Spatial Interaction Analysis of Infectious Disease Import and Export between Regions

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Human travel is a primary driver for the geographic dissemination of infectious diseases.
• Understanding the relationship between travel patterns and disease spread is critical for effective public health interventions.
• The COVID-19 pandemic highlighted the urgent need for quantitative tools to assess travel-related disease transmission risks.

Purpose of the Study:

• To develop and apply novel models and metrics for analyzing the role of inter-regional travel in disease spread.
• To quantify the risk of infectious disease (COVID-19) transmission between different regions within the United States.
• To provide a tool for policymakers to inform epidemic control strategies by evaluating travel's influence on disease dynamics.

Main Methods:

• Development of a multi-regional, time-varying compartmental disease model incorporating spatial interactions.
• Integration of the compartmental model with statistical estimates of inter-regional travel data.
• Derivation of a 'transmission import index' to assess and rank the risk of disease introduction between states.

Main Results:

• Identification of specific US states posing a high risk for spreading COVID-19 to other states over monthly timescales.
• Analysis of temporal variations in the transmission import index throughout 2020, illustrating dynamic risk patterns.
• Quantification of the relative contribution of inter-regional travel to overall disease transmission dynamics.

Conclusions:

• Inter-regional travel is a significant factor in the spatiotemporal spread of infectious diseases like COVID-19.
• The developed transmission import index offers a valuable metric for assessing and predicting disease spread risk.
• The model serves as a crucial tool for public health officials to design targeted interventions and manage epidemic control efforts effectively.