Which curve provides the best explanation of the growth in confirmed COVID-19 cases in Chile? / Qual é a curva que melhor explica o crescimento de casos confirmados da COVID-19 no Chile? / ¿Cuál es la curva que mejor explica el crecimiento de los casos confirmados de COVID-19 en Chile?
Rev. latinoam. enferm. (Online)
; 28: e3346, 2020.
Article
em En, Es, Pt
| LILACS, BDENF
| ID: biblio-1103345
Biblioteca responsável:
BR21.2
ABSTRACT
Objective 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. Method 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. Results the curve that best fits the evolution of the accumulated confirmed cases of COVID-19 in Chile is the doubly-smoothed exponential curve. Conclusion 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.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
4_TD
Base de dados:
BDENF
/
LILACS
Assunto principal:
Pneumonia Viral
/
Infecções por Coronavirus
/
Pandemias
Tipo de estudo:
Prognostic_studies
Limite:
Humans
País/Região como assunto:
America do sul
/
Chile
Idioma:
En
/
Es
/
Pt
Revista:
Rev. latinoam. enferm. (Online)
Ano de publicação:
2020
Tipo de documento:
Article