Abstract

This article presents a model able to describe and forecast the evolution of Covid-19 at the local level. This involves the design, programming and calibration of an epidemiological model that, in addition to the four states of a SEIR model, describes the path of severe and critical patients, fundamental states in order to plan the health system. Our model embeds local characteristics, such as the age composition of the population and the effect of mitigation measures on the reproductive factor. Likewise, our model is stochastic due to the incorporation of uncertainty in key variables associated with the virus and of difficult projection for the policy maker. Besides, we show the goodness of fit inside and outside the sample for Tucumán and Ciudad de Buenos Aires, Argentina. Finally, we show its application at the local level, forecasting a likely epidemiological scenario, and demands to the health system for Tucumán, Argentina.

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