Spatiotemporal distribution analysis of the COVID-19 in Shenzhen based on geographic information system

Yining Huang

doi:10.1117/12.2692774

7 September 2023 Spatiotemporal distribution analysis of the COVID-19 in Shenzhen based on geographic information system

Yining Huang

Author Affiliations +

Proceedings Volume 12789, International Conference on Modern Medicine and Global Health (ICMMGH 2023); 1278928 (2023) https://doi.org/10.1117/12.2692774
Event: International Conference on Modern Medicine and Global Health (ICMMGH 2023), 2023, Oxford, United Kingdom

Abstract

In recent years, the new coronavirus pneumonia (COVID-19) has become a worldwide concern and has sparked widespread concern. As a land port between mainland China and Hongkong, Shenzhen suffered from COVID-19 infections early in 2022, which should be given more attention. In this study, we focused on the spatiotemporal distribution at the sub-district level of reported cases from February 1st to April 3rd, which was the period of the first wave of infection in Shenzhen in early 2022. The spatiotemporal distribution map was created first, followed by the introduction of both Global and Anselin local Moran’s I for spatial correlation analysis. The distribution of reported cases showed a high degree of spatial aggregation, demonstrating that the infection was restricted to a limited area, and no significant factors related to the spatial distribution of cases were found in the correlation factors analysis, which might be due to the effectiveness of the control measures. We further explored the characteristics of the Shatou sub-district, the most affected area in Shenzhen. The result showed that population density, sanitation level, and population mobility still had an important impact on the level of epidemic risk. Similar vulnerable areas should receive more attention for the future prevention of diseases.

Citation Download Citation

Yining Huang "Spatiotemporal distribution analysis of the COVID-19 in Shenzhen based on geographic information system", Proc. SPIE 12789, International Conference on Modern Medicine and Global Health (ICMMGH 2023), 1278928 (7 September 2023); https://doi.org/10.1117/12.2692774

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