A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate

doi:10.1016/j.ecolmodel.2020.109187

	A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate
	Coro, Gianpaolo
	2020-09
发表期刊	ECOLOGICAL MODELLING
ISSN	0304-3800
EISSN	1872-7026
摘要	COVID-19 pandemic is a global threat to human health and economy that requires urgent prevention and monitoring strategies. Several models are under study to control the disease spread and infection rate and to detect possible factors that might favour them, with a focus on understanding the correlation between the disease and specific geophysical parameters. However, the pandemic does not present evident environmental hindrances in the infected countries. Nevertheless, a lower rate of infections has been observed in some countries, which might be related to particular population and climatic conditions. In this paper, infection rate of COVID-19 is modelled globally at a 0.5 degrees resolution, using a Maximum Entropy-based Ecological Niche Model that identifies geographical areas potentially subject to a high infection rate. The model identifies locations that could favour infection rate due to their particular geophysical (surface air temperature, precipitation, and elevation) and human-related characteristics (CO2 and population density). It was trained by facilitating data from Italian provinces that have reported a high infection rate and subsequently tested using datasets from World countries' reports. Based on this model, a risk index was calculated to identify the potential World countries and regions that have a high risk of disease increment. The distribution outputs foresee a high infection rate in many locations where real-world disease outbreaks have occurred, e.g. the Hubei province in China, and reports a high risk of disease increment in most World countries which have reported significant outbreaks (e.g. Western U.S.A.). Overall, the results suggest that a complex combination of the selected parameters might be of integral importance to understand the propagation of COVID-19 among human populations, particularly in Europe. The model and the data were distributed through Open-science Web services to maximise opportunities for re-usability regarding new data and new diseases, and also to enhance the transparency of the approach and results.
关键词	Ecological niche modelling Coronavirus SARS-CoV-2 COVID-19 Maximum entropy
DOI	10.1016/j.ecolmodel.2020.109187
WOS关键词	SHORT-TERM ; VIRUS ; TEMPERATURE ; CULICIDAE ; INVASION ; WEB
WOS研究方向	Environmental Sciences & Ecology
WOS类目	Ecology
出版者	ELSEVIER
引用统计
文献类型	期刊论文
专题	新冠肺炎循证社会科学证据集成
作者单位	CNR
推荐引用方式 GB/T 7714	Coro, Gianpaolo. A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate[J]. ECOLOGICAL MODELLING,2020.
APA	Coro, Gianpaolo.(2020).A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate.ECOLOGICAL MODELLING.
MLA	Coro, Gianpaolo."A global-scale ecological niche model to predict SARS-CoV-2 coronavirus infection rate".ECOLOGICAL MODELLING (2020).