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Modeling the COVID-19 Pandemic Using an SEIHR Model With Human Migration
Ruiwu Niu1, Eric W M Wong1, Yin-Chi Chan1
1Department of Electrical EngineeringCity University of Hong Kong Hong Kong China.
IEEE Access : Practical Innovations, Open Solutions
|January 3, 2022
Summary
A modified SEIHR model reveals that asymptomatic COVID-19 transmission is key to disease spread. Strict interventions, not just border control, are crucial for managing outbreaks and predicting waves.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Infectious Disease Dynamics
Background:
- The COVID-19 pandemic highlights challenges in controlling disease spread due to asymptomatic and pre-symptomatic transmission.
- International travel and globalization facilitate rapid, widespread epidemics.
Purpose of the Study:
- To develop and validate a modified SEIHR model incorporating human migration to accurately represent COVID-19 spread.
- To analyze the impact of asymptomatic transmission and migration on epidemic dynamics.
- To evaluate the effectiveness of different public health interventions.
Main Methods:
- Developed a susceptible-exposed-infected-hospitalized-removed (SEIHR) compartmental model.
- Included human migration parameters to simulate inter-regional spread.
- Derived the basic reproduction number (R0) and analyzed parameter sensitivity.
- Validated the model using historical COVID-19 data, including Hong Kong.
- Simulated intervention strategies like isolation and border control.
Main Results:
- Asymptomatic (exposed) individuals significantly influence COVID-19 transmission rates.
- High migration rates can slow local spread but risk infecting neighboring regions.
- Strict isolation measures are more effective than border closures for controlling epidemic speed.
- The SEIHR model accurately predicted the third wave of COVID-19 in Hong Kong.
Conclusions:
- Asymptomatic transmission is a critical factor in COVID-19's rapid spread.
- Targeted interventions focusing on isolation are vital for effective epidemic control.
- Mathematical modeling, like the SEIHR approach, is essential for understanding and predicting infectious disease outbreaks.
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