Senior Community Resilience with a Focus on Critical Transportation Infrastructures: An Accessibility-Based Approach to Healthcare

Abstract

The importance of bridges to mobility in transportation is well known. However, the identification of bridges that influence the mobility of senior members of communities has not been evaluated. This is imperative because of human frailties associated with aging. In this paper, senior community resilience is assessed through accessibility of seniors to hospitals after bridge damage caused by hurricane events using Pinellas County in the Tampa Bay area as case study. The paper presents: (i) exposure probabilities for hurricane events at bridge locations; (ii) bridge damage state functions and damage state rating assignments using historical data from the National Bridge Inventory database; (iii) identification of bridges at risk of hurricane-induced damage; (iv) bridges identified as serving areas (census districts) with dense population of aging people; and (v) estimated effects of bridge closures on mobility and resilience of the aged population, based on accessibility to hospitals by using congested and free-flow travel times obtained from traffic assignment modeling. Findings showed that: (i) 66 bridges prone to hurricane-induced damage were observed to affect 140 selected aging population areas; (ii) bridge closures resulted in about 15% and 75% increase in free-flow and congested travel times, respectively; (iii) complete loss of accessibility to hospitals for some aging-dense zones; and (iv) resilience indexes of 0.94 and 0.81 were computed for free-flow and congested travel times, respectively. These results highlight significant loss in senior accessibility to hospitals and emphasize the need for policy discussions on the capabilities of highway bridges for efficient senior mobility.

Residential Preferences of Post Great Disaster in Palu City, Indonesia

“…Nurhadi 3) Environment Ground Movement Prone (X8) ISO:37120 29) Liquefaction prone (X9) Tsunami-prone (X10) Fault Prone (X11) Flood prone (X12) Azizah et al 30) , Ridzuan et al 31) Land prices (X14) Chirisa 32) Infrastructure Accessibility (X15) Twumasi-Boakye et al 33) Distance to the city center (X16) Awotona 34) Road conditions (X17)…”

Infrastructure resilience curves: Performance measures and summary metrics

“…Efficacy measures, when normalized in the literature, used independent performance targets. As previously highlighted, constant [83], [136], [146], [177] or variable [24], [33] targets represent typical or ideal performance, both of which are independent from a resilience scenario. Although not identified in the literature, adaptive targets may be appropriate when standards of service vary during distinct phases of the scenario.…”

“…normalized travel delays with pre-disruption travel time in the numerator [146]: 𝐹𝐹 ′ (𝑡𝑡) = 𝐹𝐹 0 /𝐹𝐹(𝑡𝑡). Alternatively, the vertical axis could be flipped (e.g., when flood volume is the performance measure [177]).…”

Resilience of Regional Transportation Networks Subjected to Hazard-Induced Bridge Damages

“…The original resilience triangle proposed by Bruneau et al (2003) depicts this clearly. In the context of transportation networks, high performance loss coupled with long recovery times does not only lead to increased transportation user costs, but also accessibility related to societal impacts, especially among aging or frail groups (Twumasi-Boakye et al 2018). This approach ensures that resilience is not solely defined by functionality losses (a measure of importance), but weighted by the best-and worst-case representations of time to recovery.…”

“…The area for this study is known as the Tampa Bay Region in Florida; an area prone to hurricane strikes and storm surges as seen in Fig. 2 debilitating impact on the transportation network, leading to potential accessibility issues (Twumasi-Boakye et al 2018). Details of the transportation network configuration and regional model are subsequently discussed in this paper.…”