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1.
Sci Rep ; 11(1): 11317, 2021 05 31.
Artículo en Inglés | MEDLINE | ID: mdl-34059760

RESUMEN

Since the outbreak of COVID-19 in December 2019 in Wuhan, Zhejiang has become the province with the largest number of cases. The aim of this article is to present Zhejiang province's experience of establishing an accurate and smart control mechanism for epidemic prevention and control and resumption of work and production using a 'five-colour epidemic chart'. The number of confirmed cases, proportion of local cases, and occurrence of clustered outbreaks were used as evaluation indicators to calculate the county-level epidemic risk and were assigned different weight coefficients; the absence of cases for 3 and 7 consecutive days was used as the adjustment index. When the first chart was published on February 9, there were 1 very-high-risk, 12 high-risk, and 12 low-risk counties. Under the five-colour chart, Zhejiang began to adopt precise measures to prevent and control the epidemic and resume work and production. By February 24, the low-risk counties had expanded to 82, with no high-risk and very-high-risk counties. The epidemic situation in Zhejiang province has been effectively controlled. The experience of epidemic prevention and control in Zhejiang is worthy to be emulated and learned by other countries and regions.


Asunto(s)
COVID-19/epidemiología , Pandemias/prevención & control , COVID-19/prevención & control , China/epidemiología , Color , Brotes de Enfermedades , Epidemias , Humanos , Cuarentena , Medición de Riesgo/estadística & datos numéricos
2.
J Public Health (Oxf) ; 43(1): 35-41, 2021 04 12.
Artículo en Inglés | MEDLINE | ID: mdl-32930793

RESUMEN

BACKGROUND: To our knowledge, no previous studies have focused on determining whether the virulence and case fatality rate of the severe acute respiratory coronavirus 2 (SARS-CoV-2) decreases as the virus continues to spread. Hence, our aim was to retrospectively explore the differences in the risk of severe or critical COVID-19 among imported, secondary and tertiary cases in Zhejiang, China. METHODS: We categorized COVID-19 cases reported by hospitals in Zhejiang as first-, second- and third-generation cases. Univariate and multivariate logistic regression analyses were performed to compare disease severity and case generation. RESULTS: Of 1187 COVID-19 cases, 227 (19.1%, 95% CI: 16.9-21.4) manifested severe or critical illness. The adjusted risk difference for severe or critical illness was lower for second- (odds ratio (OR) = 0.84, 95% confidence interval (CI): 0.52-1.36) and third-generation (OR = 0.55, 95% CI: 0.37-0.83) cases than for first-generation cases. Compared with hospitalized patients, cases identified at centralized isolation locations (OR = 0.62, 95% CI: 0.40-0.97) and those identified through active search or gateway screening (OR = 0.28, 95% CI: 0.08-1.04) were at a lower risk of severe or critical illness. CONCLUSIONS: Second- and third-generation cases of COVID-19 have a lower risk of developing severe or critical illness than first-generation cases.


Asunto(s)
COVID-19 , Índice de Severidad de la Enfermedad , Adulto , Factores de Edad , Anciano , Análisis de Varianza , COVID-19/clasificación , COVID-19/epidemiología , China/epidemiología , Progresión de la Enfermedad , Femenino , Humanos , Incidencia , Modelos Logísticos , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Factores de Riesgo , SARS-CoV-2 , Factores Sexuales
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