · 2021Article
- Measles dynamics on network models with optimal control strategies.Advances in difference equations · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The modeling of the spreading of communicable diseases has experienced significant advances in the last two decades or so. This has been possible due to the proliferation of data and the development of new methods to gather, mine and analyze it. A key role has also been played by the latest advances in new disciplines like network science. Nonetheless, current models still lack a faithful representation of all possible heterogeneities and features that can be extracted from data. Here, we bridge a current gap in the mathematical modeling of infectious diseases and develop a framework that allows to account simultaneously for both the connectivity of individuals and the age-structure of the population. We compare different scenarios, namely, i) the homogeneous mixing setting, ii) one in which only the social mixing is taken into account, iii) a setting that considers the connectivity of individuals alone, and finally, iv) a multilayer representation in which both the social mixing and the number of contacts are included in the model. We analytically show that the thresholds obtained for these four scenarios are different. In addition, we conduct extensive numerical simulations and conclude that heterogeneities in the contact network are important for a proper determination of the epidemic threshold, whereas the age-structure plays a bigger role beyond the onset of the outbreak. Altogether, when it comes to evaluate interventions such as vaccination, both sources of individual heterogeneity are important and should be concurrently considered. Our results also provide an indication of the errors incurred in situations in which one cannot access all needed information in terms of connectivity and age of the population.
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