Geographically weighted regression model for physical, social, and economic factors affecting the COVID-19 pandemic spreading

Jasim, Ihsan Abbas; Fileeh, Moheb Kamil; Ebrahhem, Mustafa A.; Al-Maliki, Laheab A.; Al-Mamoori, Sohaib K.; Anṣārī, Naẓīr

Geographically weighted regression model for physical, social, and economic factors affecting the COVID-19 pandemic spreading

2022

This study aims to analyze the spatial distribution of the epidemic spread and the role of the physical, social, and economic characteristics in this spreading. A geographically weighted regression (GWR) model was built within a GIS environment using infection data monitored by the Iraqi Ministry of Health records for 10 months from March to December 2020. The factors adopted in this model are the size of urban interaction areas and human gatherings, movement level and accessibility, and the volume of public services and facilities that attract people. The results show that it would be possible to deal with each administrative unit in proportion to its circumstances in light of the factors that appear in it. So, there will not be a single treatment for all areas with different urban characteristics, which sometimes helps not to stop social and economic life due to the imposition of a comprehensive ban on movement and activities. Therefore, there will be other supportive policies other than the ban, depending on the urban indicators for each region, such as reducing external movement from it or relying on preventing public activities only.

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