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Global age-structured spatial modeling for emerging infectious diseases like COVID-19
Yixiong Xiao1, Jingbo Zhou1, Qu Cheng2
1Business Intelligence Lab, Baidu Research, Beijing 100193, China.
PNAS Nexus
|May 5, 2023
Summary
Emerging infectious diseases (EIDs) can cause severe global impacts without mitigation. Global pandemic preparedness requires collective international efforts, especially from developed nations, to effectively control disease spread.
Area of Science:
- Epidemiology
- Global Health
- Computational Biology
Background:
- Emerging infectious diseases (EIDs) pose significant global threats.
- Existing age-structured models often lack global spatial dynamics.
- Characterizing worldwide EID spread is crucial for pandemic preparedness.
Purpose of the Study:
- To develop a global pandemic simulator integrating age-structured transmission models.
- To explore the spatial spread and impact of EIDs across multiple cities worldwide.
- To assess the effectiveness of mitigation strategies on a global scale.
Main Methods:
- Developed a global pandemic simulator incorporating age-structured disease transmission models.
- Integrated models across 3,157 cities to simulate EID dynamics.
- Explored various scenarios to analyze disease spread and impact.
Main Results:
- Without interventions, EIDs like COVID-19 are predicted to have severe global consequences.
- Pandemics seeded in various locations show similar severe impacts within one year.
- Global mitigation efforts are significantly undermined by inaction in developed or nearby countries.
Conclusions:
- Strengthening global infectious disease monitoring is essential for early outbreak detection.
- Effective pandemic mitigation necessitates coordinated international cooperation.
- The passive response of developed nations can critically affect global pandemic outcomes.
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