Epidemic Risk Assessment by a Novel Communication Station Based Method

Area of Science:

• Epidemiology
• Public Health
• Data Science

Background:

• The COVID-19 pandemic necessitates effective control measures for safe work resumption.
• Current methods for assessing individual health conditions and travel history lack granular epidemic risk assessment.
• There is a need for precise and efficient methods to evaluate epidemic risk.

Purpose of the Study:

• To propose a novel method for fine-grained epidemic risk assessment.
• To leverage granular data from communication stations for risk evaluation.
• To enable accurate and efficient assessment of personnel epidemic risk.

Main Methods:

• Computing epidemic risk for communication stations based on infected individuals and their transit patterns.
• Calculating individual personnel risk by analyzing their station trajectory data over time.
• Utilizing granular communication station data for risk assessment.

Main Results:

• The proposed method accurately assesses individual epidemic risk.
• Simulations demonstrate the effectiveness and efficiency of the developed risk assessment approach.
• The method provides a granular understanding of epidemic risk based on movement data.

Conclusions:

• The novel method offers a precise and efficient way to assess epidemic risk.
• This approach supports safe work resumption by providing reliable risk evaluations.
• Granular data analysis from communication stations is crucial for managing public health crises.