{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T06:11:58Z","timestamp":1774937518090,"version":"3.50.1"},"reference-count":72,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T00:00:00Z","timestamp":1752537600000},"content-version":"vor","delay-in-days":19,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Northeastern University London"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Modelling epidemics using contact networks provides a significant improvement over classical compartmental models by explicitly incorporating the network of contacts. However, while network-based models describe disease spread on a given contact structure, their potential for inferring the underlying network from epidemic data remains largely unexplored. In this work, we consider the edge-based compartmental model, a compact and analytically tractable framework, and we integrate it within dynamical survival analysis to infer key network properties along with parameters of the epidemic itself. Despite correlations between structural and epidemic parameters, our framework demonstrates robustness in accurately inferring contact network properties from synthetic epidemic simulations. Additionally, we apply the framework to real-world outbreaks\u2014the 2001 UK foot-and-mouth disease outbreak and the COVID-19 epidemic in Seoul\u2014to estimate both disease parameters and network characteristics. Our results show that our framework achieves good fits to real-world epidemic data and reliable short-term forecasts. These findings highlight the potential of network-based inference approaches to uncover hidden contact structures, providing insights that can inform the design of targeted interventions and public health strategies.<\/jats:p>","DOI":"10.1093\/comnet\/cnaf018","type":"journal-article","created":{"date-parts":[[2025,7,15]],"date-time":"2025-07-15T14:56:52Z","timestamp":1752591412000},"source":"Crossref","is-referenced-by-count":0,"title":["Inferring contact network characteristics from epidemic data via compact mean-field models"],"prefix":"10.1093","volume":"13","author":[{"given":"Andr\u00e9s","family":"Guzm\u00e1n","sequence":"first","affiliation":[{"name":"Network Science Institute, Northeastern University London , 58 St Katharine's Way , London E1W 1LP,","place":["United Kingdom"]}]},{"given":"Federico","family":"Malizia","sequence":"additional","affiliation":[{"name":"Network Science Institute, Northeastern University London , 58 St Katharine's Way , London E1W 1LP,","place":["United Kingdom"]}]},{"given":"Gyeong Ho","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Big Data Science, Korea University Sejong Campus , 2511 Sejong-ro , Sejong 30019,","place":["South Korea"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7512-118X","authenticated-orcid":false,"given":"Boseung","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Big Data Science, Korea University Sejong Campus , 2511 Sejong-ro , Sejong 30019,","place":["South Korea"]},{"name":"\u00a0Biomedical Mathematics Group, Institute for Basic Science , 55 Expo-ro, Yuseong-gu , Daejeon 34126,","place":["South Korea"]},{"name":"College of Public Health, The Ohio State University , 1735 Neil Ave , Columbus OH 43210,","place":["United States"]}]},{"given":"Diana","family":"Cole","sequence":"additional","affiliation":[{"name":"School of Engineering, Mathematics and Physics, University of Kent , Cornwallis Buildings , Canterbury CT2 7NZ,","place":["United Kingdom"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1473-6644","authenticated-orcid":false,"given":"Istv\u00e1n Z","family":"Kiss","sequence":"additional","affiliation":[{"name":"Network Science Institute, Northeastern University London , 58 St Katharine's Way , London E1W 1LP,","place":["United Kingdom"]},{"name":"Department of Mathematics, Northeastern University , 360 Huntington Ave , Boston MA 02115,","place":["United States"]}]}],"member":"286","published-online":{"date-parts":[[2025,7,15]]},"reference":[{"key":"2025071513061765600_cnaf018-B1","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/978-3-319-50806-1","volume-title":"Mathematics of Epidemics on Networks","author":"Kiss","year":"2017"},{"key":"2025071513061765600_cnaf018-B2","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1103\/RevModPhys.87.925","article-title":"Epidemic processes in complex networks","volume":"87","author":"Pastor-Satorras","year":"2015","journal-title":"Rev Mod Phys"},{"key":"2025071513061765600_cnaf018-B3","first-page":"167","author":"Newman"},{"key":"2025071513061765600_cnaf018-B4","first-page":"295","author":"Keeling"},{"key":"2025071513061765600_cnaf018-B5","author":"Danon"},{"key":"2025071513061765600_cnaf018-B6","first-page":"521","author":"Moreno"},{"key":"2025071513061765600_cnaf018-B7","first-page":"1:1","author":"Chakrabarti"},{"key":"2025071513061765600_cnaf018-B8","doi-asserted-by":"crossref","first-page":"3200","DOI":"10.1103\/PhysRevLett.86.3200","article-title":"Epidemic spreading in scale-free networks","volume":"86","author":"Pastor-Satorras","year":"2001","journal-title":"Phys Rev Lett"},{"key":"2025071513061765600_cnaf018-B9","doi-asserted-by":"crossref","first-page":"066112","DOI":"10.1103\/PhysRevE.64.066112","article-title":"Infection dynamics on scale-free networks","volume":"64","author":"May","year":"2001","journal-title":"Phys Rev E"},{"key":"2025071513061765600_cnaf018-B10","volume-title":"Epidemics and immunization in scale-free networks. 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