{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T12:03:27Z","timestamp":1781870607228,"version":"3.54.5"},"reference-count":62,"publisher":"Public Library of Science (PLoS)","issue":"5","license":[{"start":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T00:00:00Z","timestamp":1746662400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100018818","name":"National Research, Development and Innovation Office","doi-asserted-by":"publisher","award":["RRF-2.3.1-21-2022-00006"],"award-info":[{"award-number":["RRF-2.3.1-21-2022-00006"]}],"id":[{"id":"10.13039\/501100018818","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018818","name":"National Research, Development and Innovation Office","doi-asserted-by":"publisher","award":["OTKA PD-145902"],"award-info":[{"award-number":["OTKA PD-145902"]}],"id":[{"id":"10.13039\/501100018818","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018818","name":"National Research, Development and Innovation Office","doi-asserted-by":"publisher","award":["OTKA K-145934"],"award-info":[{"award-number":["OTKA K-145934"]}],"id":[{"id":"10.13039\/501100018818","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018818","name":"National Research, Development and Innovation Office","doi-asserted-by":"publisher","award":["OTKA FK-145931"],"award-info":[{"award-number":["OTKA FK-145931"]}],"id":[{"id":"10.13039\/501100018818","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015498","name":"Innov\u00e1ci\u00f3s \u00e9s Technol\u00f3giai Miniszt\u00e9rium","doi-asserted-by":"publisher","award":["\u00daNKP-23-4-II-PPKE-27"],"award-info":[{"award-number":["\u00daNKP-23-4-II-PPKE-27"]}],"id":[{"id":"10.13039\/501100015498","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012550","name":"Nemzeti Kutat\u00e1si, Fejleszt\u00e9si \u00e9s Innovaci\u00f3s Alap","doi-asserted-by":"publisher","award":["TKP2021-NKTA-66"],"award-info":[{"award-number":["TKP2021-NKTA-66"]}],"id":[{"id":"10.13039\/501100012550","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012550","name":"Nemzeti Kutat\u00e1si, Fejleszt\u00e9si \u00e9s Innovaci\u00f3s Alap","doi-asserted-by":"publisher","award":["TKP2021-NVA-26"],"award-info":[{"award-number":["TKP2021-NVA-26"]}],"id":[{"id":"10.13039\/501100012550","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003825","name":"Magyar Tudom\u00e1nyos Akad\u00e9mia","doi-asserted-by":"publisher","award":["POST-COVID2021-64"],"award-info":[{"award-number":["POST-COVID2021-64"]}],"id":[{"id":"10.13039\/501100003825","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Optimal intervention planning is a critical part of epidemiological control, which is difficult to attain in real life situations. Ordinary differential equation (ODE) models can be used to optimize control but the results can not be easily translated to interventions in highly complex real life environments. Agent-based methods on the other hand allow detailed modeling of the environment but optimization is precluded by the large number of parameters. Our goal was to combine the advantages of both approaches, i.e., to allow control optimization in complex environments. The epidemic control objectives are expressed as a time-dependent reference for the number of infected people. To track this reference, a model predictive controller (MPC) is designed with a compartmental ODE prediction model to compute the optimal level of stringency of interventions, which are later translated to specific actions such as mobility restriction, quarantine policy, masking rules, school closure. The effects of interventions on the transmission rate of the pathogen, and hence their stringency, are computed using PanSim, an agent-based epidemic simulator that contains a detailed model of the environment. The realism and practical applicability of the method is demonstrated by the wide range of discrete level measures that can be taken into account. Moreover, the change between measures applied during consecutive planning intervals is also minimized. We found that such a combined intervention planning strategy is able to efficiently control a COVID-19-like epidemic process, in terms of incidence, virulence, and infectiousness with surprisingly sparse (e.g. 21 day) intervention regimes. At the same time, the approach proved to be robust even in scenarios with significant model uncertainties, such as unknown transmission rate, uncertain time and probability constants. The high performance of the computation allows a large number of test cases to be run. The proposed computational framework can be reused for epidemic management of unexpected pandemic events and can be customized to the needs of any country.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013028","type":"journal-article","created":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T17:44:48Z","timestamp":1746726288000},"page":"e1013028","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Smart epidemic control: A hybrid model blending ODEs and agent-based simulations for optimal, real-world intervention planning"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4217-0935","authenticated-orcid":true,"given":"P\u00e9ter","family":"Polcz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4385-4204","authenticated-orcid":true,"given":"Istv\u00e1n Z.","family":"Reguly","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"K\u00e1lm\u00e1n","family":"Tornai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"J\u00e1nos","family":"Juh\u00e1sz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S\u00e1ndor","family":"Pongor","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Attila","family":"Csik\u00e1sz-Nagy","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00e1bor","family":"Szederk\u00e9nyi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,5,8]]},"reference":[{"issue":"1","key":"pcbi.1013028.ref001","doi-asserted-by":"crossref","DOI":"10.1093\/intqhc\/mzaa139","article-title":"International survey of COVID-19 management strategies","volume":"33","author":"R Tartaglia","year":"2021","journal-title":"Int J Qual Health Care"},{"key":"pcbi.1013028.ref002","doi-asserted-by":"crossref","first-page":"609440","DOI":"10.3389\/fmed.2021.609440","article-title":"Bergamo and Covid-19: How the Dark Can Turn to Light","volume":"8","author":"N Perico","year":"2021","journal-title":"Front Med (Lausanne)"},{"key":"pcbi.1013028.ref003","doi-asserted-by":"crossref","first-page":"1087580","DOI":"10.3389\/fpubh.2023.1087580","article-title":"Intensity and lag-time of non-pharmaceutical interventions on COVID-19 dynamics in German hospitals","volume":"11","author":"Y Montcho","year":"2023","journal-title":"Front Public Health"},{"issue":"4","key":"pcbi.1013028.ref004","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1111\/ecot.12284","article-title":"The sooner, the better: The economic impact of non\u2010pharmaceutical interventions during the early stage of the COVID\u201019 pandemic","volume":"29","author":"A Demirg\u00fc\u00e7\u2010Kunt","year":"2021","journal-title":"Econ of Transit and Inst Chang"},{"issue":"1","key":"pcbi.1013028.ref005","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1009693","article-title":"Microsimulation based quantitative analysis of COVID-19 management strategies","volume":"18","author":"IZ Reguly","year":"2022","journal-title":"PLoS Comput Biol"},{"issue":"13","key":"pcbi.1013028.ref006","doi-asserted-by":"crossref","first-page":"12639","DOI":"10.1007\/s11071-023-08489-5","article-title":"A stochastic agent-based model to evaluate COVID-19 transmission influenced by human mobility","volume":"111","author":"K Chen","year":"2023","journal-title":"Nonl Dyn"},{"key":"pcbi.1013028.ref007","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.plrev.2016.07.005","article-title":"Mathematical models to characterize early epidemic growth: A review","volume":"18","author":"G Chowell","year":"2016","journal-title":"Phys Life Rev"},{"issue":"1","key":"pcbi.1013028.ref008","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1186\/s40249-022-01001-y","article-title":"Compartmental structures used in modeling COVID-19: a scoping review","volume":"11","author":"L Kong","year":"2022","journal-title":"Infect Dis Poverty"},{"key":"pcbi.1013028.ref009","author":"L Cao","year":"2021"},{"issue":"1","key":"pcbi.1013028.ref010","doi-asserted-by":"crossref","first-page":"18339","DOI":"10.1038\/s41598-021-97077-x","article-title":"Plateaus, rebounds and the effects of individual behaviours in epidemics","volume":"11","author":"H Berestycki","year":"2021","journal-title":"Sci Rep"},{"key":"pcbi.1013028.ref011","doi-asserted-by":"crossref","DOI":"10.1017\/S0950268820000990","article-title":"Chaos theory applied to the outbreak of COVID-19: an ancillary approach to decision making in pandemic context","volume":"148","author":"S Mangiarotti","year":"2020","journal-title":"Epidemiol Infect"},{"key":"pcbi.1013028.ref012","doi-asserted-by":"crossref","first-page":"127092","DOI":"10.1016\/j.physa.2022.127092","article-title":"Community-distributed compartmental models","volume":"596","author":"G Hern\u00e1ndez","year":"2022","journal-title":"Phys A: Statist Mech Appl"},{"issue":"1","key":"pcbi.1013028.ref013","doi-asserted-by":"crossref","first-page":"15879","DOI":"10.1038\/s41598-022-18208-6","article-title":"Recursive state and parameter estimation of COVID-19 circulating variants dynamics","volume":"12","author":"DM Silva","year":"2022","journal-title":"Sci Rep"},{"issue":"3","key":"pcbi.1013028.ref014","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0264704","article-title":"Enhancing the prediction of hospitalization from a COVID-19 agent-based model: A Bayesian method for model parameter estimation","volume":"17","author":"E Hadley","year":"2022","journal-title":"PLoS One"},{"key":"pcbi.1013028.ref015","doi-asserted-by":"crossref","first-page":"41456","DOI":"10.1109\/ACCESS.2021.3064371","article-title":"Assessing the Effectiveness of Isolation and Contact-Tracing Interventions for Early Transmission Dynamics of COVID-19 in South Korea","volume":"9","author":"H Ryu","year":"2021","journal-title":"IEEE Access"},{"issue":"10","key":"pcbi.1013028.ref016","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2021.e08143","article-title":"Application of machine learning in the prediction of COVID-19 daily new cases: A scoping review","volume":"7","author":"S Ghafouri-Fard","year":"2021","journal-title":"Heliyon"},{"key":"pcbi.1013028.ref017","doi-asserted-by":"crossref","first-page":"110059","DOI":"10.1016\/j.chaos.2020.110059","article-title":"Applications of machine learning and artificial intelligence for Covid-19 (SARS-CoV-2) pandemic: A review","volume":"139","author":"S Lalmuanawma","year":"2020","journal-title":"Chaos Solitons Fractals"},{"issue":"1","key":"pcbi.1013028.ref018","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1007\/s41666-020-00088-y","article-title":"ALeRT-COVID: Attentive Lockdown-awaRe Transfer Learning for Predicting COVID-19 Pandemics in Different Countries","volume":"5","author":"Y Li","year":"2021","journal-title":"J Healthc Inform Res"},{"issue":"9","key":"pcbi.1013028.ref019","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1007\/s11538-020-00795-y","article-title":"Optimal control of the COVID-19 pandemic with non-pharmaceutical Interventions","volume":"82","author":"TA Perkins","year":"2020","journal-title":"Bull Math Biol"},{"issue":"5","key":"pcbi.1013028.ref020","doi-asserted-by":"crossref","first-page":"2295","DOI":"10.1007\/s40435-022-01112-2","article-title":"Optimal control of the coronavirus pandemic with both pharmaceutical and non-pharmaceutical interventions","volume":"11","author":"SI Oke","year":"2023","journal-title":"Int J Dyn Control"},{"key":"pcbi.1013028.ref021","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1016\/j.matcom.2023.08.005","article-title":"Dynamic analysis and optimal control of a stochastic COVID-19 model","volume":"215","author":"G Zhang","year":"2024","journal-title":"Mathematics and Computers in Simulation"},{"key":"pcbi.1013028.ref022","doi-asserted-by":"crossref","unstructured":"K\u00f6hler J, Schwenkel L, Koch A, Berberich J, Pauli P, Allg\u00f6wer F. Robust and optimal predictive control of the COVID-19 outbreak; 2020.","DOI":"10.1016\/j.arcontrol.2020.11.002"},{"issue":"4","key":"pcbi.1013028.ref023","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1007\/s11071-020-05980-1","article-title":"Nonlinear model predictive control with logic constraints for COVID-19 management","volume":"102","author":"T P\u00e9ni","year":"2020","journal-title":"Nonlinear Dyn"},{"key":"pcbi.1013028.ref024","doi-asserted-by":"crossref","first-page":"84934","DOI":"10.1109\/ACCESS.2022.3197587","article-title":"Optimizing symptom based testing strategies for pandemic mitigation","volume":"10","author":"T Peni","year":"2022","journal-title":"IEEE Access"},{"issue":"10","key":"pcbi.1013028.ref025","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1009518","article-title":"Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing","volume":"17","author":"E Howerton","year":"2021","journal-title":"PLoS Comput Biol"},{"issue":"3","key":"pcbi.1013028.ref026","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1103\/RevModPhys.87.925","article-title":"Epidemic processes in complex networks","volume":"87","author":"R Pastor-Satorras","year":"2015","journal-title":"Rev Mod Phys"},{"key":"pcbi.1013028.ref027","doi-asserted-by":"crossref","first-page":"107525","DOI":"10.1016\/j.cmpb.2023.107525","article-title":"A survey on agents applications in healthcare: Opportunities, challenges and trends","volume":"236","author":"E Sulis","year":"2023","journal-title":"Comput Methods Programs Biomed"},{"key":"pcbi.1013028.ref028","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1109\/LCSYS.2021.3085700","article-title":"Challenges and future directions in pandemic control","volume":"6","author":"T Alamo","year":"2022","journal-title":"IEEE Control Syst Lett"},{"issue":"23","key":"pcbi.1013028.ref029","article-title":"Control of COVID-19 Outbreaks under Stochastic Community Dynamics, Bimodality, or Limited Vaccination","volume":"9","author":"B Goldenbogen","year":"2022","journal-title":"Adv Sci (Weinh)"},{"issue":"1","key":"pcbi.1013028.ref030","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1038\/s41746-021-00451-2","article-title":"Measuring the effect of Non-Pharmaceutical Interventions (NPIs) on mobility during the COVID-19 pandemic using global mobility data","volume":"4","author":"BT Snoeijer","year":"2021","journal-title":"NPJ Digit Med"},{"issue":"3","key":"pcbi.1013028.ref031","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1008633","article-title":"Testing, tracing and isolation in compartmental models","volume":"17","author":"S Sturniolo","year":"2021","journal-title":"PLoS Comput Biol"},{"issue":"10","key":"pcbi.1013028.ref032","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1008388","article-title":"A model-based evaluation of the efficacy of COVID-19 social distancing, testing and hospital triage policies","volume":"16","author":"A McCombs","year":"2020","journal-title":"PLoS Comput Biol"},{"key":"pcbi.1013028.ref033","doi-asserted-by":"crossref","first-page":"100764","DOI":"10.1016\/j.epidem.2024.100764","article-title":"Estimating the impact of test-trace-isolate-quarantine systems on SARS-CoV-2 transmission in Australia","volume":"47","author":"FM Shearer","year":"2024","journal-title":"Epidemics"},{"issue":"1","key":"pcbi.1013028.ref034","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1038\/s41746-021-00422-7","article-title":"Modeling the effect of exposure notification and non-pharmaceutical interventions on COVID-19 transmission in Washington state","volume":"4","author":"M Abueg","year":"2021","journal-title":"NPJ Digit Med"},{"issue":"7","key":"pcbi.1013028.ref035","article-title":"Covasim: An agent-based model of COVID-19 dynamics and interventions","volume":"17","author":"CC Kerr","year":"2021","journal-title":"PLoS Comput Biol"},{"issue":"7","key":"pcbi.1013028.ref036","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1009146","article-title":"OpenABM-Covid19-An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing","volume":"17","author":"R Hinch","year":"2021","journal-title":"PLoS Comput Biol"},{"key":"pcbi.1013028.ref037","doi-asserted-by":"crossref","first-page":"106012","DOI":"10.1016\/j.conengprac.2024.106012","article-title":"Agent-based model predictive control of soil\u2013crop irrigation with topographical information","volume":"150","author":"J Lopez-Jimenez","year":"2024","journal-title":"Control Engineering Practice"},{"key":"pcbi.1013028.ref038","author":"IZ Reguly","year":"2021"},{"issue":"10","key":"pcbi.1013028.ref039","article-title":"Efficient Bayesian inference for stochastic agent-based models","volume":"18","author":"ACS J\u00f8rgensen","year":"2022","journal-title":"PLoS Comput Biol"},{"issue":"4","key":"pcbi.1013028.ref040","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1010424","article-title":"Fusing an agent-based model of mosquito population dynamics with a statistical reconstruction of spatio-temporal abundance patterns","volume":"19","author":"SM Cavany","year":"2023","journal-title":"PLoS Comput Biol"},{"issue":"2","key":"pcbi.1013028.ref041","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0263150","article-title":"Using machine learning as a surrogate model for agent-based simulations","volume":"17","author":"C Angione","year":"2022","journal-title":"PLoS One"},{"issue":"1","key":"pcbi.1013028.ref042","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1007\/s11538-016-0225-6","article-title":"Optimization and control of agent-based models in biology: a perspective","volume":"79","author":"G An","year":"2017","journal-title":"Bull Math Biol"},{"key":"pcbi.1013028.ref043","doi-asserted-by":"crossref","first-page":"134052","DOI":"10.1016\/j.physd.2024.134052","article-title":"Koopman-based surrogate models for multi-objective optimization of agent-based systems","volume":"460","author":"J-H Niemann","year":"2024","journal-title":"Phys D: Nonl Phenomena"},{"key":"pcbi.1013028.ref044","doi-asserted-by":"crossref","first-page":"102242","DOI":"10.1016\/j.jocs.2024.102242","article-title":"Multilevel optimization for policy design with agent-based epidemic models","volume":"77","author":"J-H Niemann","year":"2024","journal-title":"J Comput Sci"},{"issue":"1","key":"pcbi.1013028.ref045","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1012138","article-title":"Optimal control of agent-based models via surrogate modeling","volume":"21","author":"LL Fonseca","year":"2025","journal-title":"PLoS Comput Biol"},{"issue":"1","key":"pcbi.1013028.ref046","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/0025-5564(87)90035-6","article-title":"Recasting nonlinear differential equations as S-systems: a canonical nonlinear form","volume":"87","author":"MA Savageau","year":"1987","journal-title":"Math Biosci"},{"issue":"1","key":"pcbi.1013028.ref047","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1038\/s41746-023-00927-3","article-title":"Harnessing the power of synthetic data in healthcare: innovation, application, and privacy","volume":"6","author":"M Giuffr\u00e8","year":"2023","journal-title":"NPJ Digit Med"},{"key":"pcbi.1013028.ref048","doi-asserted-by":"crossref","first-page":"120098","DOI":"10.1016\/j.watres.2023.120098","article-title":"Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants","volume":"241","author":"P Polcz","year":"2023","journal-title":"Water Res"},{"key":"pcbi.1013028.ref049","doi-asserted-by":"crossref","unstructured":"Csutak B, Polcz P, Szederkenyi G. Computation of COVID-19 epidemiological data in Hungary using dynamic model inversion. In: 2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI). 2021:91\u20136. doi: 10.1109\/saci51354.2021.9465563","DOI":"10.1109\/SACI51354.2021.9465563"},{"key":"pcbi.1013028.ref050","doi-asserted-by":"crossref","unstructured":"Csutak B, Polcz P, Szederk\u00e9nyi G. Model-based epidemic data reconstruction using feedback linearization. In: 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET). 2022. 1\u20136.","DOI":"10.1109\/ICECET55527.2022.9873061"},{"issue":"3","key":"pcbi.1013028.ref051","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.3390\/app12031113","article-title":"Reconstruction of epidemiological data in hungary using stochastic model predictive control","volume":"12","author":"P Polcz","year":"2022","journal-title":"Appl Sci"},{"issue":"5","key":"pcbi.1013028.ref052","doi-asserted-by":"crossref","DOI":"10.1136\/bmjopen-2020-042354","article-title":"Relative infectiousness of asymptomatic SARS-CoV-2 infected persons compared with symptomatic individuals: a rapid scoping review","volume":"11","author":"D McEvoy","year":"2021","journal-title":"BMJ Open"},{"key":"pcbi.1013028.ref053","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.ijid.2021.02.065","article-title":"Transmissibility of asymptomatic COVID-19: Data from Japanese clusters","volume":"105","author":"K Nakajo","year":"2021","journal-title":"Int J Infect Dis"},{"key":"pcbi.1013028.ref054","doi-asserted-by":"crossref","unstructured":"Horv\u00e1th G, Szederk\u00e9nyi G, Reguly IZ. Quantifying and comparing the impact of combinations of non-pharmaceutical interventions on the spread of COVID-19. In: 2023 31st Mediterranean Conference on Control and Automation (MED). IEEE; 2023.","DOI":"10.1109\/MED59994.2023.10185817"},{"key":"pcbi.1013028.ref055","doi-asserted-by":"crossref","unstructured":"Keomley-Horvath B, Horvath G, Polcz P, Siklosi B, Tornai K, Juhasz J. The design and utilisation of pansim, a portable pandemic simulator. In: 2022 First Combined International Workshop on Interactive Urgent Supercomputing (CIW-IUS). IEEE. 2022.","DOI":"10.1109\/CIW-IUS56691.2022.00006"},{"issue":"7858","key":"pcbi.1013028.ref056","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1038\/s41586-021-03470-x","article-title":"Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England","volume":"593","author":"E Volz","year":"2021","journal-title":"Nature"},{"key":"pcbi.1013028.ref057","author":"FP Lyngse","year":"2021"},{"key":"pcbi.1013028.ref058","first-page":"100592","article-title":"Epidemiological characteristics and transmission dynamics of the outbreak caused by the SARS-CoV-2 Omicron variant in Shanghai, China: A descriptive study","volume":"29","author":"Z Chen","year":"2022","journal-title":"Lancet Reg Health West Pac"},{"issue":"4","key":"pcbi.1013028.ref059","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1016\/j.jinf.2022.07.006","article-title":"Fighting Omicron epidemic in China: Real-world big data from Fangcang shelter hospital during the outbreak in Shanghai 2022","volume":"85","author":"L Ye","year":"2022","journal-title":"J Infect"},{"key":"pcbi.1013028.ref060","unstructured":"European Centre for Disease Prevention and Control. 2021. Contact tracing: public health management of persons, including healthcare workers, who have had contact with COVID-19 cases in the European Union \u2013 third update. https:\/\/www.ecdc.europa.eu\/sites\/default\/files\/documents\/covid-19-contact-tracing-public-health-management-third-update.pdf"},{"issue":"4","key":"pcbi.1013028.ref061","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1017\/S0022050722000407","article-title":"Pandemics depress the economy, public health interventions do not: evidence from the 1918 flu","volume":"82","author":"S Correia","year":"2022","journal-title":"J Econ Hist"},{"issue":"1","key":"pcbi.1013028.ref062","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1186\/s12889-022-13788-4","article-title":"Socio-economic analysis of short-term trends of COVID-19: modeling and data analytics","volume":"22","author":"M El Jai","year":"2022","journal-title":"BMC Public Health"}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013028","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T17:45:04Z","timestamp":1746726304000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013028"}},"subtitle":[],"editor":[{"given":"Alejandro Fern\u00e1ndez","family":"Villaverde","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2025,5,8]]},"references-count":62,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,5,8]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1013028","relation":{},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,8]]}}}