TY - JOUR AU - Duarte, Rigoberto Fimia AU - Rodríguez, Ricardo Osés AU - Rodríguez, Pedro Y. de la Fé AU - Llanes, Claudia Osés AU - Gavilanes, María P. Zambrano AU - Puebla, Luis E. Jerez AU - González, Frank M. Wilford PY - 2021/09/18 Y2 - 2024/03/28 TI - COVID-19: fitting a ROR prediction model for Cuba as vaccination advance JF - European Journal of Applied Sciences JA - EJAS VL - 9 IS - 5 SE - Articles DO - 10.14738/aivp.95.10864 UR - https://journals.scholarpublishing.org/index.php/AIVP/article/view/10864 SP - 56-65 AB - <p><strong>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 </strong><strong>Regressive Objective Regression </strong><strong>(ROR) methodology. The daily official reports of new COVID-19 cases in Cuba from March 2020 until July the 15<sup>th</sup>, 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 7<sup>th</sup>, 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.</strong></p> ER -