Research on Early Warning of Transmission of Tuberculosis Infectious Diseases from the Perspective of Social Factors

In this study, the infiltration model was established to study the early warning of pulmonary tuberculosis data in Xiamen public hospitals. Based on the gender characteristics of residents in Xiamen, a percolation model was established to analyze the transmission rates of diseases under different co...

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Bibliographic Details
Published in:Journal of advanced computational intelligence and intelligent informatics 2024-05, Vol.28 (3), p.739-745
Main Authors: Zhu, Miao, Li, Xiyi, Zhang, Xingyue, Dong, Xiaoyu
Format: Article
Language:English
Subjects:
Disease prevention
Emergency communications systems
Epidemics
Infections
Infectious diseases
Pandemics
Pathogens
Percolation
Social networks
Tuberculosis
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Summary:In this study, the infiltration model was established to study the early warning of pulmonary tuberculosis data in Xiamen public hospitals. Based on the gender characteristics of residents in Xiamen, a percolation model was established to analyze the transmission rates of diseases under different contact types. In addition, the calculation method of the percolation threshold is discussed, and the model is verified by a simulation experiment. The results show that the model can predict the spread of epidemic situations well. The early warning value and relevant preventive measures were obtained by simulating the spread of tuberculosis under different exposure numbers. Bond percolation analysis was used to predict the proportion of the eventually infected population, this threshold of percolation was the basic regeneration number of tuberculosis, and the tuberculosis infection situation was effectively predicted.
ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2024.p0739