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1.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(5): 655-662, 2022 May 10.
Article in Chinese | MEDLINE | ID: covidwho-1969571

ABSTRACT

2019-nCoV Omicron (B.1.1.529) variant, which has brought new challenges to the prevention and control of COVID-19 pandemic, has the characteristics of stronger transmissibility and more rapid transmission and more significant immune evasion. It took only two months to become a predominant strain worldwide after its identification in South Africa in November 2021. Local epidemics caused by Omicron variant have been reported in several provinces in China. However, the epidemiological characteristics of highly mutated Omicron variant remain unclear. This article summarizes the progress in the research of functional mutations, transmissibility, virulence, immune evasion and cross-reactive immune responses of Omicron variant, to provide references for the effective prevention and control of COVID-19 pandemic caused by Omicron variant.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Mutation , Pandemics
2.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(5):655-662, 2022.
Article in Chinese | PubMed | ID: covidwho-1848753

ABSTRACT

2019-nCoV Omicron (B.1.1.529) variant, which has brought new challenges to the prevention and control of COVID-19 pandemic, has the characteristics of stronger transmissibility and more rapid transmission and more significant immune evasion. It took only two months to become a predominant strain worldwide after its identification in South Africa in November 2021. Local epidemics caused by Omicron variant have been reported in several provinces in China. However, the epidemiological characteristics of highly mutated Omicron variant remain unclear. This article summarizes the progress in the research of functional mutations, transmissibility, virulence, immune evasion and cross-reactive immune responses of Omicron variant, to provide references for the effective prevention and control of COVID-19 pandemic caused by Omicron variant.

3.
Zhonghua Yu Fang Yi Xue Za Zhi ; 56(4): 474-478, 2022 Apr 06.
Article in Chinese | MEDLINE | ID: covidwho-1834947

ABSTRACT

Objective: To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies. Methods: To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease. Results: In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI:3.86-5.13) days, 5.12 (95%CI:4.63-5.62) days, 0.87 (95%CI:0.67-1.07) days, 11.89 (95%CI:9.81-13.98) days and 22.00 (95%CI:21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI:6.89-10.86) days and 6.18 (95%CI:1.89-10.47) days, respectively. Conclusion: The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.


Subject(s)
COVID-19 , Contact Tracing , Cohort Studies , Humans , Incidence , Prospective Studies
4.
Zhonghua Yu Fang Yi Xue Za Zhi ; 54(7): 720-725, 2020 Jul 06.
Article in Chinese | MEDLINE | ID: covidwho-731282

ABSTRACT

Objective: Analysis of clustering characteristics of coronavirus disease 2019 (COVID-19) in Guangdong Province. Methods: The COVID-19 cases in Guangdong Province onset from January 1 to February 29, 2020 were collected from Chinese information system for disease control and prevention and Emergency Public Reporting System. Obtain the epidemiological survey data of the cluster epidemic situation, and clarify the scale of cluster epidemic situation, the characteristics of the index cases, family and non-family subsequent cases. Calculate serial interval according to the onset time of the index cases and subsequent cases, secondary attack rate based on the close contacts tracking results, the characteristics of different cases in the clustered epidemic were compared. Results: A total of 283 cluster were collected, including 633 index cases, 239 subsequent cases. Families are mainly clustered, the total number involved in each cluster is in the range of 2-27, M (P25, P75) are 2.0 (2.0, 4.0). During January 15 to February 29, the secondary attack rate is 2.86% (239/8 363) in Guangdong Province, the family secondary attack rate was 4.84% (276/3 697), and the non-family secondary attack rate was 1.32% (61/4 632). According to the reporting trend of the number of cases in Guangdong Province, it can be divided into four stages, the rising stage, the high platform stage, the descending stage and the low level fluctuation period. The secondary attack rate of the four stages were 3.5% (140/3 987), 2.3% (55/2 399), 2.6% (37/1 435), 1.3% (7/542), respectively. The difference was statistically significant (P=0.003). Conclusion: COVID-19 cluster mainly occurs in families in Guangdong Province. The scale of the clustered epidemic was small; the serial interval was short; and the overall secondary attack rate was low.


Subject(s)
Coronavirus Infections/epidemiology , Epidemics , Pneumonia, Viral/epidemiology , COVID-19 , China/epidemiology , Cluster Analysis , Humans , Pandemics
5.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(12): 1999-2004, 2020 Dec 10.
Article in Chinese | MEDLINE | ID: covidwho-144088

ABSTRACT

Objective: To analyze the clinical courses and outcomes of COVID-19 cases and the influencing factors in Guangdong province and provide basis for the formulation or adjustment of medical care and epidemic control strategy for COVID-19. Methods: We collected demographic data, medical histories, clinical courses and outcomes of 1 350 COVID-19 patients reported in Guangdong as of 4 March 2020 via epidemiological investigation and process tracking. Disease severity and clinical course characteristics of the patients and influencing factors of severe illness were analyzed in our study. Results: Among 1 350 cases of COVID-19 cases in Guangdong, 72 (5.3%) and 1 049 (77.7%) were mild and ordinary cases, 164 (12.1%) were severe cases, 58 (4.3%) were critical cases and 7 (0.5%) were fatal. The median duration of illness were 23 days (P(25), P(75): 18, 31 days) and the median length of hospitalization were 20 days (P(25), P(75): 15,27 days). For severe cases, the median time of showing severe manifestations was on the 12(th) day after onset (P(25), P(75): 9(th) to 15(th) days), and the median time of severe manifestation lasted for 8 days (P(25), P(75): 4, 14 days). Among 1 066 discharged/fetal cases, 36.4% (36/99) and 1.0% (1/99) of the mild cases developed to ordinary cases and severe cases respectively after admission; and 5.2% (50/968) and 0.6% (6/968) of the ordinary cases developed to severe cases, and critical cases respectively after admission. In severe cases, 11.4% developed to critical cases (10/88). The influencing factors for severe illness or worse included male (aHR=1.87, 95%CI: 1.43-2.46), older age (aHR=1.67, 95%CI: 1.51-1.85), seeking medical care on day 2-3 after onset (aHR=1.73, 95%CI: 1.20-2.50) pre-existing diabetes (aHR=1.75, 95%CI: 1.12-2.73) and hypertension (aHR=1.49, 95%CI: 1.06-2.09). Conclusions: The course of illness and length of hospitalization of COVID-19 cases were generally long and associated with severity of disease clinical outcomes. The severe cases were mainly occurred in populations at high risk. In the epidemic period, classified management of COVID-19 cases should be promoted according to needs for control and prevention of isolation and treatment for the purpose of rational allocation of medical resources.


Subject(s)
COVID-19 , Aged , COVID-19/epidemiology , China/epidemiology , Hospitalization , Humans , Male , Patient Discharge , SARS-CoV-2
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