Abstract
BackgroundCOVID-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.ResultsThe 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.ConclusionsModel 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.
Highlights
The Coronavirus disease (COVID-19) has spread more globally and rapidly than previous outbreaks [1], which suggests that rising international connectivity [2, 3] and urbanisation [4, 5] have played a key role in its diffusion between and within territories
Lombardia (Italy) [7, 8], New York [9], Madrid (Spain) [10], and Tehran (Iran) [11] all by far outnumbered cases in other regions within their respective countries in the first few months of 2020. This exploratory study seeks to test the role played by globalisation, settlement and population characteristics to explain the spatial diffusion of reported COVID-19 cases at a global scale in the early stages of the pandemic
By April 8th 2020 – the final week in this study – there had been 20,277,716 reported cases recorded within the COVID-19 Data Repository by the Center for Systems Science and Engineering at Johns Hopkins University (JHU) [15]
Summary
The Coronavirus disease (COVID-19) has spread more globally and rapidly than previous outbreaks (e.g., the 1918 Spanish Influenza pandemic and the 2003 SARS epidemic) [1], which suggests that rising international connectivity [2, 3] and urbanisation [4, 5] have played a key role in its diffusion between and within territories. Lombardia (Italy) [7, 8], New York (the United States) [9], Madrid (Spain) [10], and Tehran (Iran) [11] all by far outnumbered cases in other regions within their respective countries in the first few months of 2020 This exploratory study seeks to test the role played by globalisation, settlement and population characteristics to explain the spatial diffusion of reported COVID-19 cases at a global scale in the early stages of the pandemic. Understood to have diffused geographically from a single point of origin in China in late December 2019 [12, 13], spatial diffusion across country borders was at first relatively slow It took 45 days for the virus to spread to 30 countries, areas or territories [14]. Expansion diffusion identifies the general tendency for phenomena to spread ‘outward’, and infectious diseases are most associated with contagious (expansion) diffusion, indicating direct transmission between neighbours due to their physical proximity
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