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Risk assessment of infectious disease epidemic based on fuzzy Bayesian network
Lingmei Fu1, Qing Yang2, Xingxing Liu2
1College of Emergency Management, Nanjing Tech University, Nanjing, Jiangsu, China.
Summary
A new Fuzzy Bayesian Network (FBN) model enhances infectious disease epidemic (IDE) risk assessment by integrating multiple methods to identify key factors like information transfer and quarantine ability.
Area of Science:
- Epidemiology and Public Health
- Computational Modeling
- Risk Management
Background:
- Infectious disease epidemics (IDE) pose significant global health challenges, necessitating robust risk assessment strategies.
- Traditional risk assessment methods often struggle to capture complex causalities and inherent uncertainties in epidemic dynamics.
- Fuzzy Bayesian Networks (FBN) offer a promising approach for modeling complex systems with uncertainty.
Purpose of the Study:
- To develop and validate a novel Fuzzy Bayesian Network (FBN) model for comprehensive infectious disease epidemic (IDE) risk assessment.
- To integrate grounded theory, interpretive structural modeling, and a novel expert weighting algorithm within the FBN framework.
- To quantify uncertainties in IDE risk assessment and identify critical risk factors for effective prevention and control.
Main Methods:
- Development of a novel Fuzzy Bayesian Network (FBN) model incorporating grounded theory, interpretive structural modeling, and a unique expert weighting algorithm.
- Application of the FBN model to assess the COVID-19 outbreak risk in Wuhan, China.
- Sensitivity analysis to pinpoint critical risk factors and quantitative validation using a three-criterion method (variation connection, consistent effect, cumulative limitation).
Main Results:
- The FBN model predicted an 82.26% probability of COVID-19 outbreak in Wuhan, aligning well with the actual situation.
- Key risk factors identified include 'information transfer mechanism,' 'coordination and cooperation among personnel,' 'population flow,' and 'quarantine ability.'
- The model demonstrated effectiveness based on the three-criterion validation method, confirming its reliability.
Conclusions:
- The developed FBN model provides a reliable and effective tool for quantitative risk assessment of infectious disease epidemics (IDE).
- The study highlights critical factors influencing epidemic spread, offering valuable insights for public health decision-making.
- The FBN model demonstrates significant potential for supporting evidence-based strategies in infectious disease prevention and control.
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