## 2 Materials and Methods
### Requirements, Collection, and Preparation of Data  
As mentioned, this study aims to identify and analyze spatial disparities in the access to the MOH healthcare centers in Jeddah city by measuring spatial accessibility of such services. The original 2 SFCA method executed by the GIS technology was used to calculate spatial accessibility scores by considering the catchment area based on the travel time threshold. Spatial factors (i.e., locations of population, locations of healthcare centers, and travel time) were only used to measure spatial accessibility using the 2 SFCA method. We did not include nonspatial factors in this study (i.e., socioeconomic variables and demographic characteristics of the population) due to a lack of this type of data at the districts level of Jeddah city. However, to achieve the purpose of this study, we captured three GIS coverages, adding their nonspatial data (Table 1). These coverages were (1) healthcare center locations, (2) population districts, and (3) the road network linking between the population threshold and the healthcare centers. As shown in Table 1, some characteristics of roads (i.e., length and speed limit of roads) were added to the attribute table of road network to estimate a travel time for the car-based transportation between the population threshold and the healthcare centers, where the transportation by buses, bikes, and walking is remarkably low in Jeddah city. All of the preceding data were processed in the ArcGIS Software and used to measure the spatial accessibility to healthcare centers in order to identify and analyze disparities of spatial access to such services in Jeddah. The above data were collected from various sources in paper format (data were not digital), then entered into the GIS through the digitization method. First, spatial boundaries of districts and related census data were collected from the report of Jeddah Urban Indicators Production issued by the Jeddah Urban Observatory (JUO) in 2015. To build the database within the ArcGIS Software, the census data were converted from paper format to Excel table by the digitization method. Furthermore, the spatial boundaries of \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dataset** & **Data Type** & **Description** & **Data Format** \\ \hline \multirow{4}{*}{Population} & \multirow{2}{*}{Spatial} & Urban district & \multirow{2}{*}{Polygon} \\  & & boundaries & \\ \cline{3-4}  & & Census data at the & \\  & & level of urban & \\  & & districts: numbers & \\  & & and density of & \\  & & population, etc. & \\ \hline \multirow{4}{*}{MOH healthcare centers} & \multirow{2}{*}{Spatial} & Locations of & \multirow{2}{*}{Point} \\  & & healthcare centers & \\ \cline{1-1} \cline{3-4}  & & Name and location & \\ \cline{1-1} \cline{3-4}  & & address, etc. & \\ \hline \multirow{4}{*}{Road network} & \multirow{2}{*}{Spatial} & Road centerline & \multirow{2}{*}{Line} \\ \cline{3-4}  & & Road ID, name, type, & \\ \cline{1-1} \cline{3-4}  & & length, and speed & \\ \cline{1-1} \cline{3-4}  & & limit of roads, etc. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A summary of data requirements. districts were represented as a polygon format within the ArcGIS Software, where each polygon represents one district that has a unique ID number (record) within the census attribute table. Second, the addresses of the MOH healthcare centers in Jeddah city were identified through the interactive map on the MOH website ([[https://www.moh.gov.sa/Pages/Default.aspx](https://www.moh.gov.sa/Pages/Default.aspx)]([https://www.moh.gov.sa/Pages/Default.aspx](https://www.moh.gov.sa/Pages/Default.aspx))) [accessed on 27 June 2021]. Those were later geo-coded to be the locations of facilities that were represented in a points format within the ArcGIS Software. Each point represents one location that has a unique ID number (record) within the related attribute table.