Epidemiology, modelling and information systems in the COVID-19 control in Cuba
Abstract
Introduction. This paper summarizes the contribution by the Technical Group for Modelling and Epidemiology to face COVID-19. The objective was to create knowledge and scientific evidence to support the Government’s decision making, the health system and other sectors. Methods. Implementation research from a transdisciplinary perspective was carried out, with epidemiology providing the guidelines. Tools were developed to identify the magnitude and dissemination of COVID-19 in the country, as well as the analysis of the risk to get sick and severity; also, tools for the evaluation of the measures implemented. Results and Discussion. Improvements were made to the information systems and the Covid19CubaData platform was created to standardize and visualize the data. Prognosis mathematical models were developed. Geographical information systems were used to identify vulnerable population groups and stratify interventions. The impact of the actions was evaluated with a clinical-epidemiological analysis, as well as the use of big data techniques on mobility and real time estimation of the effective reproductive number. Multilevel and artificial intelligence models allowed for comparing the behavior of the pandemic in Cuba and the world. Indicators were brought forward for the de-escalation of the actions. The equity in the country’s response to COVID-19 was evaluated. Conclusions: the epidemiological research done, supported by modelling and the information systems, was useful for the government and the Ministry of Public Health to effectively face COVID-19.
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