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Prediction of the COVID-19 trend for 2021 in northwestern Argentina

##article.authors##

  • Eduardo Agustín Mendoza Fundación Miguel Lillo image/svg+xml https://orcid.org/0000-0003-2216-4332
  • Octavio Bruzzone Unidad Ejecutora Instituto de Investigaciones Forestales y Agropecuarias Bariloche, (Instituto Nacional de Tecnología Agropecuaria/Consejo Nacional de Investigaciones Científicas y Técnicas)
  • María Julia Dantur Juri Unidad Ejecutora Lillo image/svg+xml

DOI:

https://doi.org/10.1590/1980-549720220001

Keywords:

Prediction, model, COVID-19, vaccine, Tucumán

Abstract

Using a lagged polynomial regression model, which used COVID-19 data from 2020 with no vaccines, the prediction of COVID-19 was performed in a scenario with vaccine administration for Tucumán in 2021. The modeling included the identification of a contagion breaking point between both series with the best correlation. Previously, the lag that served to obtain the smallest error between the expected and observed values was indicated by means of cross correlation. The validation of the model was carried out with real data. In 21 days, 18,640 COVID-19 cases out of 20,400 reported cases were predicted. The maximum peak of COVID-19 was estimated 21 days in advance with the expected intensity.

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Posted

12/13/2021 — Updated on 12/15/2021

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Section

Health Sciences