Causality Network of Infectious Disease Revealed with Causal Decomposition

Jingpeng Sun, Kai Yuan, Chen Chen, Heng Xu, Hesong Wang, Yuxing Zhi, Silong Peng, Chung Kang Peng, Norden Huang, Guangrui Huang, Albert Yang

研究成果: Article同行評審

2 引文 斯高帕斯(Scopus)

摘要

Causal inference in the field of infectious disease attempts to gain insight into the potential causal nature of an association between risk factors and diseases. Simulated causality inference experiments have shown preliminary promise in improving understanding of the transmission of infectious diseases but still lack sufficient quantitative causal inference studies based on real-world data. Here, we investigate the causal interactions between three different infectious diseases and related factors, us-ing causal decomposition analysis, to characterize the na-ture of infectious disease transmission. We show that the complex interactions between infectious disease and hu-man behavior have a quantifiable impact on transmission efficiency of infectious diseases. Our findings, by shedding light on the underlying transmission mechanism of infec-tious diseases, suggest that causal inference analysis is a promising approach to determine epidemiological interventions.

原文English
頁(從 - 到)1-10
頁數10
期刊IEEE Journal of Biomedical and Health Informatics
DOIs
出版狀態Accepted/In press - 2023

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