Distributional impact of COVID-19: regional inequalities in cases and deaths in Spain during the first wave

Abstract

Spain is being hit hard by the COVID-19 pandemic. During the first wave, from mid-March to early June 2020, the disease caused nearly 30,000 deaths in a population of 47 million. This article quantifies the unevenness in the distribution of epidemiological variables across the Spanish territory. The study is relevant because Spain is divided into regions that hold devolved authority for providing health care services to their citizens. Using inequality metrics, the study shows: i) By mid-April inequality in the epidemiological variables reached a stationary value that changed little with the incorporation of new cases and deaths. At the end of the outbreak, cumulative cases and deaths were fairly unevenly distributed across Spanish provinces; ii) Inequality shows a monotonic downward trend throughout the outbreak showing a decrease from the onset to the end ranging from 22% to 49% in cases and between 17% and 42% in deaths; iii) Over 90% of the inequality observed can be attributed to differences between regions, while less than 10% is due to the differences across provinces within regions. Awareness of the existence and nature of the inequality observed in the epidemiological variables is needed to develop successful policies to improve health services in Spain.

The Unequal Effect of the COVID-19 Pandemic on the Labour Market and Income Inequality in China: A Multisectoral CGE Model Analysis Coupled with a Micro-Simulation Approach

“…By affecting the per capita income of different households, the COVID-19 pandemic likely increased income inequality in China. On the one hand, rural residents may suffer greater income losses relative to urban residents, as rural workers are less employed on a salary basis, and migrant workers from rural areas are confined to their villages and unable to return to work in cities [8,20]. The sudden reduction or halt in remittance flows from migrant workers would further reduce the income of rural households [21,35].…”

“…As the employment and earnings of labourers with low education levels are more significantly reduced, the pandemic would have a greater negative impact on the income of low-income households than their more advantaged counterparts [17][18][19]. Strict disease control measures hindered migrant workers from returning to work, reduced the income of rural households, and aggravated the income disparity between rural and urban households [8,20,21]. Hence, the second hypothesis is that income inequality would be aggravated by the COVID-19 pandemic.…”

“…Hence, the second hypothesis is that income inequality would be aggravated by the COVID-19 pandemic. Although several studies have preliminarily analysed the distributional effects of the pandemic in developed countries [10,12,20], the unequal impact of the pandemic on China's labour market and income inequality has been scarcely explored.…”

Investigating the two-way relationship between mobility flows and COVID-19 cases

“…For the arrivals equation, these FEs capture factors that determine mobility flows like connectivity between provinces and their geographical position ( Brinkman and Mangum, 2022 ), the sociodemographic structure of the population ( Engle et al, 2020 ), the degree of economic activity and structure of labour markets for business trips, and regional attractiveness for leisure trips, among others. For the cases equation, the FEs control for aspects like the population density ( Orea and Alvarez, 2022 ), the ability of regional health authorities to deal with the pandemic ( Gutiérrez et al, 2021 ), potential differences in cultural traits ( Chen et al, 2021 ), air pollution ( Carteni et al, 2020 ), or the sociodemographic composition of the population ( Glaeser et al, 2020 ), all which have been shown to affect infection rates. There seems to be a negative association between the two, implying that provinces with greater normalized inflows have fewer normalized cases, ceteris paribus .…”

“…They find that the lockdown was effective at flattening the curve. More recently, Gutiérrez et al (2021) evaluate the regional inequalities in cases and deaths across Spanish regions. They show that part of the heterogeneity in the disease incidence across territories is due to differences in mobility flows.…”