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The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population
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 di...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8135172/ https://www.ncbi.nlm.nih.gov/pubmed/34016145 http://dx.doi.org/10.1186/s12992-021-00707-2 |
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author | Sigler, Thomas Mahmuda, Sirat Kimpton, Anthony Loginova, Julia Wohland, Pia Charles-Edwards, Elin Corcoran, Jonathan |
author_facet | Sigler, Thomas Mahmuda, Sirat Kimpton, Anthony Loginova, Julia Wohland, Pia Charles-Edwards, Elin Corcoran, Jonathan |
author_sort | Sigler, Thomas |
collection | PubMed |
description | 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12992-021-00707-2. |
format | Online Article Text |
id | pubmed-8135172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-81351722021-05-20 The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population Sigler, Thomas Mahmuda, Sirat Kimpton, Anthony Loginova, Julia Wohland, Pia Charles-Edwards, Elin Corcoran, Jonathan Global Health Research 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12992-021-00707-2. BioMed Central 2021-05-20 /pmc/articles/PMC8135172/ /pubmed/34016145 http://dx.doi.org/10.1186/s12992-021-00707-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Sigler, Thomas Mahmuda, Sirat Kimpton, Anthony Loginova, Julia Wohland, Pia Charles-Edwards, Elin Corcoran, Jonathan The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population |
title | The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population |
title_full | The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population |
title_fullStr | The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population |
title_full_unstemmed | The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population |
title_short | The socio-spatial determinants of COVID-19 diffusion: the impact of globalisation, settlement characteristics and population |
title_sort | socio-spatial determinants of covid-19 diffusion: the impact of globalisation, settlement characteristics and population |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8135172/ https://www.ncbi.nlm.nih.gov/pubmed/34016145 http://dx.doi.org/10.1186/s12992-021-00707-2 |
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