**2. Data and methodology**

#### **2.1 Dependent variable and the selection of socio-economic variables**

This study uses the total number of confirmed COVID-19 cases per 100,000 population from 81 Turkish provinces as the dependent variable. This data is publicly available and reported as weekly averages by the Turkish Ministry of Health.

To be able to determine which explanatory variables might be important in the spread of Covid-19, we examine thoroughly the previous literature that applies both a spatial and non-spatial analysis. Bassino and Ladmiral [25] argue economic variables like wealth or income are the main drivers of the person-to-person spread of infectious diseases such as COVID-19. Bassino and Ladmiral [26] demonstrate that low literacy has been influential in the spread of the disease. Sun et al. [17, 27] find that age is effective on the spread of COVID-19 cases. Population and population density were also noted as significant variables by [15, 25, 28, 29]. The number of doctors and the number of hospital beds are considered important factors by [3, 25, 26] because their availability has the potential to draw more COVID-19 patients to the area. Living in an urban vs. rural area might be another determinant in the spread of cases as noted by [25, 29]. Ehlert [15] also considers household size as a factor. Social life indicators and average space available per household are used by [25].

We proxy the socioeconomic and health status of each province that is noted in the literature by using the Life Index in Provinces provided by the Turkish Statistical Institute in 2016. This index is produced based on the approach of the OECD Better Life Index. The aim of the Life Index in Provinces is to compare the well–being and living quality of Turkish provinces as well as their economic status. To do so, 11 leading indicators and 41 sub–indicators that include both objective and subjective
