Flood-Driven Road Network Disruptions and Their Impact on Healthcare Accessibility in Illinois
Session Number
3
Advisor(s)
Dr. Emma McDaniel, MIT Lincoln Laboratory
Location
A115
Discipline
Computer Science
Start Date
15-4-2026 2:15 PM
End Date
15-4-2026 3:00 PM
Abstract
Extreme rainfall is becoming more frequent and is increasing the risk of transportation disruptions that can delay access to healthcare. Previous studies have measured regions based on different risk indicators in a flood plain. Another study uses these same factors in determining road network access during a flood during COVID-19. This study quantifies the impact of flooding on population accessibility in Illinois by analyzing how road network disruptions affect hospital system service coverage areas. We integrated flood-impacted roads data with the U.S. Census data to assess changes in populations. Using spatial network analysis, we calculated travel-time service areas under normal and flood conditions. By comparing the accessible population totals before and after closures, we determined the number of residents who lost access within standard times. Results are evaluated using population impact and normalization to allow comparison. Then, we removed each flooded road from the complete road network to determine which road was most influential in maintaining the population’s healthcare access. By combining transportation network modeling with demographic data, this research shows information critical for prioritizing infrastructure to healthcare access. The findings can support emergency planning by identifying regions where transportation disruptions create gaps in timely medical care during floods
Flood-Driven Road Network Disruptions and Their Impact on Healthcare Accessibility in Illinois
A115
Extreme rainfall is becoming more frequent and is increasing the risk of transportation disruptions that can delay access to healthcare. Previous studies have measured regions based on different risk indicators in a flood plain. Another study uses these same factors in determining road network access during a flood during COVID-19. This study quantifies the impact of flooding on population accessibility in Illinois by analyzing how road network disruptions affect hospital system service coverage areas. We integrated flood-impacted roads data with the U.S. Census data to assess changes in populations. Using spatial network analysis, we calculated travel-time service areas under normal and flood conditions. By comparing the accessible population totals before and after closures, we determined the number of residents who lost access within standard times. Results are evaluated using population impact and normalization to allow comparison. Then, we removed each flooded road from the complete road network to determine which road was most influential in maintaining the population’s healthcare access. By combining transportation network modeling with demographic data, this research shows information critical for prioritizing infrastructure to healthcare access. The findings can support emergency planning by identifying regions where transportation disruptions create gaps in timely medical care during floods