The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population

Abstract

Background COVID-19 is an emergent infectious disease that has spread geographically to become a global pandemic. While much research focuses on the epidemiological and virological aspects of COVID-19 transmission, there remains an important gap in knowledge regarding the drivers of geographical diffusion between places, in particular at the global scale. Here, we use quantile regression to model the roles of globalisation, human settlement and population characteristics as socio-spatial determinants of reported COVID-19 diffusion over a six-week period in March and April 2020. Our exploratory analysis is based on reported COVID-19 data published by Johns Hopkins University which, despite its limitations, serves as the best repository of reported COVID-19 cases across nations. Results The quantile regression model suggests that globalisation, settlement, and population characteristics related to high human mobility and interaction predict reported disease diffusion. Human development level (HDI) and total population predict COVID-19 diffusion in countries with a high number of total reported cases (per million) whereas larger household size, older populations, and globalisation tied to human interaction predict COVID-19 diffusion in countries with a low number of total reported cases (per million). Population density, and population characteristics such as total population, older populations, and household size are strong predictors in early weeks but have a muted impact over time on reported COVID-19 diffusion. In contrast, the impacts of interpersonal and trade globalisation are enhanced over time, indicating that human mobility may best explain sustained disease diffusion. Conclusions Model results confirm that globalisation, settlement and population characteristics, and variables tied to high human mobility lead to greater reported disease diffusion. These outcomes serve to inform suppression strategies, particularly as they are related to anticipated relocation diffusion from more- to less-developed countries and regions, and hierarchical diffusion from countries with higher population and density. It is likely that many of these processes are replicated at smaller geographical scales both within countries and within regions. Epidemiological strategies must therefore be tailored according to human mobility patterns, as well as countries’ settlement and population characteristics. We suggest that limiting human mobility to the greatest extent practical will best restrain COVID-19 diffusion, which in the absence of widespread vaccination may be one of the best lines of epidemiological defense.

A Spatial Analysis of COVID-19 in African Countries: Evaluating the Effects of Socio-Economic Vulnerabilities and Neighbouring

“…With the continent's large populations living in high levels of poverty and crowded informal urban settings, coupled with its fragile health systems, there were global fears that the continent would be particularly devasted by the COVID-19 pandemic [10][11][12][13]. However, the COVID-19 pandemic is affecting the African countries differently due to varied economic wealth, health care systems, and governance, which are conditions identified in prior studies to be significant in explaining COVID-19 is spread [14][15][16].…”

Seroprevalence, prevalence, and genomic surveillance: monitoring the initial phases of the SARS-CoV-2 pandemic in Betim, Brazil

“…Covid-19 diffusion presents strong socio-spatial determinants. Relocation diffusion from more- to less-developed regions and hierarchical diffusion from countries with higher population and density were relevant since early 2020 [41]. Data indicated a similar pattern in the São Paulo State with contiguous diffusion from the capital metropolitan area and hierarchical with long-distance spread through major highways that connects São Paulo city with cities of regional relevance [42].…”

An in-depth statistical analysis of the COVID-19 pandemic’s initial spread in the WHO African region

“…Additionally, we found that the speed at which the first 50 infections happen in a country is positively related to its population density. Urban, dense areas usually produce the prerequisites for crowding, greater number of social interactions and close contact, which increases the risk for the spread of an infectious agent (IZA, 2020; Neiderud et al, 2015;Sigler et al, 2021).…”

“…These precautions could include stricter border control and decreased mobilisation of people, resulting in lower early cases. However, given the geographic complexity of the continent and the knowledge gap on the drivers of geographical diffusion between areas, further research is needed to examine this hypothesis in detail (Sigler et al, 2021).…”