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

Chong-En Li, Zih-Hong Lin, Yi-Ya Hsu, Nae-Wen Kuo
Author Information
  1. Chong-En Li: Department of Geography, National Taiwan Normal University, Taipei, Taiwan.
  2. Zih-Hong Lin: School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia.
  3. Yi-Ya Hsu: School of Built Environment, University of New South Wales, Sydney, NSW 2052, Australia.
  4. Nae-Wen Kuo: Department of Geography, National Taiwan Normal University, Taipei, Taiwan.

Abstract

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  = 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  = 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.

Keywords

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Word Cloud

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