Research on the Discovery of Timing Causal Structure in Epidemic Prevention and Control

Tengjiao Mao, Chunxiao Cai, Yue Lu, Ruihua Wang, Wei Liu

2022

Abstract

Decision-makers need to timely and accurately identify departments with unfavorable handling based on the effect of epidemic prevention and control, which requires the construction of a timing causal structure between departments. In consideration of a large number of departments and influencing factors involved, traditional algorithms are more costly to construct causal structures. In this paper, the departments involved in epidemic prevention and control and related factors are analyzed. A causality analysis framework based on Bayesian networks is proposed. The dimensionality of data is reduced based on time-varying characteristics. Bayesian network structure learning algorithms are used to build a structural model based on timing causality. The results of the simulation case show that the method takes the advantage of fast convergence and accurate causality.

Paper Citation

in Harvard Style

Mao T., Cai C., Lu Y., Wang R. and Liu W. (2022). Research on the Discovery of Timing Causal Structure in Epidemic Prevention and Control. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 386-392. DOI: 10.5220/0011737900003607

in Bibtex Style

@conference{icpdi22,
author={Tengjiao Mao and Chunxiao Cai and Yue Lu and Ruihua Wang and Wei Liu},
title={Research on the Discovery of Timing Causal Structure in Epidemic Prevention and Control},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={386-392},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011737900003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - Research on the Discovery of Timing Causal Structure in Epidemic Prevention and Control
SN - 978-989-758-620-0
AU - Mao T.
AU - Cai C.
AU - Lu Y.
AU - Wang R.
AU - Liu W.
PY - 2022
SP - 386
EP - 392
DO - 10.5220/0011737900003607
PB - SciTePress