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Assessing the impact of interregional mobility on COVID19 spread in Spain using transfer entropy

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Název: Assessing the impact of interregional mobility on COVID19 spread in Spain using transfer entropy
Autoři: Ponce De Leon, Miguel, Pontes, Camila, Arenas, Alex, Valencia, Alfonso
Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Informace o vydavateli: Springer Science and Business Media LLC, 2025.
Rok vydání: 2025
Témata: Human mobility, Transfer entropy, Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica, Epidemic, Causal inference
Popis: Human mobility played a key role in shaping the spatiotemporal dynamics of COVID19 transmission. This study employs Transfer Entropy (TE), an information-theoretic approach, to investigate the directional relationship between interregional mobility and COVID19 spread in Spain. Specifically, we use the mobility-associated risk time series, derived from phone-based origin–destination data and local infection prevalence, to estimate the flow of potentially infected individuals between regions. TE is then applied to measure the information flow from mobility-associated risk to regional case counts, enabling us to uncover spatio-temporal patterns of mobility-driven transmission. Using real-world data, we identified provinces that acted as outbreak drivers during the COVID19 pandemic in Spain and detected temporal shifts in the strength and direction of mobility’s influence. Our findings align with key epidemiological events, such as the 2020 summer outbreak in Lleida linked to seasonal workers, and highlight the effects of non-pharmaceutical interventions, including bar closures in Catalunya, on transmission dynamics. Finally, we validated our approach using simulations from a metapopulation SIR model with known transmission pathways, showing that TE can recover mobility-induced transmission structure while reducing indirect or spurious associations. Altogether, our work provides a novel approach to study the effect of interregional mobility on epidemic spread and to uncover spatio-temporal patterns of mobility-driven transmission, offering valuable insights to inform the timing and regional targeting of non-pharmaceutical interventions.
This work has received funding from the Horizon 2020 project CREXDATA (ID: 101092749) and the MePreCiSa project of the UNICO I+D Cloud program, co-financed by the Ministry for Digital Transformation and of Civil Service and the EU-Next Generation EU as financing entities, within the framework of the PRTR and the MRR. CP was supported by the fellowship “Juan de la Cierva - Formación” from the Ministry of Education and Science of Spain (ID: FJC2021-046655-I). AA acknowledges support from the Spanish Ministerio de Ciencia e Innovación (PID2021-128005NB-C21), and the Joint Appointment Program at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.
Druh dokumentu: Article
Popis souboru: application/pdf
Jazyk: English
ISSN: 2045-2322
DOI: 10.1038/s41598-025-17218-4
Přístupová URL adresa: https://hdl.handle.net/2117/440699
https://doi.org/10.1038/s41598-025-17218-4
Rights: CC BY NC ND
Přístupové číslo: edsair.doi.dedup.....5ad95cde01e36a6c9cb1e8e94ccfb06d
Databáze: OpenAIRE
Popis
Abstrakt:Human mobility played a key role in shaping the spatiotemporal dynamics of COVID19 transmission. This study employs Transfer Entropy (TE), an information-theoretic approach, to investigate the directional relationship between interregional mobility and COVID19 spread in Spain. Specifically, we use the mobility-associated risk time series, derived from phone-based origin–destination data and local infection prevalence, to estimate the flow of potentially infected individuals between regions. TE is then applied to measure the information flow from mobility-associated risk to regional case counts, enabling us to uncover spatio-temporal patterns of mobility-driven transmission. Using real-world data, we identified provinces that acted as outbreak drivers during the COVID19 pandemic in Spain and detected temporal shifts in the strength and direction of mobility’s influence. Our findings align with key epidemiological events, such as the 2020 summer outbreak in Lleida linked to seasonal workers, and highlight the effects of non-pharmaceutical interventions, including bar closures in Catalunya, on transmission dynamics. Finally, we validated our approach using simulations from a metapopulation SIR model with known transmission pathways, showing that TE can recover mobility-induced transmission structure while reducing indirect or spurious associations. Altogether, our work provides a novel approach to study the effect of interregional mobility on epidemic spread and to uncover spatio-temporal patterns of mobility-driven transmission, offering valuable insights to inform the timing and regional targeting of non-pharmaceutical interventions.<br />This work has received funding from the Horizon 2020 project CREXDATA (ID: 101092749) and the MePreCiSa project of the UNICO I+D Cloud program, co-financed by the Ministry for Digital Transformation and of Civil Service and the EU-Next Generation EU as financing entities, within the framework of the PRTR and the MRR. CP was supported by the fellowship “Juan de la Cierva - Formación” from the Ministry of Education and Science of Spain (ID: FJC2021-046655-I). AA acknowledges support from the Spanish Ministerio de Ciencia e Innovación (PID2021-128005NB-C21), and the Joint Appointment Program at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.
ISSN:20452322
DOI:10.1038/s41598-025-17218-4