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

Abstract

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.

Spatiotemporal Pattern and Its Determinants for Newly Reported HIV/AIDS Among Older Adults in Eastern China From 2004 to 2021: Retrospective Analysis Study

“…The OLS model requires the data to be independently distributed, and the results are global estimates of the parameters that do not reflect the pattern of change in the data with geographical location. The GWR model embeds the spatial location of the data into regression parameters and uses local weighted least squares to estimate the parameters, which is a local statistical model [ 17 ]. In the presence of spatial autocorrelation, the traditional OLS model is not applicable to data analysis.…”

Air Pollution and Meteorological Parameters in SARS-CoV-2 Virus Spread and Transition

“…One of the most reported pollutants correlated with this virus in papers is PM [5,40]. It has been found that PM2.5 was negatively correlated with SARS-CoV-2 cases while PM10 demonstrated not to be signifi cant with infection cases [41,42]. This could indicate that PM does not act as a carrier of virions, but airborne derived from water vapor does.…”

Visible minority status and occupation were associated with increased COVID-19 infection in Greater Vancouver British Columbia between June and November 2020: an ecological study

“…However, conventional regression methods ignore the spatial dependence between the geographical units under study, which is essential to understanding relationships for infectious disease. As a result, various studies have been developed to analyze the spatial determinants of the spread of COVID-19 across different geographies (16)(17)(18)(19).…”