The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Dynamics and Control of Diseases in Networks with Community Structure
Open accessAbstract
The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“When a population is organised in this fashion the capacity of epidemics to spread is reduced (Keeling 1999; Salathe ´ & Jones 2010).”
From Parasite-stress promotes in-group assortative sociality: The cases of strong family ties and heightened religiosity (2012) · cites this paper as Salathé & Jones 2010
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Social Network Analysis: Methods and Applications
Wasserman, S. S., & Faust, K. (1994) · Cited by 18,005
Centrality in social networks conceptual clarification
Freeman, L. C. (1978) · Social Networks · doi:10.1016/0378-8733(78)90021-7 · Cited by 17,062
Community structure in social and biological networks
Girvan, M., & Newman, M. E. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.122653799 · Cited by 15,502
Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
Infectious Diseases of Humans: Dynamics and Control
(1992) · Annals of Internal Medicine · doi:10.7326/0003-4819-117-2-174_4 · Cited by 7,819
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Error and attack tolerance of complex networksPreprint
Albert, R., Jeong, H., & Barabási, A.-Ĺ. (2000) · Cited by 6,554
Epidemic Spreading in Scale-Free Networks
Pastor‐Satorras, R., & Vespignani, A. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.3200 · Cited by 5,785
Uncovering the overlapping community structure of complex networks in nature and society
Palla, G., Derényi, I., Farkas, I., & Vicsek, T. (2005) · Nature · doi:10.1038/nature03607 · Cited by 5,373
Flagged first, then by citations
Cited by
Sorted by citations
Items 501–585 of 585
Comment Diffusons-nous sur les Réseaux Sociaux ?Preprint
Stattner, E. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1602.00252
epidemiological network Clusters of poverty and disease emerge from feedbacks on an
Pluciński, M. M., Getz, W. M., & Bonds, M. H. (2012)
Higher-Order Networks in Complex Systems: Temporality and Interconnectivity
Wider, N. (2016) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-a-010657886
Scalable community detection for social networks
Pérez, A. P. (2016) · doi:10.5821/dissertation-2117-96317
Financial Bridges and Network CommunitiesPreprint
Casarin, R., Costola, M., & Yenerdag, E. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2951716
Spatio-temporal distribution and persistence of Mycobacterium bovis in a badger population
Benton, C. H. (2017) · Figshare
Third Party Effect: Community Based Spreading in Complex Networks
Bauckhage, C., Ojeda, C., Sifa, R., & Agarwal, S. (2017) · Springer eBooks · doi:10.1007/978-3-658-19287-7_5
Disease Spreading in Time-Evolving Networked Communities
Pacheco, J. M., Segbroeck, S. V., & Santos, F. C. (2017) · Theoretical biology · doi:10.1007/978-981-10-5287-3_13
Estudo da relação estrutura-dinâmica em redes modulares
Comin, C. H. (2016) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.76.2016.tde-14102016-085653
A suitable data model for HIV infection and epidemic detection
Safaei, A., Azad, M., & Abdi, F. (2015) · Journal of Occupational Health and Epidemiology · doi:10.18869/acadpub.johe.4.4.229
Gang, L., Guodong, Y., Haitao, T., Liu, K., & Yongzhong, S. (2017) · International Conference on Information Management and Engineering (ICIME) · doi:10.1145/3149572.3149573
Barnard, R. C., Kiss, I. Z., Luc Berthouze, A., & Miller, J. C. (2018) · Bulletin of Mathematical Biology · doi:10.1007/s11538-018-0484-5 · Cited by 15
Sah, P. (2017) · DigitalGeorgetown (Georgetown University Library)
Efficient vaccination strategies for epidemic control using network informationPreprint
Yang, Y., McKhann, A., Chen, S., Harling, G., & Onnela, J.-P. “. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1903.07503
The costs and benefits of sociality in semi-free ranging Barbary macaques (Macaca sylvanus)
Müller‐Klein, N. (2019) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-7319
The Link Stream of Contacts in a Whole HospitalPreprint
Martinet, L., Crespelle, C., Eric Fleury, B., Boëlle, P., & Guillemot, D. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1805.05752
The effects of heterogeneity in individual infectiousness on disease modeling predictions
White, L. A. (2018) · University of Minnesota Digital Conservancy (University of Minnesota)
Comment Diffusons-nous sur les R\'eseaux Sociaux ?
Stattner, E. (2015) · HAL
NNC: Neural-Network Control of Dynamical Systems on GraphsPreprint
Asikis, T., Böttcher, L., & Antulov-Fantulin, N. (2020) · arXiv (Cornell University) · doi:10.3929/ethz-b-000450528
The Silent PartnersPreprint
Almogy, G. (2020) · Preprints.org · doi:10.20944/preprints202007.0475.v1
Stochastic Dynamic Optimization in Spatial and Network Resource Economic Models.
Alebrahim, E. K. E. S. (2020) · NCSU Libraries Repository (North Carolina State University Libraries)
Creating a Cross-Domain Simulation Framework for Risk Analyses of Cities
Schauer, S., & Raß, S. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-62840-6_15
On node ranking in graphsPreprint
Dudkina, E., Bin, M., Breen, J., Crisostomi, E., Ferraro, P., Kirkland, S., Mareček, J., Murray‐Smith, R., Parisini, T., Stone, L., et al. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2107.09487
Paul, G. A. (2021) · University of Minnesota Digital Conservancy (University of Minnesota)
More Efficient, Doubly Robust, Nonparametric Estimators of Treatment Effects in Multilevel StudiesPreprint
Park, C., & Kang, H. (2021) · arXiv (Cornell University)
Finding Community Structures In Social Activity Data
Peng, C. (2015) · King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) · doi:10.25781/kaust-5cbcp
Network Analysis for Surveillance Design and Evaluation
Fournié, G., Delabouglise, A., Métras, R., Kim, Y., & Duboz, R. (2022) · Springer eBooks · doi:10.1007/978-3-030-82727-4_11
The Silent PartnersPreprint
Almogy, G. (2020) · Preprints.org · doi:10.20944/preprints202007.0475.v2
Kim, S., & Choi, J. (2022) · Biology · doi:10.3390/biology11101409
Sulaimon, T. A., Chaters, G. L., Nyasebwa, O. M., Swai, E. S., Cleaveland, S., Enright, J. A., Kao, R. R., & Johnson, P. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.04.510793
Multi-strain disease dynamics on metapopulation networksPreprint
Smith, M. J., VanderWaal, K. L., Torremorell, M., Corzo, C. A., & Craft, M. E. (2022) · doi:10.22541/au.156026839.96630781/v2
(2022) · Advances in computational intelligence and robotics book series · doi:10.4018/978-1-7998-8343-2.ch007
Gorji, M.-A., & Boushehri, S. N. S. (2023) · Research Square · doi:10.21203/rs.3.rs-2936581/v1
On the impact of population density and mobility restrictions in the control of epidemic spreading
Hurrelbrink, A., & Topîrceanu, A. (2023) · IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) · doi:10.1109/saci58269.2023.10158557
Individual Disgust and Collective Anxiety: A Two-Layer Framework of the Behavioral Immune SystemPreprint
Yin, B., Zheng, B., & Ye, Y. (2024) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/a3f9p
A Primer on Graph-Theoretic Models and Metrics: Using Graphs for Modeling and Assessing Robustness
Snyder, D., Johnson, C., Hastings, K. C., Bennett, B. E., Menthe, L., & Steier, J. (2024) · RAND Corporation eBooks · doi:10.7249/rra1506-1
Community Discovery in Complex Network Big Data
Ji, Q. (2024) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/979-8-3693-4292-3.ch003
Firiza, S.-M., Scornea, A.-M., & Topîrceanu, A. (2024) · IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) · doi:10.1109/saci60582.2024.10619727
( ω 1 , ω 2 ) -temporal random hyperbolic graphs
Zambirinis, S., & Papadopoulos, F. (2024) · Physical review. E · doi:10.1103/physreve.110.024309
Reconstruction of genomic and proteomic scale network structures and functions
Choudhari, J. K., Gupta, A. K., Bhatt, S., Kurmi, S., & Chouhan, U. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-22326-6.00013-4
Simulating the diffusion of PPR-like disease to improve surveillancePreprint
Mesdour, A., Ijoma, S. I., Bolajoko, M.-B., Ciss, M., Cardinale, É., Eubank, S., Andraud, M., & Apolloni, A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.08.627410
Ma, J., & Yuan, Z. (2025) · Physics Letters A · doi:10.1016/j.physleta.2025.130582
Fragmented social networks promote complex behavioural contagions over infectious disease spread
Wijayatilake, N., Bansal, S., Pedersen, A., & Silk, M. (2025) · bioRxiv · doi:10.1098/rspb.2026.1424
Community aware temporal network generation
Girardini, N. A., Longa, A., Trebucchi, G., Cencetti, G., Passerini, A., & Lepri, B. (2025) · Applied Network Science · doi:10.1007/s41109-025-00731-w
Bridges in social networks: current status and challenges
Kim, J., Jeong, S., Kim, J., & Lim, S. (2025) · PeerJ Computer Science · doi:10.7717/peerj-cs.3122
Kurihara, S. (2025) · Springer eBooks · doi:10.1007/978-981-96-8066-5_8
Infection risk assessment for socially structured population using stochastic microexposure model
Vecherin, S. N., Meyer, A. C., Cummings, C. L., Trump, B. D., Ehlschlaeger, C., & Linkov, I. (2025) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/s41370-025-00811-0
Spread of the plague in Venice, 1630–1631: epidemic entropy in a “natural experiment”Preprint
Hwang, J. L., Srivathsan, A., Deiner, M. S., Blumberg, S., Porco, T. C., & Lietman, T. M. (2025) · medRxiv · doi:10.1101/2025.10.06.25335371
Pacheco, M. D. R. B., & Devoto, M. (2025) · Oikos · doi:10.1002/oik.11077
Multilayer modular fusion graph attention network (MMF-GAT) for epidemic prediction
Fujimoto, K., Liu, L., Kuo, J. C., Gao, B., Chan, H. K., Carr, M., Sealy, R., Luo, X., & Bahl, J. (2025) · PLOS complex systems. · doi:10.1371/journal.pcsy.0000070
Random hyperbolic graphs with arbitrary mesoscale structures
Guarino, S., Mastrostefano, E., & Torre, D. (2025) · Physical review. E · doi:10.1103/5q8n-lnc1 · Cited by 1
An Analysis of Vaccination Strategies on Epidemic Spread in a Friendship Network
Nair, N. S., John, J. M., & Lekha, D. S. (2025) · International Conference on Smart Computing and Communications (ICSCC) · doi:10.1109/icscc66177.2025.11233558
DynaMap: A Map Equation-based Parallel Algorithm for Detecting Communities on Dynamic Graphs
Santos, G. G., Lakhotia, K., & Rose, C. A. F. D. (2025) · International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) · doi:10.1109/sbac-pad66369.2025.00021
Mesdour, A., Ijoma, S. I., Bolajoko, M.-B., Ciss, M., Eubank, S., Cardinale, É., Andraud, M., & Apolloni, A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.16.693877
Stochastic Epidemic Modeling on Networks Using Markov Processes: A Simulation Study
Sailaja, Y., Chakote, S., Shreyashwini, R., & Khandelwal, V. (2025) · International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS) · doi:10.1109/csitss67709.2025.11294530
Yu, G., Garee, M. J., Ventresca, M., & Yih, Y. (2024) · Figshare · doi:10.6084/m9.figshare.25449051
Feld, Y., & Hartmann, A. K. (2025) · Physical review. E · doi:10.1103/8g2r-w6x6
Halász, V., & Rocklöv, J. (2026) · Scientific Reports · doi:10.1038/s41598-025-33300-3
A new take on optimal vaccine prioritization: when age-based strategy is efficient?
Gonçalves, M., Fierens, P. I., & Leandro Chaves, R. E. G. O. (2026) · International Journal of Data Science and Analytics · doi:10.1007/s41060-026-01053-5
Romano, V. (2017) · theses.fr (ABES) · doi:10.70675/f70af640z4487z412fz8448zff17c4cdc483 · Cited by 1
Network epidemiology aimed at risk assessment in infection prevention and control
Darbon, A. (2019) · theses.fr (ABES) · doi:10.70675/4098cb12zbf15z4268z8541zb3acde05db44
Community-Aware Network Dismantling via Gateways: Large-Scale Evaluation on LFR Benchmarks
Sawicki, J., Ganzha, M., Paprzycki, M., Han, J., & Sahu, S. (2026) · Future Internet · doi:10.3390/fi18040212
Topology-Driven Mental Health Resilience: A Network Science Simulation Study
AlMakinah, R., & Canbaz, M. A. (2026) · Studies in computational intelligence · doi:10.1007/978-3-032-16719-4_21
Graph attention-guided dynamics for adaptive community evolution in complex networks
Moujahid, A., & Marquez, C. R. (2026) · Journal of Computational Science · doi:10.1016/j.jocs.2026.102887
Zhang, M., Maekawa, T., Sekiguchi, K., Murata, T., & Ohsawa, Y. (2026) · JMIR Formative Research · doi:10.2196/90393
Leitch, J., Jordan, N. R., Drake, J. M., Cant, M. A., & Alexander, K. A. (2026) · Ecology and Evolution · doi:10.1002/ece3.73719
Effects of network community quarantine strength on disease transmission
Yang, M., Chen, Y. X., Yang, C., & Dang, L. (2026) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0326554
Ullah, M. S., & Wang, J. (2026) · Complexity · doi:10.1155/cplx/9893312
Preventing Epidemic Spread Using Leaky Vaccines
Chen, D. Q., Li, A., Li, G., Marathe, M., Srinivasan, A., Vullikanti, A., & Wu, J. (2026) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi69079.2026.00117
Boudouma, F., Farhi, Y., Dehhaoui, M., Hajji, H., Arbani, O., Kadi, K. A. E., & Fellahi, S. (2026) · Veterinary Sciences · doi:10.3390/vetsci13090858
Dynamics of opinion-disease coevolution in complex networks
Ke, L., Zhu, Y., Jiang, J., & Liu, J. (2026) · The European Physical Journal B · doi:10.1140/epjb/s10051-026-01270-8
Lezaar, Y., Boumalik, M., Lhor, Y., El-Ayachi, M., Araba, A., & Bouslikhane, M. (2023) · Epidemiology - Open Journal · doi:10.17140/epoj.2023.v8.i01.pp20-38.1670
Metadata
- Authors
- Salathé, M., & Jones, J. H.
- Affiliations
- Stanford University (US)
- Corresponding author
- Salathé, Marcel
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-04-08
- Volume
- 6
- Issue
- 4
- Pages
- e1000736
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC2851561
- OpenAlex
- W2010965902
- Cited by
- 586
- References
- 61
- Citations by year
- 2026: 18 · 2025: 27 · 2024: 34 · 2023: 32 · 2022: 33 · 2021: 50 · 2020: 42 · 2019: 36 · 2018: 53 · 2017: 33 · 2016: 41 · 2015: 44 · 2014: 39 · 2013: 37 · 2012: 36
- FWCI
- 23.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Funders
- National Science Foundation (0619926)
- National Institutes of Health
- National Institute of General Medical Sciences (GM28016, R01GM028016)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (K01HD051494, K01HD51494)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- disease transmission, community structure, contact networks, epidemic dynamics, vaccination strategies, bridge nodes, limited vaccine supply, disease control, social networks
- MeSH terms
- Algorithms, Computer Simulation, Disease Outbreaks, Humans, Residence Characteristics, Stochastic Processes, Vaccination, Incidence, Databases, Factual, Community-Acquired Infections, Disease Transmission, Infectious, Computational Biology, Host-Pathogen Interactions
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
