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[Prediction of end of lockdown post-peak of cases in first wave of the COVID-19 pandemic in Chile].
- Source :
-
Medwave [Medwave] 2020 Nov 09; Vol. 20 (10), pp. e8057. Date of Electronic Publication: 2020 Nov 09. - Publication Year :
- 2020
-
Abstract
- Introduction: The results of mandatory confinement have been detrimental in several respects. Nonetheless, they have resulted in reducing the number of active cases of COVID-19. Chile has begun the de-escalation and needs to know the best time to end the restrictions.<br />Objective: We discuss the best conditions and guarantees for the end of compulsory confinement.<br />Methods: This study is based on a trend model with prediction estimation. The data of the variables of interest were subjected to linear regression studies to determine the curve that best explained the data. The coefficient of determination, the standard deviation of y in x, and the confidence interval of the observed curve were estimated. The trend curve was chosen in accordance with the regression estimates.<br />Outcomes: It was found that all dependent variables tended to decrease over time in a quadratic fashion, except for the new cases variable. In general, the R2 and MAPE estimates are satisfactory, except for the variable number of PCR tests per day.<br />Conclusions: Gradual and cautious steps should be taken before ending mandatory confinement. In the current de-escalator, daily PCR tests should be increased, maintaining vigilance on indicators of incidence, prevalence, and positivity of PCR tests. Evidence suggests with some degree of confidence that mandatory confinement could be safely lifted as of August 30, 2020. Long-term preparations must be made to contain future waves of new cases.
- Subjects :
- Chile epidemiology
Confidence Intervals
Humans
Incidence
Linear Models
Prevalence
Reverse Transcriptase Polymerase Chain Reaction trends
COVID-19 epidemiology
COVID-19 prevention & control
Pandemics
Quarantine trends
Reverse Transcriptase Polymerase Chain Reaction statistics & numerical data
SARS-CoV-2
Subjects
Details
- Language :
- Spanish; Castilian
- ISSN :
- 0717-6384
- Volume :
- 20
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Medwave
- Publication Type :
- Academic Journal
- Accession number :
- 33231573
- Full Text :
- https://doi.org/10.5867/medwave.2020.10.8057