{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T21:18:27Z","timestamp":1757625507923,"version":"3.44.0"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T00:00:00Z","timestamp":1756166400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T00:00:00Z","timestamp":1756166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["101092749"],"award-info":[{"award-number":["101092749"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100031478","name":"NextGenerationEU","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100031478","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011033","name":"Agencia Estatal de Investigaci\u00f3n","doi-asserted-by":"publisher","award":["FJC2021-046655-I"],"award-info":[{"award-number":["FJC2021-046655-I"]}],"id":[{"id":"10.13039\/501100011033","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004837","name":"Ministerio de Ciencia e Innovaci\u00f3n","doi-asserted-by":"publisher","award":["PID2021-128005NB-C21"],"award-info":[{"award-number":["PID2021-128005NB-C21"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100011661","name":"Pacific Northwest National Laboratory","doi-asserted-by":"publisher","award":["DE-AC05-76RL01830"],"award-info":[{"award-number":["DE-AC05-76RL01830"]}],"id":[{"id":"10.13039\/100011661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-17218-4","type":"journal-article","created":{"date-parts":[[2025,8,26]],"date-time":"2025-08-26T19:44:59Z","timestamp":1756237499000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessing the impact of interregional mobility on COVID19 spread in Spain using transfer entropy"],"prefix":"10.1038","volume":"15","author":[{"given":"Miguel","family":"Ponce-de-Leon","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Camila","family":"Pontes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alex","family":"Arenas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alfonso","family":"Valencia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,26]]},"reference":[{"key":"17218_CR1","doi-asserted-by":"crossref","unstructured":"Pascal P. K., et al. Enhancing global preparedness during an ongoing pandemic from partial and noisy data. PNAS Nexus, 2(6), pgad192, (2023).","DOI":"10.1093\/pnasnexus\/pgad192"},{"issue":"23","key":"17218_CR2","doi-asserted-by":"publisher","first-page":"eabc0764","DOI":"10.1126\/sciadv.abc0764","volume":"6","author":"N Oliver","year":"2020","unstructured":"Oliver, N. et al. Mobile phone data for informing public health actions across the COVID-19 pandemic life cycle. Sci. Adv. 6(23), eabc0764 (2020).","journal-title":"Sci. Adv."},{"key":"17218_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.physrep.2021.02.001","volume":"913","author":"N Perra","year":"2021","unstructured":"Perra, N. Non-pharmaceutical interventions during the COVID-19 pandemic: A review. Phys. Rep. 913, 1\u201352 (2021).","journal-title":"Phys. Rep."},{"issue":"1","key":"17218_CR4","doi-asserted-by":"publisher","first-page":"9132","DOI":"10.1038\/s41598-022-11531-y","volume":"12","author":"M Smith","year":"2022","unstructured":"Smith, M, Ponce-de-Leon, M & Valencia, Al. Evaluating the policy of closing bars and restaurants in Catalu\u00f1a and its effects on mobility and COVID19 incidence. Sci. Rep. 12(1), 9132 (2022).","journal-title":"Sci. Rep."},{"issue":"10231","key":"17218_CR5","doi-asserted-by":"publisher","first-page":"1193","DOI":"10.1016\/S0140-6736(20)30753-4","volume":"395","author":"O Mitj\u00e0","year":"2020","unstructured":"Mitj\u00e0, O. et al. Experts\u2019 request to the Spanish Government: Move Spain towards complete lockdown. The Lancet 395(10231), 1193\u20131194 (2020).","journal-title":"The Lancet"},{"issue":"7196","key":"17218_CR6","doi-asserted-by":"publisher","first-page":"779","DOI":"10.1038\/nature06958","volume":"453","author":"MC Gonz\u00e1lez","year":"2008","unstructured":"Gonz\u00e1lez, M. C., Hidalgo, C. A. & Barab\u00e1si, A.-L. Understanding individual human mobility patterns. Nature 453(7196), 779\u2013782 (2008).","journal-title":"Nature"},{"issue":"5","key":"17218_CR7","doi-asserted-by":"publisher","first-page":"e37027","DOI":"10.1371\/journal.pone.0037027","volume":"7","author":"A Noulas","year":"2012","unstructured":"Noulas, A., Scellato, S., Lambiotte, R., Pontil, M. & Mascolo, C. A Tale of many cities: Universal patterns in human urban mobility. PLoS ONE 7(5), e37027 (2012).","journal-title":"PLoS ONE"},{"issue":"1","key":"17218_CR8","doi-asserted-by":"publisher","first-page":"5276","DOI":"10.1038\/srep05276","volume":"4","author":"T Louail","year":"2014","unstructured":"Louail, T. et al. From mobile phone data to the spatial structure of cities. Sci. Rep. 4(1), 5276 (2014).","journal-title":"Sci. Rep."},{"issue":"36","key":"17218_CR9","doi-asserted-by":"publisher","first-page":"15274","DOI":"10.1073\/pnas.0900282106","volume":"106","author":"N Eagle","year":"2009","unstructured":"Eagle, N., Pentland, A. S. & Lazer, D. Inferring friendship network structure by using mobile phone data. Proc. Natl. Acad. Sci. 106(36), 15274\u201315278 (2009).","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"45","key":"17218_CR10","doi-asserted-by":"publisher","first-page":"15888","DOI":"10.1073\/pnas.1408439111","volume":"111","author":"P Deville","year":"2014","unstructured":"Deville, P. et al. Dynamic population mapping using mobile phone data. Proc. Natl. Acad. Sci. 111(45), 15888\u201315893 (2014).","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"6264","key":"17218_CR11","doi-asserted-by":"publisher","first-page":"1073","DOI":"10.1126\/science.aac4420","volume":"350","author":"J Blumenstock","year":"2015","unstructured":"Blumenstock, J., Cadamuro, G. & On, R. Predicting poverty and wealth from mobile phone metadata. Science 350(6264), 1073\u20131076 (2015).","journal-title":"Science"},{"key":"17218_CR12","doi-asserted-by":"publisher","first-page":"101777","DOI":"10.1016\/j.compenvurbsys.2022.101777","volume":"94","author":"T Yabe","year":"2022","unstructured":"Yabe, T. et al. Mobile phone location data for disasters: A review from natural hazards and epidemics. Comput. Environ. Urban Syst. 94, 101777 (2022).","journal-title":"Comput. Environ. Urban Syst."},{"issue":"7","key":"17218_CR13","doi-asserted-by":"publisher","first-page":"e1003716","DOI":"10.1371\/journal.pcbi.1003716","volume":"10","author":"M Tizzoni","year":"2014","unstructured":"Tizzoni, M. et al. On the use of human mobility proxies for modeling epidemics. PLoS Comput. Biol. 10(7), e1003716 (2014).","journal-title":"PLoS Comput. Biol."},{"issue":"52","key":"17218_CR14","doi-asserted-by":"publisher","first-page":"32883","DOI":"10.1073\/pnas.2012326117","volume":"117","author":"F Schlosser","year":"2020","unstructured":"Schlosser, F. et al. Covid-19 lockdown induces disease-mitigating structural changes in mobility networks. Proc. Natl. Acad. Sci. 117(52), 32883\u201332890 (2020).","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"4","key":"17218_CR15","first-page":"041055","volume":"10","author":"A Arenas","year":"2020","unstructured":"Arenas, A. et al. Modeling the Spatiotemporal Epidemic Spreading of COVID-19 and the Impact of Mobility and Social Distancing Interventions. Phys. Rev. X 10(4), 041055 (2020).","journal-title":"Phys. Rev. X"},{"issue":"1","key":"17218_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41746-020-00374-4","volume":"4","author":"A Ferrari","year":"2021","unstructured":"Ferrari, A. et al. Simulating SARS-CoV-2 epidemics by region-specific variables and modeling contact tracing app containment. npj Digit. Med. 4(1), 1\u20138 (2021).","journal-title":"npj Digit. Med."},{"issue":"3","key":"17218_CR17","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.jocs.2010.07.002","volume":"1","author":"D Balcan","year":"2010","unstructured":"Balcan, D. et al. Modeling the spatial spread of infectious diseases: The GLobal Epidemic and Mobility computational model. J. Comput. Sci. 1(3), 132\u2013145 (2010).","journal-title":"J. Comput. Sci."},{"issue":"10","key":"17218_CR18","doi-asserted-by":"publisher","first-page":"e1009326","DOI":"10.1371\/journal.pcbi.1009326","volume":"17","author":"M Mazzoli","year":"2021","unstructured":"Mazzoli, M. et al. Interplay between mobility, multi-seeding and lockdowns shapes COVID-19 local impact. PLoS Comput. Biol. 17(10), e1009326 (2021).","journal-title":"PLoS Comput. Biol."},{"issue":"1","key":"17218_CR19","doi-asserted-by":"publisher","first-page":"4164","DOI":"10.1038\/s41467-024-48528-2","volume":"15","author":"AC Perofsky","year":"2024","unstructured":"Perofsky, A. C. et al. Impacts of human mobility on the citywide transmission dynamics of 18 respiratory viruses in pre- and post-COVID-19 pandemic years. Nat. Commun. 15(1), 4164 (2024).","journal-title":"Nat. Commun."},{"issue":"1","key":"17218_CR20","doi-asserted-by":"publisher","first-page":"4961","DOI":"10.1038\/s41467-020-18190-5","volume":"11","author":"KH Grantz","year":"2020","unstructured":"Grantz, K.\u00a0H. et al. The use of mobile phone data to inform analysis of COVID-19 pandemic epidemiology. Nat. Commun. 11(1), 4961 (2020).","journal-title":"Nat. Commun."},{"issue":"10","key":"17218_CR21","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1093\/pnasnexus\/pgad302","volume":"2","author":"F Delussu","year":"2023","unstructured":"Delussu, F., Tizzoni, M. & Gauvin, L. The limits of human mobility traces to predict the spread of covid-19: A transfer entropy approach. PNAS nexus 2(10), 302 (2023).","journal-title":"PNAS nexus"},{"issue":"6531","key":"17218_CR22","doi-asserted-by":"publisher","first-page":"eabd9338","DOI":"10.1126\/science.abd9338","volume":"371","author":"JM Brauner","year":"2021","unstructured":"Brauner, J. M. et al. Inferring the effectiveness of government interventions against COVID-19. Science 371(6531), eabd9338 (2021).","journal-title":"Science"},{"issue":"5","key":"17218_CR23","doi-asserted-by":"publisher","first-page":"827","DOI":"10.3390\/electronics9050827","volume":"9","author":"T Alamo","year":"2020","unstructured":"Alamo, T., Reina, D. G., Mammarella, M. & Abella, A. Covid-19: Open-Data Resources for Monitoring, Modeling, and Forecasting the Epidemic. Electronics 9(5), 827 (2020).","journal-title":"Electronics"},{"issue":"W1","key":"17218_CR24","doi-asserted-by":"publisher","first-page":"W619","DOI":"10.1093\/nar\/gkab417","volume":"49","author":"PW Harrison","year":"2021","unstructured":"Harrison, P.\u00a0W. et al. The COVID-19 Data Portal: Accelerating SARS-CoV-2 and COVID-19 research through rapid open access data sharing. Nucleic Acids Res. 49(W1), W619\u2013W623 (2021).","journal-title":"Nucleic Acids Res."},{"issue":"1","key":"17218_CR25","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1109\/TAI.2020.3020521","volume":"1","author":"S Latif","year":"2020","unstructured":"Latif, S. et al. Leveraging data science to combat COVID-19: A comprehensive review. IEEE Trans. Artif. Intell. 1(1), 85\u2013103 (2020).","journal-title":"IEEE Trans. Artif. Intell."},{"issue":"3","key":"17218_CR26","doi-asserted-by":"publisher","first-page":"1296","DOI":"10.1007\/s10489-020-01862-6","volume":"51","author":"J Shuja","year":"2021","unstructured":"Shuja, J., Alanazi, E., Alasmary, W. & Alashaikh, A. COVID-19 open source data sets: A comprehensive survey. Appl. Intell. 51(3), 1296\u20131325 (2021).","journal-title":"Appl. Intell."},{"issue":"1","key":"17218_CR27","first-page":"1","volume":"8","author":"MP-de Leon","year":"2021","unstructured":"Leon, Miguel P.-de et al. Covid-19 flow-maps an open geographic information system on covid-19 and human mobility for spain. Sci. data 8(1), 1\u201316 (2021).","journal-title":"Sci. data"},{"key":"17218_CR28","unstructured":"Judea, P. Causality. Cambridge University Press, Cambridge, 2 edition, 2009."},{"key":"17218_CR29","doi-asserted-by":"crossref","unstructured":"Alex,\u00a0E. Y. and Wenying, S.. Data-driven causal analysis of observational biological time series. eLife 11, e72518, (2022).","DOI":"10.7554\/eLife.72518"},{"key":"17218_CR30","doi-asserted-by":"crossref","unstructured":"Ashley,\u00a0R. C., Sarah K. H., Elaine, L., Daniel, M., and Joshua,\u00a0S. W. A Primer for Microbiome Time-Series Analysis. Frontiers in Genetics, 11, (2020).","DOI":"10.3389\/fgene.2020.00310"},{"issue":"1","key":"17218_CR31","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1146\/annurev-statistics-040120-010930","volume":"9","author":"A Shojaie","year":"2022","unstructured":"Shojaie, A. & Fox, E. B. Granger Causality: A Review and Recent Advances. Annu. Rev. Stat. Appl. 9(1), 289\u2013319 (2022).","journal-title":"Annu. Rev. Stat. Appl."},{"key":"17218_CR32","doi-asserted-by":"crossref","unstructured":"Clive,\u00a0W. J. G. Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society, pages 424\u2013438, (1969).","DOI":"10.2307\/1912791"},{"key":"17218_CR33","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/0165-1889(80)90069-X","volume":"2","author":"CWJ Granger","year":"1980","unstructured":"Granger, C. W. J. Testing for causality: A personal viewpoint. J. Econ. Dyn. Control 2, 329\u2013352 (1980).","journal-title":"J. Econ. Dyn. Control"},{"issue":"1","key":"17218_CR34","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1093\/ije\/dyp296","volume":"39","author":"Sa Galea","year":"2010","unstructured":"Galea, S., Riddle, M. & Kaplan, G.\u00a0A. Causal thinking and complex system approaches in epidemiology. Int. J. Epidemiol. 39(1), 97\u2013106 (2010).","journal-title":"Int. J. Epidemiol."},{"issue":"6106","key":"17218_CR35","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1126\/science.1227079","volume":"338","author":"G Sugihara","year":"2012","unstructured":"Sugihara, G. et al. etecting causality in complex ecosystems. Science 338(6106), 496\u2013500 (2012).","journal-title":"Science"},{"key":"17218_CR36","doi-asserted-by":"crossref","unstructured":"Daniel, H., Erik, L., Maik, S., & Klaus,\u00a0R. P. Topological Causality in Dynamical Systems. Phys. Rev. Lett. 119(9), 098301, (2017).","DOI":"10.1103\/PhysRevLett.119.098301"},{"issue":"1","key":"17218_CR37","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1007\/s10827-010-0262-3","volume":"30","author":"R Vicente","year":"2011","unstructured":"Vicente, R., Wibral, M., Lindner, M. & Pipa, G. Transfer entropy\u2014a model-free measure of effective connectivity for the neurosciences. J. Comput. Neurosci. 30(1), 45\u201367 (2011).","journal-title":"J. Comput. Neurosci."},{"issue":"2","key":"17218_CR38","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1103\/PhysRevLett.85.461","volume":"85","author":"T Schreiber","year":"2000","unstructured":"Schreiber, T. Measuring information transfer. Phys. Rev. Lett. 85(2), 461 (2000).","journal-title":"Phys. Rev. Lett."},{"issue":"23","key":"17218_CR39","doi-asserted-by":"publisher","first-page":"238701","DOI":"10.1103\/PhysRevLett.103.238701","volume":"103","author":"L Barnett","year":"2009","unstructured":"Barnett, L., Barrett, A. B. & Seth, A. K. Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables. Phys. Rev. Lett. 103(23), 238701 (2009).","journal-title":"Phys. Rev. Lett."},{"issue":"03","key":"17218_CR40","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1142\/S0218127407017628","volume":"17","author":"M Lungarella","year":"2007","unstructured":"Lungarella, M., Ishiguro, K., Kuniyoshi, Y. & Otsu, N. Methods for quantifying the causal structure of bivariate time series. Int. J. Bifurcation Chaos 17(03), 903\u2013921 (2007).","journal-title":"Int. J. Bifurcation Chaos"},{"key":"17218_CR41","doi-asserted-by":"crossref","unstructured":"Fatimah Abdul Razak and Henrik Jeldtoft Jensen. Quantifying \u2018Causality\u2019 in Complex Systems: Understanding Transfer Entropy. PLOS ONE, 9(6):e99462, June 2014.","DOI":"10.1371\/journal.pone.0099462"},{"issue":"10","key":"17218_CR42","doi-asserted-by":"publisher","first-page":"103123","DOI":"10.1063\/1.5047429","volume":"28","author":"M Porfiri","year":"2018","unstructured":"Porfiri, M. & Ruiz Mar\u00edn, M. Inference of time-varying networks through transfer entropy, the case of a Boolean network model. Chaos: An Interdisciplinary Journal of Nonlinear Science 28(10), 103123 (2018).","journal-title":"Chaos: An Interdisciplinary Journal of Nonlinear Science"},{"key":"17218_CR43","doi-asserted-by":"crossref","unstructured":"Thomas, D. & Franziska,\u00a0J. P. Using transfer entropy to measure information flows between financial markets. Stud. Nonlinear Dyn. Econom. 17(1), 85\u2013102 (2013).","DOI":"10.1515\/snde-2012-0044"},{"issue":"4","key":"17218_CR44","doi-asserted-by":"publisher","first-page":"e1501158","DOI":"10.1126\/sciadv.1501158","volume":"2","author":"J Borge-Holthoefer","year":"2016","unstructured":"Borge-Holthoefer, J. et al. The dynamics of information-driven coordination phenomena: A transfer entropy analysis. Sci. Adv. 2(4), e1501158 (2016).","journal-title":"Sci. Adv."},{"issue":"164","key":"17218_CR45","doi-asserted-by":"publisher","first-page":"20190628","DOI":"10.1098\/rsif.2019.0628","volume":"17","author":"SM Kissler","year":"2020","unstructured":"Kissler, S. M., Viboud, C., Grenfell, B. T. & Gog, J. R. Symbolic transfer entropy reveals the age structure of pandemic influenza transmission from high-volume influenza-like illness data. J. R. Soc. Interface 17(164), 20190628 (2020).","journal-title":"J. R. Soc. Interface"},{"key":"17218_CR46","doi-asserted-by":"publisher","unstructured":"[dataset], Miguel, P.-de L. et al. COVID19 Flow-Maps Daily Cases Dataset. Zenodo https:\/\/doi.org\/10.5281\/zenodo.4634868, (2021).","DOI":"10.5281\/zenodo.4634868"},{"key":"17218_CR47","doi-asserted-by":"publisher","unstructured":"[dataset], Miguel Ponce-de, L et al. COVID19 Flow-Maps Population Dataset (Maestra 2). Zenodo https:\/\/doi.org\/10.5281\/zenodo.4635258 (2021).","DOI":"10.5281\/zenodo.4635258"},{"key":"17218_CR48","unstructured":"[dataset], Miguel Ponce-de, L et al. COVID19 Flow-Maps Daily-Mobility Dataset (Maestra 1). Zenodo https:\/\/doi.org\/10.5281\/zenodo.4634895 (2021)."},{"key":"17218_CR49","doi-asserted-by":"publisher","unstructured":"[dataset], Miguel Ponce-de, L. et al. COVID19 Flow-Maps GeoLayers Dataset. Zenodo https:\/\/doi.org\/10.5281\/zenodo.4634662, (2021).","DOI":"10.5281\/zenodo.4634662"},{"key":"17218_CR50","doi-asserted-by":"crossref","unstructured":"Hamada, S. B., Hongru, D., Maximilian, M., Ensheng D., Marietta,\u00a0M. S. & Lauren,\u00a0M. G. Association between mobility patterns and covid-19 transmission in the usa: a mathematical modelling study. Lancet Infect. Dis. 20(11), 1247\u20131254, (2020).","DOI":"10.1016\/S1473-3099(20)30553-3"},{"issue":"10","key":"17218_CR51","doi-asserted-by":"publisher","first-page":"2400078","DOI":"10.1002\/andp.202400078","volume":"536","author":"C Granell","year":"2024","unstructured":"Granell, C., G\u00f3mez, S., G\u00f3mez-Garde\u00f1es, J. & Arenas, A. Probabilistic discrete-time models for spreading processes in complex networks: A review. Ann. Phys. 536(10), 2400078 (2024).","journal-title":"Ann. Phys."},{"issue":"1","key":"17218_CR52","doi-asserted-by":"publisher","first-page":"3748","DOI":"10.1038\/s41467-019-11763-z","volume":"10","author":"M Feng","year":"2019","unstructured":"Feng, M., Cai, S.-M., Tang, M. & Lai, Y.-C. Equivalence and its invalidation between non-markovian and markovian spreading dynamics on complex networks. Nat. Commun. 10(1), 3748 (2019).","journal-title":"Nat. Commun."},{"key":"17218_CR53","doi-asserted-by":"crossref","unstructured":"Nicol\u00f3,\u00a0A. C. & Paolo, P. Effective transfer entropy to measure information flows in credit markets. Stat. Methods Appl. 31(4), 729\u2013757, (2022).","DOI":"10.1007\/s10260-021-00614-1"},{"issue":"9","key":"17218_CR54","doi-asserted-by":"publisher","first-page":"577","DOI":"10.7326\/M20-0504","volume":"172","author":"SA Lauer","year":"2020","unstructured":"Lauer, S. A. et al. The incubation period of coronavirus disease 2019 (COVID-19) from publicly reported confirmed cases: Estimation and application. Ann. Intern. Med. 172(9), 577\u2013582 (2020).","journal-title":"Ann. Intern. Med."},{"issue":"05","key":"17218_CR55","first-page":"1","volume":"10","author":"C Cheng","year":"2021","unstructured":"Cheng, Ch. et al. The incubation period of COVID-19: A global meta-analysis of 53 studies and a Chinese observation study of 11 545 patients. Infect. Dis. Poverty 10(05), 1\u201313 (2021).","journal-title":"Infect. Dis. Poverty"},{"issue":"2","key":"17218_CR56","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1140\/epjb\/e2002-00379-2","volume":"30","author":"R Marschinski","year":"2002","unstructured":"Marschinski, R. & Kantz, H. Analysing the information flow between financial time series. Eur. Phys. J. B - Condensed Matter and Complex Systems 30(2), 275\u2013281 (2002).","journal-title":"Eur. Phys. J. B - Condensed Matter and Complex Systems"},{"issue":"2","key":"17218_CR57","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.bsheal.2020.03.004","volume":"2","author":"M D\u2019Arienzo","year":"2020","unstructured":"D\u2019Arienzo, M. & Coniglio, A. Assessment of the sars-cov-2 basic reproduction number, r0, based on the early phase of covid-19 outbreak in italy. Biosaf. Health 2(2), 57\u201359 (2020).","journal-title":"Biosaf. Health"},{"key":"17218_CR58","unstructured":"Oriol, G. \u00c1lava ya sufre una mayor incidencia del virus que Lombard\u00eda al decretarse la cuarentena. https:\/\/elpais.com\/sociedad\/2020-03-09\/alava-ya-sufre-una-mayor-incidencia-del-virus-que-lombardia-al-decretarse-la-cuarentena.html,(2020)."},{"key":"17218_CR59","unstructured":"Oriol, G. Un funeral en Vitoria caus\u00f3 m\u00e1s de 60 infectados. https:\/\/elpais.com\/sociedad\/2020-03-06\/mas-de-60-personas-se-contagiaron-a-la-vez-en-un-funeral-en-vitoria.html, (2020)."},{"key":"17218_CR60","unstructured":"Jessica,\u00a0M. E. & Virginia,\u00a0L. El brote entre temporeros de Arag\u00f3n deja una cuarta comarca en la fase 2. https:\/\/elpais.com\/sociedad\/2020-06-23\/el-brote-entre-temporeros-de-aragon-deja-una-cuarta-comarca-en-la-fase-2.html (2020)"},{"key":"17218_CR61","unstructured":"Coronavirus: A\u00edslan cincuenta temporeros en un pueblo de Lleida por un positivo. https:\/\/www.lavanguardia.com\/local\/lleida\/20200603\/481590717165\/aislan-cincuenta-temporeros-seros-lleida-positivo-covid-19-coronavirus.html, ( 2020)."},{"issue":"4","key":"17218_CR62","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1038\/s41567-017-0022-7","volume":"14","author":"J G\u00f3mez-Garde\u00f1es","year":"2018","unstructured":"G\u00f3mez-Garde\u00f1es, J., Soriano-Pa\u00f1os, D. & Arenas, A. Critical regimes driven by recurrent mobility patterns of reaction-diffusion processes in networks. Nat. Phys. 14(4), 391\u2013395 (2018).","journal-title":"Nat. Phys."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-17218-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-17218-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-17218-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T18:33:27Z","timestamp":1757442807000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-17218-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,26]]},"references-count":62,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["17218"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-17218-4","relation":{},"ISSN":["2045-2322"],"issn-type":[{"type":"electronic","value":"2045-2322"}],"subject":[],"published":{"date-parts":[[2025,8,26]]},"assertion":[{"value":"18 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"31504"}}