2010/05/11 by Teruhiko Yoneyama, Yoneyama, Teruhiko, Mukkai S. Krishnamoorthy +1
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Physics and Astronomy · #COVID-19 epidemiological studies #Complex Network Analysis Techniques #Data-Driven Disease Surveillance #FOS: Biological sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Populations and Evolution (q-bio.PE) #physics.soc-ph #q-bio.PE
paper · pdf · doi:10.48550/arxiv.1006.0018
arxiv created 2010/05/11 · openalex publication_date 2010/05/11 · arxiv updated 2010/06/02 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28
Pandemics have the potential to cause immense disruption and damage to communities and societies. In this paper, we model the Influenza Pandemic of 2009. We propose a hybrid model to determine how the pandemic spreads through the world. The model considers both the SEIR-based model for local areas and the network model for global connection between countries referring to data on international travelers. Our interest is to reproduce the situation using the data of early stage of pandemic and to predict the future transition by extending the simulation cycle. Without considering the tendency of seasonal flu, the simulation does not predict the second peak of the pandemic in the real world. However, considering the seasonal tendency, the simulation result predicts the next peak in winter. Thus we consider the seasonal tendency is an important factor for the spreading of the pandemic.