This study employed location-allocation modeling and a geographic information system (GIS) to study the current placement of automated external defibrillators (AEDs) in relationship to neighborhoods in Riyadh City, Saudi Arabia, and to determine the optimal locations for additional AEDs in the city. Using GIS to mathematically locate additional healthcare facilities for the placement of AEDs is more reliable than to select them using informed guesses. The objective of this research was to elaborate a mathematical and GIS model for placing AED devices so that people who need to use these devices in the City of Riyadh, Saudi Arabia, can access them within a time frame of three minutes or less, which is the international standard for such accessibility. The research employed street blocks as demand points; existing healthcare facilities, mosques, and schools as supply points; and the maximum coverage algorithm to model optimal locations for AED devices. Models were run for both vehicle and pedestrian travel times. Model results of current conditions indicated that 75% of household blocks were covered when vehicles were used to access AED sites, as compared to 9% of people when pedestrian travel to an AED is considered. Introduction of 1,371 mosques and 34 community colleges and universities as additional supply points for AEDs improved coverage to 94% for vehicular access, but only 34% for pedestrian traffic. Although mosques are considered to be focus points for Muslim communities, other facilities including, but not limited to, police stations, malls, primary and secondary schools, and playgrounds should be used to gain wider coverage. In addition, cluster analysis should be employed to avoid selecting AED supply points that are too close to each other and which are unlikely to improve accessibility. The study succeeded in elaborating a framework for conceptualizing the relationship between vehicular and pedestrian access to AEDs. It also demonstrates how GIS-based location-allocation modeling can be used for efficient placement of AEDs. The broad conceptual framework for AED placement used in this study has applicability to other countries in the Middle East.
","abstract_html":"<p>This study employed location-allocation modeling and a geographic information system (GIS) to study the current placement of automated external defibrillators (AEDs) in relationship to neighborhoods in Riyadh City, Saudi Arabia, and to determine the optimal locations for additional AEDs in the city. Using GIS to mathematically locate additional healthcare facilities for the placement of AEDs is more reliable than to select them using informed guesses. The objective of this research was to elaborate a mathematical and GIS model for placing AED devices so that people who need to use these devices in the City of Riyadh, Saudi Arabia, can access them within a time frame of three minutes or less, which is the international standard for such accessibility. The research employed street blocks as demand points; existing healthcare facilities, mosques, and schools as supply points; and the maximum coverage algorithm to model optimal locations for AED devices. Models were run for both vehicle and pedestrian travel times. Model results of current conditions indicated that 75% of household blocks were covered when vehicles were used to access AED sites, as compared to 9% of people when pedestrian travel to an AED is considered. Introduction of 1,371 mosques and 34 community colleges and universities as additional supply points for AEDs improved coverage to 94% for vehicular access, but only 34% for pedestrian traffic. Although mosques are considered to be focus points for Muslim communities, other facilities including, but not limited to, police stations, malls, primary and secondary schools, and playgrounds should be used to gain wider coverage. In addition, cluster analysis should be employed to avoid selecting AED supply points that are too close to each other and which are unlikely to improve accessibility. The study succeeded in elaborating a framework for conceptualizing the relationship between vehicular and pedestrian access to AEDs. It also demonstrates how GIS-based location-allocation modeling can be used for efficient placement of AEDs. The broad conceptual framework for AED placement used in this study has applicability to other countries in the Middle East.</p>","abstract_has_math":false,"creators":["Magzoub, Abubakr Abdelkafi"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Open Access Dissertation","degree_discipline":"College of Technology","degree_department":null,"school":null,"contributors":["William F. Welsh, PhD","Hugh Semple, PhD","John Dugger, PhD"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-01-01T08:00:00Z","date_published":"2018-01-01T08:00:00Z","updated_at":"2026-07-24T02:17:33Z","subjects":["Automated external defibrillator (AED)","Geographic information system (GIS)","Out of Hospital Cardiac Arrests (OHCA)","Riyadh","Saudi Arabia","Geographic Information Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.emich.edu/theses/935","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["William F. Welsh, PhD","Hugh Semple, PhD","John Dugger, PhD"]},{"key":"dc:creator","label":"Author","values":["Magzoub, Abubakr Abdelkafi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-01-09T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["College of Technology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Automated external defibrillator (AED)","Geographic information system (GIS)","Out of Hospital Cardiac Arrests (OHCA)","Riyadh","Saudi Arabia","Geographic Information Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.emich.edu/theses/935"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["This study employed location-allocation modeling and a geographic information system (GIS) to study the current placement of automated external defibrillators (AEDs) in relationship to neighborhoods in Riyadh City, Saudi Arabia, and to determine the optimal locations for additional AEDs in the city. Using GIS to mathematically locate additional healthcare facilities for the placement of AEDs is more reliable than to select them using informed guesses. The objective of this research was to elaborate a mathematical and GIS model for placing AED devices so that people who need to use these devices in the City of Riyadh, Saudi Arabia, can access them within a time frame of three minutes or less, which is the international standard for such accessibility. The research employed street blocks as demand points; existing healthcare facilities, mosques, and schools as supply points; and the maximum coverage algorithm to model optimal locations for AED devices. Models were run for both vehicle and pedestrian travel times. Model results of current conditions indicated that 75% of household blocks were covered when vehicles were used to access AED sites, as compared to 9% of people when pedestrian travel to an AED is considered. Introduction of 1,371 mosques and 34 community colleges and universities as additional supply points for AEDs improved coverage to 94% for vehicular access, but only 34% for pedestrian traffic. Although mosques are considered to be focus points for Muslim communities, other facilities including, but not limited to, police stations, malls, primary and secondary schools, and playgrounds should be used to gain wider coverage. In addition, cluster analysis should be employed to avoid selecting AED supply points that are too close to each other and which are unlikely to improve accessibility. The study succeeded in elaborating a framework for conceptualizing the relationship between vehicular and pedestrian access to AEDs. It also demonstrates how GIS-based location-allocation modeling can be used for efficient placement of AEDs. The broad conceptual framework for AED placement used in this study has applicability to other countries in the Middle East.
"]},{"key":"dc:title","label":"Title","values":["Preparing for out of hospital cardiac arrests (OHCA) in Riyadh, Saudi Arabia: A GIS scenario-modeling approach"]}]}],"canonical_facts":{"dc:contributor":["William F. Welsh, PhD","Hugh Semple, PhD","John Dugger, PhD"],"dc:creator":["Magzoub, Abubakr Abdelkafi"],"dc:date.available":["2019-01-09T08:00:00Z"],"dc:description.abstract":["This study employed location-allocation modeling and a geographic information system (GIS) to study the current placement of automated external defibrillators (AEDs) in relationship to neighborhoods in Riyadh City, Saudi Arabia, and to determine the optimal locations for additional AEDs in the city. Using GIS to mathematically locate additional healthcare facilities for the placement of AEDs is more reliable than to select them using informed guesses. The objective of this research was to elaborate a mathematical and GIS model for placing AED devices so that people who need to use these devices in the City of Riyadh, Saudi Arabia, can access them within a time frame of three minutes or less, which is the international standard for such accessibility. The research employed street blocks as demand points; existing healthcare facilities, mosques, and schools as supply points; and the maximum coverage algorithm to model optimal locations for AED devices. Models were run for both vehicle and pedestrian travel times. Model results of current conditions indicated that 75% of household blocks were covered when vehicles were used to access AED sites, as compared to 9% of people when pedestrian travel to an AED is considered. Introduction of 1,371 mosques and 34 community colleges and universities as additional supply points for AEDs improved coverage to 94% for vehicular access, but only 34% for pedestrian traffic. Although mosques are considered to be focus points for Muslim communities, other facilities including, but not limited to, police stations, malls, primary and secondary schools, and playgrounds should be used to gain wider coverage. In addition, cluster analysis should be employed to avoid selecting AED supply points that are too close to each other and which are unlikely to improve accessibility. The study succeeded in elaborating a framework for conceptualizing the relationship between vehicular and pedestrian access to AEDs. It also demonstrates how GIS-based location-allocation modeling can be used for efficient placement of AEDs. The broad conceptual framework for AED placement used in this study has applicability to other countries in the Middle East.
"],"dc:identifier":["https://commons.emich.edu/theses/935"],"dc:subject":["Automated external defibrillator (AED)","Geographic information system (GIS)","Out of Hospital Cardiac Arrests (OHCA)","Riyadh","Saudi Arabia","Geographic Information Sciences"],"dc:title":["Preparing for out of hospital cardiac arrests (OHCA) in Riyadh, Saudi Arabia: A GIS scenario-modeling approach"],"thesis:degree_discipline":["College of Technology"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T02:17:33Z"}