Geostatistical assessment of the built environment and spatio-temporal distribution patterns of COVID-19 cases in Istanbul, Turkiye

This study aims to investigate the geostatistical relationships between the built environment at the neighborhood level and the spatio-temporal distribution patterns of COVID-19 cases. Istanbul, Turkiye, one of the most highly populated metropolitan cities in the world, was chosen as the study area. Clustering and Outlier Analysis (Anselin Local Moran's I), correlation analysis, and Geographically Weighted Regression (GWR) are utilized for testing the relationships between land use types, land use diversity, and net population density, representing the built environment and the intensity of COVID-19 cases. Spatial patterns of selected regions with high exposure to COVID-19 are also interpreted, and place-based outcomes are presented. Results are supported by and discussed with descriptive statistics. Land-use diversity, net population density, green areas, commercial areas, and commercial-residential areas are determined to be the predominant determinants of the spatio-temporal distri-bution of COVID-19 cases in Istanbul. Based on the GWR model, green areas are found to be the variable having the highest effect on the neighborhoods. Land use diversity and commercial areas are the other two prominent variables that affect the high exposure to COVID-19 cases in a neighborhood and its surroundings. Relevantly, it can be concluded that the neighborhood effect plays a crucial role in the spread of and high exposure to COVID-19. The findings of the study will guide the development of design and planning criteria to overcome risk factors such as pandemics in spatial planning decisions at the neighborhood level for cities.