COVID-19: fitting a ROR prediction model for Cuba as vaccination advance


  • Rigoberto Fimia Duarte
  • Ricardo Osés Rodríguez
  • Pedro Y. de la Fé Rodríguez
  • Claudia Osés Llanes
  • María P. Zambrano Gavilanes
  • Luis E. Jerez Puebla
  • Frank M. Wilford González



Cuba, COVID-19, prognostic, Regressive Objective Regression, SARS-CoV-2, vaccination


Most of countries are still in the midst of the deadly COVID-19 pandemic, and there is a shortage of licensed vaccines and access to them currently. This research was undertaken to predict new COVID-19 cases, as well as the impact of vaccination in Cuba using the Regressive Objective Regression (ROR) methodology. The daily official reports of new COVID-19 cases in Cuba from March 2020 until July the 15th, 2021, allowed to fit the ROR model. Thanks of the present restriction measures and the vaccination rate in Cuba, cases are predicted to fall as of October the 7th, 2021. The intensification and sustainability of hygienic and sanitary measures must be keep, as well as social distancing, otherwise the number of new daily cases might increase close to or even higher than 10,000. It is concluded that COVID-19 despite being a new disease, can be surveilled by ROR modeling, which allows better pandemic management.




How to Cite

Duarte, R. F. ., Rodríguez, R. O. ., Rodríguez, P. Y. de la F. ., Llanes, C. O. ., Gavilanes, M. P. Z. ., Puebla, L. E. J. ., & González, F. M. W. . (2021). COVID-19: fitting a ROR prediction model for Cuba as vaccination advance. European Journal of Applied Sciences, 9(5), 56–65.