[Spatiotemporal changes of COVID-19 outbreak in Shanghai].
Zhonghua Liu Xing Bing Xue Za Zhi
; 43(11): 1699-1704, 2022 Nov 10.
Article
in Chinese
| MEDLINE | ID: covidwho-2143855
ABSTRACT
Objective:
To clarify the epidemiological characteristics and spatiotemporal clustering dynamics of COVID-19 in Shanghai in 2022.Methods:
The COVID-19 data presented on the official websites of Municipal Health Commissions of Shanghai during March 1, 2022 and May 31, 2022 were collected for a spatial autocorrelation analysis by GeoDa software. A logistic growth model was used to fit the epidemic situation and make a comparison with the actual infection situation.Results:
Pudong district had the highest number of symptomatic and asymptomatic infectants, accounting for 29.30% and 35.58% of the total infectants. Differences in cumulative attack rates and infection rates among 16 districts (P<0.001) were significant. The rates were significantly higher in Huangpu district than in other districts. The attack rate of COVID-19 from March 1, 2022 to May 31, 2022 had a global spatial positive correlation (P<0.05). Spatial distribution of COVID-19 attack rate was different at different periods. The global autocorrelation coefficient from March 16 to March 29, April 6 to April 12 and May 18 to May 24 had no statistical significance (P>0.05). Our local autocorrelation analysis showed that 22 high-high clustering areas were detected in eight periods.The high-risk hot-spot areas have experienced a "less-more-less" change process. The growth model fitting results were consistent with the actual infection situation.Conclusion:
There was a clear spatiotemporal correlation in the distribution of COVID-19 in Shanghai. The comprehensive prevention and control measures of COVID-19 epidemic in Shanghai have effectively prohibited the growth of the epidemic, not only curbing the spatially spread of high-risk epidemic areas, but also reducing the risk of transmission to other cities.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Epidemics
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Limits:
Humans
Country/Region as subject:
Asia
Language:
Chinese
Journal:
Zhonghua Liu Xing Bing Xue Za Zhi
Year:
2022
Document Type:
Article
Affiliation country:
Cma.j.cn112338-20220608-00511
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