Study on geographical characteristics and influencing factors of scarlet fever based on Bayesian hierarchical spatio-temporal model and geodetector

Wang Man; Xianqiang Wei; Junhao Sun

doi:10.1117/12.3007396

30 August 2023 Study on geographical characteristics and influencing factors of scarlet fever based on Bayesian hierarchical spatio-temporal model and geodetector

Wang Man, Xianqiang Wei, Junhao Sun

Author Affiliations +

Proceedings Volume 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023); 127970C (2023) https://doi.org/10.1117/12.3007396
Event: 2nd International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 2023, Qingdao, China

Abstract

With the improvement of living standards, health issues are particularly concerned by people. Scarlet fever is an infectious disease with high incidence among children. The research direction of scarlet fever has gradually shifted from clinical research to spatial-temporal analysis of geography. In this study, the number of scarlet fever cases from 2013 to 2018 was obtained from China Public Health Science Data Center, combined with social factor data as relevant variables, and analyzed using spatial autocorrelation, Bayesian hierarchical spatio-temporal models, and Geodetector. Research shows that scarlet fever presents regional characteristics in China with the Qinling Mountains-Huaihe River Line as the boundary, and the cities north of the line have a higher risk of disease than cities south of the line. At the same time, traffic factors are the most important non-weather factors affecting the risk of scarlet fever. Therefore, the cities north of the boundary need to pay more attention to the risk of scarlet fever and take preventive measures when traveling to reduce the risk of infection.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wang Man, Xianqiang Wei, and Junhao Sun "Study on geographical characteristics and influencing factors of scarlet fever based on Bayesian hierarchical spatio-temporal model and geodetector", Proc. SPIE 12797, Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023), 127970C (30 August 2023); https://doi.org/10.1117/12.3007396

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