doi:10.1186/s12874-023-01842-7engAleta, AlbertoBlas-Laína, Juan LuisTirado Anglés, GabrielMoreno, YamirUnraveling the COVID-19 hospitalization dynamics in Spain using Bayesian inferenceART-2023-132908Background: One of the main challenges of the COVID-19 pandemic is to make sense of available, but often heterogeneous and noisy data. This contribution presents a data-driven methodology that allows exploring the hospitalization dynamics of COVID-19, exemplified with a study of 17 autonomous regions in Spain from summer 2020 to summer 2021. Methods: We use data on new daily cases and hospitalizations reported by the Spanish Ministry of Health to implement a Bayesian inference method that allows making short-term predictions of bed occupancy of COVID-19 patients in each of the autonomous regions of the country. Results: We show how to use the temporal series for the number of daily admissions and discharges from hospital to reproduce the hospitalization dynamics of COVID-19 patients. For the case-study of the region of Aragon, we estimate that the probability of being admitted to hospital care upon infection is 0.090 [0.086-0.094], (95% C.I.), with the distribution governing hospital admission yielding a median interval of 3.5 days and an IQR of 7 days. Likewise, the distribution on the length of stay produces estimates of 12 days for the median and 10 days for the IQR. A comparison between model parameters for the regions analyzed allows to detect differences and changes in policies of the health authorities. Conclusions: We observe important regional differences, signaling that to properly compare very different populations, it is paramount to acknowledge all the diversity in terms of culture, socio-economic status, and resource availability. To better understand the impact of this pandemic, much more data, disaggregated and properly annotated, should be made available.2023http://zaguan.unizar.es/record/12531310.1186/s12874-023-01842-7http://zaguan.unizar.es/record/125313oai:zaguan.unizar.es:125313info:eu-repo/grantAgreement/ES/DGA/E36-20Rinfo:eu-repo/grantAgreement/ES/MCIN-AEI-FEDER/PID2020-115800GB-I00info:eu-repo/grantAgreement/ES/MICINN/RYC2021-033226-Iinfo:eu-repo/grantAgreement/ES/UZ/UZ-SANTANDER/2020-0274BMC Medical Research Methodology 23 (2023), 24 [11 pp.]byhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccess