{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T00:48:40Z","timestamp":1783039720043,"version":"3.54.6"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,5,15]],"date-time":"2021-05-15T00:00:00Z","timestamp":1621036800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,5,15]],"date-time":"2021-05-15T00:00:00Z","timestamp":1621036800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"National Institute Of Allergy And Infectious Diseases of the National Institutes of Health","award":["R01AI127236"],"award-info":[{"award-number":["R01AI127236"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Health Care Manag Sci"],"published-print":{"date-parts":[[2021,9]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Agent-based network modeling (ABNM) simulates each person at the individual-level as agents of the simulation, and uses network generation algorithms to generate the network of contacts between individuals. ABNM are suitable for simulating individual-level dynamics of infectious diseases, especially for diseases such as HIV that spread through close contacts within intricate contact networks. However, as ABNM simulates a scaled-version of the full population, consisting of all infected and susceptible persons, they are computationally infeasible for studying certain questions in low prevalence diseases such as HIV. We present a new simulation technique, agent-based <jats:italic>evolving<\/jats:italic> network modeling (ABENM), which includes a new network generation algorithm, Evolving Contact Network Algorithm (ECNA), for generating scale-free networks. ABENM simulates only infected persons and their immediate contacts at the individual-level as agents of the simulation, and uses the ECNA for generating the contact structures between these individuals. All other susceptible persons are modeled using a compartmental modeling structure. Thus, ABENM has a hybrid agent-based and compartmental modeling structure. The ECNA uses concepts from graph theory for generating scale-free networks. Multiple social networks, including sexual partnership networks and needle sharing networks among injecting drug-users, are known to follow a scale-free network structure. Numerical results comparing ABENM with ABNM estimations for disease trajectories of hypothetical diseases transmitted on scale-free contact networks are promising for application to low prevalence diseases.<\/jats:p>","DOI":"10.1007\/s10729-021-09558-0","type":"journal-article","created":{"date-parts":[[2021,5,15]],"date-time":"2021-05-15T09:02:32Z","timestamp":1621069352000},"page":"623-639","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Agent-based evolving network modeling: a new simulation method for modeling low prevalence infectious diseases"],"prefix":"10.1007","volume":"24","author":[{"given":"Matthew","family":"Eden","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca","family":"Castonguay","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Buyannemekh","family":"Munkhbat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hari","family":"Balasubramanian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8384-6041","authenticated-orcid":false,"given":"Chaitra","family":"Gopalappa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,5,15]]},"reference":[{"key":"9558_CR1","doi-asserted-by":"publisher","first-page":"295","DOI":"10.4161\/viru.24041","volume":"4","author":"CI Siettos","year":"2013","unstructured":"Siettos CI, Russo L (2013) Mathematical modeling of infectious disease dynamics. Virulence 4:295\u2013306","journal-title":"Virulence"},{"key":"9558_CR2","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1186\/1742-4682-6-11","volume":"6","author":"T Smieszek","year":"2009","unstructured":"Smieszek T, Fiebig L, Scholz RW (2009) Models of epidemics: when contact repetition and clustering should be included. Theor Biol Med Model 6:11\u20134682 -6-11","journal-title":"Theor Biol Med Model"},{"key":"9558_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1742-5573-9-1","volume":"9","author":"AM El-Sayed","year":"2012","unstructured":"El-Sayed AM, Scarborough P, Seemann L, Galea S (2012) Social network analysis and agent-based modeling in social epidemiology. Epidemiol Perspect Innov 9:1\u20135573 -9-1","journal-title":"Epidemiol Perspect Innov"},{"key":"9558_CR4","unstructured":"Centers for Disease Control and Prevention. Estimated HIV incidence and prevalence in the United States, 2010\u20132015. HIV Surveillance Supplemental Report 2018;23(No. 1). http:\/\/www.cdc.gov\/hiv\/library\/reports\/hiv-surveillance.html. Published March 2018. Accessed [November 2018]"},{"key":"9558_CR5","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1097\/QAI.0000000000001856","volume":"79","author":"AM Oster","year":"2018","unstructured":"Oster AM, France AM, Panneer N, Banez Ocfemia MC, Campbell E, Dasgupta S et al (2018) Identifying clusters of recent and rapid HIV transmission through analysis of molecular surveillance data. J Acquir Immune Defic Syndr 79:543\u2013550","journal-title":"J Acquir Immune Defic Syndr"},{"key":"9558_CR6","doi-asserted-by":"publisher","first-page":"e98272","DOI":"10.1371\/journal.pone.0098272","volume":"9","author":"AW McCormick","year":"2014","unstructured":"McCormick AW, Abuelezam NN, Rhode ER, Hou T, Walensky RP, Pei PP et al (2014) Development, calibration and performance of an HIV transmission model incorporating natural history and behavioral patterns: application in South Africa. PLoS One 9:e98272","journal-title":"PLoS One"},{"key":"9558_CR7","doi-asserted-by":"crossref","unstructured":"Reniers G, Armbruster B, Lucas A (2015) Sexual networks, partnership mixing, and the female-to-male ratio of HIV infections in generalized epidemics: An agent-based simulation study. Demogr Res 33(15):425\u2013450","DOI":"10.4054\/DemRes.2015.33.15"},{"key":"9558_CR8","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1016\/0025-5564(95)00093-3","volume":"133","author":"M Kretzschmar","year":"1996","unstructured":"Kretzschmar M, Morris M (1996) Measures of concurrency in networks and the spread of infectious disease. Math Biosci 133:165\u2013195","journal-title":"Math Biosci"},{"key":"9558_CR9","doi-asserted-by":"publisher","unstructured":"Johnson LF, Kubjane M, Moolla H (2018) MicroCOSM: a model of social and structural drivers of HIV and interventions to reduce HIV incidence in high-risk populations in South Africa. bioRxiv 310763.\u00a0https:\/\/doi.org\/10.1101\/310763","DOI":"10.1101\/310763"},{"key":"9558_CR10","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1007\/s10479-009-0571-y","volume":"178","author":"IT Vieira","year":"2010","unstructured":"Vieira IT, Cheng RCH, Harper PR, de Senna V (2010) Small world network models of the dynamics of HIV infection. Ann Oper Res 178:173\u2013200","journal-title":"Ann Oper Res"},{"key":"9558_CR11","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1177\/0272989X16668509","volume":"37","author":"C Gopalappa","year":"2017","unstructured":"Gopalappa C, Farnham PG, Chen YH, Sansom SL (2017) Progression and transmission of HIV\/AIDS (PATH 2.0): a new agent-based model to estimate HIV transmissions in the United States. Med Decis Mak 37:224\u2013233","journal-title":"Med Decis Mak"},{"key":"9558_CR12","doi-asserted-by":"publisher","first-page":"e58","DOI":"10.2196\/publichealth.9357","volume":"4","author":"W Luo","year":"2018","unstructured":"Luo W, Katz DA, Hamilton DT, McKenney J, Jenness SM, Goodreau SM, Stekler JD, Rosenberg ES, Sullivan PS, Cassels S (2018) Development of an agent-based model to investigate the impact of HIV self-testing programs on men who have sex with men in Atlanta and Seattle. JMIR Public Health Surveill 4:e58","journal-title":"JMIR Public Health Surveill"},{"key":"9558_CR13","doi-asserted-by":"publisher","first-page":"3200","DOI":"10.1103\/PhysRevLett.86.3200","volume":"86","author":"R Pastor-Satorras","year":"2001","unstructured":"Pastor-Satorras R, Vespignani A (2001) Epidemic spreading in scale-free networks. Phys Rev Lett 86:3200\u20133203","journal-title":"Phys Rev Lett"},{"key":"9558_CR14","doi-asserted-by":"publisher","first-page":"1852","DOI":"10.1093\/bioinformatics\/bty921","volume":"35","author":"N Moshiri","year":"2019","unstructured":"Moshiri N, Ragonnet-Cronin M, Wertheim JO, Mirarab S (2019) FAVITES: simultaneous simulation of transmission networks, phylogenetic trees and sequences. Bioinformatics 35:1852\u20131861","journal-title":"Bioinformatics"},{"key":"9558_CR15","doi-asserted-by":"publisher","first-page":"19289","DOI":"10.1038\/s41598-019-55689-4","volume":"9","author":"J Liesenborgs","year":"2019","unstructured":"Liesenborgs J, Hendrickx DM, Kuylen E, Niyukuri D, Hens N, Delva W (2019) SimpactCyan 1.0: An Open-source Simulator for Individual-Based Models in HIV Epidemiology with R and Python Interfaces. Sci Rep 9:19289\u201319019 55689-4","journal-title":"Sci Rep"},{"key":"9558_CR16","doi-asserted-by":"publisher","first-page":"128701","DOI":"10.1103\/PhysRevLett.88.128701","volume":"88","author":"J Davidsen","year":"2002","unstructured":"Davidsen J, Ebel H, Bornholdt S (2002) Emergence of a small world from local interactions: modeling acquaintance networks. Phys Rev Lett 88:128701","journal-title":"Phys Rev Lett"},{"key":"9558_CR17","doi-asserted-by":"publisher","first-page":"1439","DOI":"10.1073\/pnas.0305684101","volume":"101","author":"M Marsili","year":"2004","unstructured":"Marsili M, Vega-Redondo F, Slanina F (2004) The rise and fall of a networked society: a formal model. Proc Natl Acad Sci U S A 101:1439\u20131442","journal-title":"Proc Natl Acad Sci U S A"},{"key":"9558_CR18","doi-asserted-by":"publisher","first-page":"228701","DOI":"10.1103\/PhysRevLett.99.228701","volume":"99","author":"JM Kumpula","year":"2007","unstructured":"Kumpula JM, Onnela JP, Saramaki J, Kaski K, Kertesz J (2007) Emergence of communities in weighted networks. Phys Rev Lett 99:228701","journal-title":"Phys Rev Lett"},{"key":"9558_CR19","doi-asserted-by":"publisher","first-page":"056104","DOI":"10.1103\/PhysRevE.67.056104","volume":"67","author":"A Vazquez","year":"2003","unstructured":"Vazquez A (2003) Growing network with local rules: preferential attachment, clustering hierarchy, and degree correlations. Phys Rev E Stat Nonlinear Soft Matter Phys 67:056104","journal-title":"Phys Rev E Stat Nonlinear Soft Matter Phys"},{"key":"9558_CR20","doi-asserted-by":"publisher","first-page":"056122","DOI":"10.1103\/PhysRevE.70.056122","volume":"70","author":"M Boguna","year":"2004","unstructured":"Boguna M, Pastor-Satorras R, Diaz-Guilera A, Arenas A (2004) Models of social networks based on social distance attachment. Phys Rev E Stat Nonlinear Soft Matter Phys 70:056122","journal-title":"Phys Rev E Stat Nonlinear Soft Matter Phys"},{"key":"9558_CR21","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1016\/j.socnet.2006.08.002","volume":"29","author":"G Robins","year":"2007","unstructured":"Robins G, Pattison P, Kalish Y, Lusher D (2007) An introduction to exponential random graph (p*) models for social networks. Soc Networks 29:173\u2013191","journal-title":"Soc Networks"},{"key":"9558_CR22","doi-asserted-by":"publisher","unstructured":"Schmid CS, Desmarais BA (2017) Exponential random graph models with big networks: Maximum pseudolikelihood estimation and the parametric bootstrap. In: Nie J-Y, Obradovic Z, Suzumura T, Ghosh R, Nambiar R, Wang C, Zang H, Baeza-Yates R, Baeza-Yates R, Hu X, Kepner J, Cuzzocrea A, Tang J, Toyoda M (eds) Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. Institute of Electrical and Electronics Engineers Inc,\u00a0p 116\u2013121.\u00a0https:\/\/doi.org\/10.1109\/BigData.2017.8257919","DOI":"10.1109\/BigData.2017.8257919"},{"key":"9558_CR23","unstructured":"Barabasi AL (2021) Nework Science- Chapter 4, The Scale-free Property. http:\/\/networksciencebook.com. Accessed March 2021"},{"key":"9558_CR24","doi-asserted-by":"publisher","first-page":"907","DOI":"10.1038\/35082140","volume":"411","author":"F Liljeros","year":"2001","unstructured":"Liljeros F, Edling CR, Amaral LA, Stanley HE, Aberg Y (2001) The web of human sexual contacts. Nature 411:907\u2013908","journal-title":"Nature"},{"key":"9558_CR25","doi-asserted-by":"publisher","first-page":"e1006000","DOI":"10.1371\/journal.ppat.1006000","volume":"13","author":"JO Wertheim","year":"2017","unstructured":"Wertheim JO, Kosakovsky Pond SL, Forgione LA, Mehta SR, Murrell B, Shah S, Smith DM, Scheffler K, Torian LV (2017) Social and genetic networks of HIV-1 transmission in New York City. PLoS Pathog 13:e1006000","journal-title":"PLoS Pathog"},{"key":"9558_CR26","doi-asserted-by":"publisher","first-page":"304","DOI":"10.1093\/infdis\/jit524","volume":"209","author":"JO Wertheim","year":"2014","unstructured":"Wertheim JO, Leigh Brown AJ, Hepler NL, Mehta SR, Richman DD, Smith DM, Kosakovsky Pond SL (2014) The global transmission network of HIV-1. J Infect Dis 209:304\u2013313","journal-title":"J Infect Dis"},{"key":"9558_CR27","doi-asserted-by":"crossref","unstructured":"Brown AJL, Lycett SJ, Weinert L, Hughes GJ, Fearnhill E, Dunn DT (2011) Transmission network parameters estimated from HIV sequences for a Nationwide epidemic. J Infect Dis 204","DOI":"10.1093\/infdis\/jir550"},{"key":"9558_CR28","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1126\/science.286.5439.509","volume":"286","author":"AL Barabasi","year":"1999","unstructured":"Barabasi AL, Albert R (1999) Emergence of scaling in random networks. Science 286:509\u2013512","journal-title":"Science"},{"key":"9558_CR29","doi-asserted-by":"crossref","unstructured":"Fotouhi B, Rabbat MG (2013) Degree correlation in scale-free graphs. Eur\u00a0Phys J B 86(510)","DOI":"10.1140\/epjb\/e2013-40920-6"},{"key":"9558_CR30","first-page":"2020","volume":"6-10","author":"AM France","year":"2020","unstructured":"France AM, Gopalappa C, Singh S, Chen Y, Oster AM, Bingham A et al (2020) Poster # PEC0522 - nationally representative simulation model of HIV transmission clusters in the United States, e-poster track C. AIDS 6-10:2020","journal-title":"AIDS"},{"key":"9558_CR31","doi-asserted-by":"publisher","unstructured":"Singh S, France AM, Chen Y, Farnham P, Oster A, Goplappa C (2021) Progression and transmission of HIV (PATH 4.0)-A new agent-based evolving network simulation for modeling HIV transmission clusters. Math\u00a0Biosci Eng 18(3):2150\u20132181. https:\/\/doi.org\/10.3934\/mbe.2021109","DOI":"10.3934\/mbe.2021109"},{"key":"9558_CR32","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1038\/30918","volume":"393","author":"DJ Watts","year":"1998","unstructured":"Watts DJ, Strogatz SH (1998) Collective dynamics of \u2018small-world\u2019 networks. Nature 393:440\u2013442","journal-title":"Nature"}],"container-title":["Health Care Management Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10729-021-09558-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10729-021-09558-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10729-021-09558-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T10:02:10Z","timestamp":1650880930000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10729-021-09558-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,15]]},"references-count":32,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,9]]}},"alternative-id":["9558"],"URL":"https:\/\/doi.org\/10.1007\/s10729-021-09558-0","relation":{},"ISSN":["1386-9620","1572-9389"],"issn-type":[{"value":"1386-9620","type":"print"},{"value":"1572-9389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,15]]},"assertion":[{"value":"8 December 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 February 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 May 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}