Which curve provides the best explanation of the growth in confirmed COVID-19 cases in Chile?

to explore the best type of curve or trend model that could explain the epidemiological behavior of the infection by COVID-19 and derive the possible causes that contribute to explain the corresponding model and the health implications that can be inferred. data were collected from the COVID-19 repo...

Full description

Saved in:
Bibliographic Details
Published in:Revista latino-americana de enfermagem 2020-01, Vol.28, p.e3346-e3346
Main Authors: Díaz-Narváez, Víctor, San-Martín-Roldán, David, Calzadilla-Núñez, Aracelis, San-Martín-Roldán, Pablo, Parody-Muñoz, Alexander, Robledo-Veloso, Gonzalo
Format: Article
Language:English
Subjects:
2019-nCoV
Betacoronavirus
Chile - epidemiology
Coronavirus
Coronavirus Infections
Coronavirus Infections - epidemiology
Coronaviruses
COVID-19
Epidemiology
Humans
Models, Statistical
NURSING
Original
Pandemics
Pandemics - statistics & numerical data
Pneumonia, Viral - epidemiology
SARS-CoV-2
Time Factors
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:to explore the best type of curve or trend model that could explain the epidemiological behavior of the infection by COVID-19 and derive the possible causes that contribute to explain the corresponding model and the health implications that can be inferred. data were collected from the COVID-19 reports of the Department of Epidemiology, Ministry of Health, Chile. Curve adjustment studies were developed with the data in four different models: quadratic, exponential, simple exponential smoothing, and double exponential smoothing. The significance level used was α≤0.05. the curve that best fits the evolution of the accumulated confirmed cases of COVID-19 in Chile is the doubly-smoothed exponential curve. the number of infected patients will continue to increase. Chile needs to remain vigilant and adjust the strategies around the prevention and control measures. The behavior of the population plays a fundamental role. We suggest not relaxing restrictions and further improving epidemiological surveillance. Emergency preparations are needed and more resource elements need to be added to the current health support. This prediction is provisional and depends on keeping all intervening variables constant. Any alteration will modify the prediction.
ISSN:1518-8345
0104-1169
1518-8345
DOI:10.1590/1518-8345.4493.3346