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Introduction: Epidemiological models have proven to be crucial in supporting the decision-making of health authorities during the COVID-19 pandemic as well as raising awareness among the general public of the different measures adopted by authorities (social distancing, mask usage, vaccination, etc.). Objectives: This work describes the methodology to integrate different data sources to generate a single time series that provides real incidence rates of COVID-19 in Spain. Methodology: This series considers both reported and non-notified cases, that is, those that have not been registered by health authorities. Results: This work also describes how the information generated in this project has been treated and stored, it presents the estimated real incidence data obtained, as well as the organizations and research teams that use it, and the different communication channels that have been used to disseminate it (webpage, sharing results with health authorities, and repository). Conclusion: This work integrates information from multiple data sources for the analysis and prediction of the incidence of COVID-19. Through a multidisciplinary approach, it has been possible to propose a response to the problem of estimating the real incidence of COVID-19 cases. [ABSTRACT FROM AUTHOR]