Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/6298
Title: Assessment of Characteristics and Conditions before the End of Lockdown
Authors: San-Martín-Roldán, David
Rojo-Lazo, Francisca
Calzadilla-Núñez, Aracelis
San-Martín-Roldán, Pablo
Keywords: COVID-19
forecasting
lockdown
SARS-CoV-2
Issue Date: 2021
Abstract: Assessment of Characteristics and Conditions before the End of Lockdown David San-Martín-Roldán1*, Francisca Rojo-Lazo1, Aracelis Calzadilla-Núñez2, Pablo San-Martín-Roldán3,... 1Escuela de Obstetricia y Puericultura, Facultad de Medicina, Universidad de Valparaíso, Valparaíso, Chile 2Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Santiago, Chile 3Instituto de Nutrición y Tecnología de los Alimentos (INTA), Universidad de Chile, Santiago, Chile Abstract After months of blockades and restriction, the decision of the best time to end the lockdown after the first wave of the COVID-19 pandemic is the big question for health rectors. This study aimed to evaluate the characteristics and conditions for ending the blockade after the first wave of COVID-19. Data on the variables of interest were subjected to linear and non-linear regression studies to determine the curve that best explains the data. The coefficient of determination, the standard deviation of y in x, and the observed curve of the confidence interval were estimated. Regression which was estimated, subsequently revealed the trend curve. The study found that all dependent variables tend to decrease over time in a quadratic fashion, except for the variable for new cases. In general, the R2 and mean absolute percentage error (MAPE) estimated were satisfactory: gradual and cautious steps should be taken before ending the lockdown. The results suggested that surveillance of crucial indicators (e.g., incidence, prevalence, and PCR test positivity) should be maintained before lockdown is terminated. Moreover, the findings indicated that long-term preparations should be made to contain future waves of new cases. Keywords: COVID-19, forecasting, lockdown, SARS-CoV-2
URI: http://localhost:8080/xmlui/handle/123456789/6298
Appears in Collections:VOL 16 NO 1 2021

Files in This Item:
File Description SizeFormat 
3.pdf212.01 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.