  Since the outbreak of COVID-19, it has rapidly evolved into a sudden and
major public health emergency globally. With the variants of COVID-19, the
difficulty of pandemic control continues to increase, which has brought
significant costs to the society. The existing pandemic control zoning method
ignores the impact on residents'lives. In this study, we propose a refined and
low-cost pandemic control method by scientifically delineating zoning areas.
First, a spatial interaction network is built up based on the multimodal
transport travel data in Nanjing, China, and an improved Leiden community
detection method based on the gravity model is used to obtain a preliminary
zoning scheme. Then, we use spatial constraints to correct the results with the
discrete spatial distribution. Finally, reasonable zones for pandemic control
are obtained. The modularity of the algorithm results is 0.4185, proving that
the proposed method is suitable for pandemic control zoning. The proposed
method is also demonstrated to be able to minimize traffic flows between
pandemic control areas and only 24.8% of travel connections are cut off, thus
reducing the impact of pandemic control on residents'daily life and reducing
the cost of pandemic control. The findings can help to inform sustainable
strategies and suggestions for the pandemic control.
