Fig 8 -

Nightingale rose diagram illustrating the variation in Baidu migration and emigration indices during different periods in Xiamen (a: Jan 1–Mar 15, b: Jan 1–Jan 22, c: Jan 23–Feb 15, d: Feb 16–Mar 15). The green area indicates the range of the index, while the red line signifies the mean migration index for each period.</p

Data on Baidu migration and emigration across different time periods in Xiamen.

Data on Baidu migration and emigration across different time periods in Xiamen.</p

Prediction of COVID-19 progression in Xiamen using the SEIR model.

Prediction of COVID-19 progression in Xiamen using the SEIR model.</p

Comparative population density across various regions during distinct periods.

Comparative population density across various regions during distinct periods.</p

Diagram illustrating the proposed approach’s framework.

Diagram illustrating the proposed approach’s framework.</p

Contains the Table B1.

The outbreak of the Coronavirus Disease 2019 (COVID-19) has profoundly influenced daily life, necessitating the understanding of the relationship between the epidemic’s progression and population dynamics. In this study, we present a data-driven framework that integrates GIS-based data mining technology and a Susceptible, Exposed, Infected and Recovered (SEIR) model. This approach helps delineate population dynamics at the grid and community scales and analyze the impacts of government policies, urban functional areas, and intercity flows on population dynamics during the pandemic. Xiamen Island was selected as a case study to validate the effectiveness of the data-driven framework. The results of the high/low cluster analysis provide 99% certainty (P </div

Data on Baidu migration and immigration across various time periods in Xiamen.

Data on Baidu migration and immigration across various time periods in Xiamen.</p

Fig 7 -

Nightingale rose diagram depicting Baidu migration and immigration indices during different periods in Xiamen (a: Jan 1–Mar 15, b: Jan 1–Jan 22, c: Jan 23–Feb 15, d: Feb 16–Mar 15). The green area signifies the range of the index, while the red line indicates the mean of the migration index.</p

Projection of the SEIR model for Xiamen, comparing scenarios before and after the lockdown implemented on February 2.

Projection of the SEIR model for Xiamen, comparing scenarios before and after the lockdown implemented on February 2.</p

Prediction of the SEIR model for Xiamen City before and after lockdown implementation.

Prediction of the SEIR model for Xiamen City before and after lockdown implementation.</p