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Application and prospect of Bayesian spatio-temporal model in the study of hydatid disease / 中华地方病学杂志
Chinese Journal of Endemiology ; (12): 341-344, 2022.
Article in Zh | WPRIM | ID: wpr-931548
Responsible library: WPRO
ABSTRACT
With the development of computer technology and the abundance of spatio-temporal data, Bayesian spatio-temporal model (BSTM) has been developed rapidly, and wildly used by academics to investigate the spatial epidemiological feature of infectious diseases. Hydatid disease is a global natural focus disease that seriously endangers human health. Its epidemic process is complex and affected by many factors. BSTM provides a new method for study of hydatid disease. By modeling, we can not only analyze the influencing factors of hydatid disease, but also can predict the epidemic trend and make the disease distribution map, which is of great significance to public health decisionmaking. Based on a comprehensive review of the literatures, this paper expounds the principles, types and application status of BSTM in hydatid disease.
Key words
Full text: 1 Index: WPRIM Type of study: Prognostic_studies Language: Zh Journal: Chinese Journal of Endemiology Year: 2022 Type: Article
Full text: 1 Index: WPRIM Type of study: Prognostic_studies Language: Zh Journal: Chinese Journal of Endemiology Year: 2022 Type: Article