Using GIS to Understand the Influence of Hurricane Harvey on Spatial Access to Primary Care

An integrated approach to analyze equitable access to food stores under disasters from human mobility patterns

Limited access to food stores is often linked to higher health risks and lower community resilience. Socially vulnerable populations experience persistent disparities in equitable food store access. However, little research has been done to examine how people's access to food stores is affected by natural disasters. Previous studies mainly focus on examining potential access using the travel distance to the nearest food store, which often falls short of capturing the actual access of people. Therefore, to fill this gap, this paper incorporates human mobility patterns into the measure of actual access, leveraging large-scale mobile phone data. Specifically, we propose a novel enhanced two-step floating catchment area method with travel preferences (E2SFCA-TP) to measure accessibility, which extends the traditional E2SFCA model by integrating actual human mobility behaviors. We then analyze people's actual access to grocery and convenience stores across both space and time under the devastating winter storm Uri in Harris County, Texas. Our results highlight the value of using human mobility patterns to better reflect people's actual access behaviors. The proposed E2SFCA-TP measure is more capable of capturing mobility variations in people's access, compared with the traditional E2SFCA measure. This paper provides insights into food store access across space and time, which could aid decision making in resource allocation to enhance accessibility and mitigate the risk of food insecurity in underserved areas.

Lessons from COVID-19 pandemic: Analysis of unequal access to food stores using the Gini coefficient

COVID-19 has dramatically altered daily life worldwide, with some urban residents resorting to panic buying at the beginning of the pandemic. Large-scale lockdowns and restaurant closures have increased the need for grocery shopping. Such shifts in consumer patterns have altered supply-demand systems. Insufficient food store availability increases the likelihood of crowding and thus increases the probability of viral infection. People who live without easy access to food stores also face high infection risks when forced to travel long distances for grocery shopping. The COVID-19 pandemic has demonstrated the importance of the number and distribution of food stores to virus transmission. Food access is also a core factor of urban resilience during the pandemic. This study used the Gini coefficient to investigate the fairness of accessibility to food stores at the city and village levels, with Taipei City chosen as the research area. Different spatial scales were considered, and we calculated the equality of food access for older (≥65 years old) and non-older populations separately to determine whether one group faces greater inequality. At the city level, both older and non-older populations in Taipei have reasonable access (Gini coefficient between 0.3 and 0.4), with mean Gini coefficients of 0.3616 and 0.3655, respectively. This city-level analysis represents the overall degree of unequal access to food stores. At the village level, eight villages (1.8 %; total N = 456) had severe access inequality (Gini coefficient > 0.6) for older adults; they are located primarily in downtown or suburban areas. For the non-older population, only two villages (0.4 %; total N = 456) in suburban areas exhibit severe access inequality. The village-level analysis identified villages with low equality of access to food stores and revealed local problems that cannot be observed at the city level.