Socioeconomic Conditioning of the Development of the COVID-19 Pandemic and Its Global Spatial Differentiation

Abstract

The COVID pandemic very quickly became the world’s most serious social and economic problem. This paper’s focus is on the spatial aspect of its spread, with the aims being to point to spatial conditioning underpinning development of the pandemic, and to identify and assess possible socio-economic features exerting an impact on that. Particular attention has been paid to the percentage of positive tests for the presence of the coronavirus, as well as mortality due to the disease it causes. The statistics used relate to 102 countries, with the research for each extending from the time first cases of COVID-19 were reported through to 18 November 2020. The focus of investigation has been the stochastic co-occurrence of both a morbidity index and a mortality index, with intentionally selected socio-economic variables. Results have then been summarized through the classification of countries in relation to the two indices. Highest values relate to Latin America. A significant co-occurrence of morbidity and mortality with GDP per capita has been identified, as values for the indices are found to be lower in wealthier countries. The basic conclusion is that the dependency of the pandemic on environmental and socio-economic conditioning became more complex and ambiguous, while also being displaced gradually as concrete political decisions came to be taken.

What have we learned about socioeconomic inequalities in the spread of COVID-19? A systematic review

“…While about one half of the studies point towards the positive link ( Gonzalez-Val & Sanz-Gracia, 2021 ; Kianfar, Mesgari, Mollalo, & Kaveh, 2022 ; Li, et al, 2021 ), the other half of them had shown no association ( Kumru, Yiğit, & Hayran, 2021 ; Teh, et al, 2021 ). Only a handful of studies have examined the role of measures of income level ( Leung, Sharma, Adithipyangkul, & Hosie, 2020 ; Li, et al, 2021 ), amount of education ( Li, et al, 2021 ; Bański, Mazur, & Kamińska, 2021 ), unemployment ( Jain & Singh, 2020 ) or household size ( El Mouhayyar, Jaber, Bergmann, Tighiouart, & Jaber, 2021 ) on infection rate. Perhaps this is because of two reasons.…”

Peruvian children toothbrushing during the COVID-19 pandemic

“…In addition, Peru became the country with the highest COVID-19 case fatality rate in the world, despite the efforts made by the government, evidencing the collapse of its health system. 14 – 16 From all the above, it can be understood that the residents of Peru had to survive a complex and challenging context, which not only put their lives and those of their families at risk, but also compromised the economic stability of their homes; therefore, the performance of practices that did not need to be addressed urgently, such as dental brushing for children, was delayed.…”

Sustainability of the agri-food supply chain amidst the pandemic: Diversification, local input production, and consumer behavior

“…This finding suggests that major spatial aspects underpin differentiated impacts of the pandemic. Besides geography influencing the spread and magnitude of the effect of coronavirus, Bański et al (2021) posit that socioeconomic conditioning determines the severity of impacts of the pandemic. Furthermore, as earlier stated by Snow et al (2021) , a high level of ingenuity among local communities precipitated the resilience of New Zealand and the Australian agriculture sector to coronavirus disruptions.…”