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1.
Zhonghua Liu Xing Bing Xue Za Zhi ; 43(6): 835-840, 2022 Jun 10.
Article in Chinese | MEDLINE | ID: covidwho-1903513

ABSTRACT

Objective: To analyze the epidemiological characteristics of COVID-19 caused by 2019-nCoV Delta variant (B.1.617.2) in Gansu province, and provide evidence for the prevention and control of COVID-19. Methods: The information of COVID-19 cases, including demographic characteristics, epidemiological history, onset date, diagnosis date, exposure place, detection way and infection source, in Gansu from 17 October to 25 November, 2021 were collected. Software Excel 2016,SPSS 22 and ArcGIS 10.7 were used for data process and analysis. Results: As of November 25, 2021, a total of 146 COVID-19 cases had been reported in Gansu and the epidemic affected 10 counties (districts) in 5 cities. The epidemic of COVID-19 in Gansu had three stages: imported case stage,imported-local case stage and local case stage. The age of cases ranged from 1 to 87 years,and the cases in age group 18-59 years accounted for 59.59% (87/146). The male to female ratio of the cases was 1∶1.12 (69∶77). The cases were mainly people engaged in business services (17.12%, 25/146),retirees (15.75%, 23/146),students (13.70%, 20/146),the jobless and unemployed (12.33%, 18/146). In 3 epidemic stages, the cases aged 18-59 years accounted for 44.44%,54.41% and 70.00% respectively,showing an upward trend,and there were differences among different populations (trend χ2=23.24, P<0.001). Also, the incubation period of the cases tended to decrease, and severe cases accounted for 33.33% (6/18), 19.12% (13/68) and 3.33% (2/60) respectively, showing a downward trend. Community screening (25.34%, 37/146) and close contact screening were the main ways to detect cases,the cases detected by close contact screening in 3 epidemic stages accounted for 50.00% (9/18), 66.18% (45/68) and 86.67% (52/60) respectively. The epidemic had obvious case clustering in confined places,and the main exposure modes were living together (24.66%), working/studying together (11.64%), taking same transportation (9.59%) and dining together (9.59%). Conclusions: The COVID-19 epidemic in Gansu was caused by 2019-nCoV Delta variant from imported cases. The virus was mainly transmitted through travel, sharing transportation, dining together and home contact. The characteristics of COVID-19 epidemic in Gansu changed with time, the case's clinical symptoms were not obvious and the incubation period became shorter. The infections mainly occurred in group aged 18 years and above.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , China/epidemiology , Cities , Cluster Analysis , Female , Humans , Male
2.
Zhonghua Liu Xing Bing Xue Za Zhi ; 41(0): E032, 2020 Apr 01.
Article in Chinese | MEDLINE | ID: covidwho-27070

ABSTRACT

Objective: To understand the epidemiological characteristics of COVID-19 cases in different epidemic stages in Gansu province. Methods: Epidemiological investigation was conducted to collect the information of confirmed COVID-19 cases, including demographic, epidemiological and clinical information. Results: As of 25 February 2020, a total of 91 confirmed COVID-19 cases had been reported in Gansu. The epidemic of COVID-19 in Gansu can be divided as three different stages, i.e. imported case stage, imported-case plus indigenous case stage, and indigenous case stage. A total of 63 cases were clustered cases (69.23%), 3 cases were medical staff infected with non-occupational exposure. The initial symptoms included fever (54.95%, 50/91), cough (52.75%, 48/91), or fatigue (28.57%, 26/91), the proportion of each symptom showed a decreasing trend along with the three epidemic stages, but only the differences in proportions of fever (trend χ2=2.20, P<0.05) and fatigue (trend χ2=3.18, P<0.05) among the three epidemic stages were statistically significant. The cases with critical severe symptoms accounted for 42.85% (6/14), 23.73% (14/59) and 16.67% (3/18), respectively, in three epidemic stages, showed a decreasing trend (H=6.45, P<0.05). Also, the incubation period prolonged along with the epidemic stage (F=51.65, P<0.01), but the intervals between disease onset and hospital visit (F=5.32, P<0.01), disease onset and diagnosis (F=5.25, P<0.01) became shorter along with the epidemic stage. Additionally, the basic reproduction number (R0) had decreased from 2.61 in imported case stage to 0.66 in indigenous case stage. Conclusions: The COVID-19 epidemic in Gansu was caused by the imported cases, and about 2/3 cases were clustered ones. No medical worker was observed to be infected by occupational exposure. With the progression of COVID-19 epidemic in Gansu, the change in initial symptom and incubation period suggests, the early screening cannot only depend on body temperature monitoring.

3.
Non-conventional in Chinese | WHO COVID | ID: covidwho-707519

ABSTRACT

OBJECTIVE: To investigate the current situation of virus exposure risk incidents of nurses against corona virus disease 2019 (COVID-19) in Wuhan, and to provide reference evidence for nursing managers to protect nursing staff who were working in the isolation ward. METHODS: In the study, 308 nursing staff against COVID-19 working in the isolation ward in Wuhan were conveniently selected to participate in the investigation. The designed questionnaires including 7 kinds of protective exposure risk events were made by the team of researchers on the basis of literature review and interview with the nurses in Wuhan. All the participants recalled their working experience in the status of dressing in personal protective equipment and filled in the questionnaires online by WeChat according to the same instruction. RESULTS: The questionnaires were filled in validly by a total of 304 nursing staff, of whom 88.8% received emergency training on the prevention and dealing measurement of exposure risk events. The incidence of shoe cover contamination, falling off or torn was relatively high, about 53.6%. Due to the protection of gloves, the incidence of hand or skin contamination was relatively low, about 14.1%. The most nervousness of protective exposure risk event for nurses was N95 mask contamination, falling off or shifting, with a score of 8.2±2.3, showing a higher psychiatric burden. Single factor analysis found that the number of days in Wuhan was different, the number of the types of protective risk events occurred was different (χ(2)=14.562, P=0.024), orderly multivariate Logistic regression found that men were the independent protective factor for the number of the types of protective exposure risk events that occurred (P=0.019). CONCLUSION: Protective exposure risk events may occur in the work of nursing staff working in the isolation ward in Wuhan. It is necessary to guide nurses to prevent the occurrence of protective exposure risk events and effectively deal with them, so as to prevent virus exposure and reduce psycholo-gical burden.

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