Effectiveness of measures against COVID-19 based on pandemic case analysis
Background: : the lack of references to crises similar to COVID-19 pandemic in the past makes difficult to predict what may happen in the immediate future. Logically, the present effects are easily documented, but those that will leave their mark on the different actors in the medium and long term a...
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Published in | Archivo médico de Camagüey Vol. 24; no. 5; pp. 653 - 664 |
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Main Authors | , |
Format | Journal Article |
Language | Spanish |
Published |
Universidad de Ciencias Médicas de Camagüey
01.10.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Background: : the lack of references to crises similar to COVID-19 pandemic in the past makes difficult to predict what may happen in the immediate future. Logically, the present effects are easily documented, but those that will leave their mark on the different actors in the medium and long term are subject to more debate. Objective: to analyze the behavior of this pandemic in the Cuban region centered on the month of April, showing the best direction to follow when making decisions. Methods: a mathematical model was designed based on the impact of the effectiveness of the measures in the face of this pandemic based on the polynomial functions of confirmed cases and the cases recovered in the territory during the month of April. Results: the current and future behavior of the effectiveness of the treatment in the face of this pandemic is showed, allowing decisions to be made in the short and long term, taking into account these variables. Conclusions: the effectiveness function was obtained based on the functions of confirmed cases and daily recovered cases, showing that improvements are expected in the confrontation of the pandemic with extreme discipline, which allows the territory to establish an improvement strategy based on an action plan. DeCS: PANDEMICS/prevention CORONAVIRUS INFECTIONS/transmission; CORONAVIRUS INFECTIONS/epidemiology; DISEASE OUTBREAKS; EPIDEMIOLOGY, DESCRIPTIVE. |
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ISSN: | 1025-0255 |