气候变化领域集成服务门户(CCPortal): Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions

CCPortal

DOI	10.1038/s41467-021-26742-6
	Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions
	Vahedi B.; Karimzadeh M.; Zoraghein H.
发表日期	2021
ISSN	2041-1723
卷号	12 期号:1
英文摘要	Measurements of human interaction through proxies such as social connectedness or movement patterns have proved useful for predictive modeling of COVID-19, which is a challenging task, especially at high spatial resolutions. In this study, we develop a Spatiotemporal autoregressive model to predict county-level new cases of COVID-19 in the coterminous US using spatiotemporal lags of infection rates, human interactions, human mobility, and socioeconomic composition of counties as predictive features. We capture human interactions through 1) Facebook- and 2) cell phone-derived measures of connectivity and human mobility, and use them in two separate models for predicting county-level new cases of COVID-19. We evaluate the model on 14 forecast dates between 2020/10/25 and 2021/01/24 over one- to four-week prediction horizons. Comparing our predictions with a Baseline model developed by the COVID-19 Forecast Hub indicates an average 6.46% improvement in prediction Mean Absolute Errors (MAE) over the two-week prediction horizon up to 20.22% improvement in the four-week prediction horizon, pointing to the strong predictive power of our model in the longer prediction horizons. © 2021, The Author(s).
语种	英语
scopus关键词	cell; cell component; COVID-19; prediction; vector autoregression; cell phone use; epidemiology; forecasting; genetics; human; isolation and purification; machine learning; population dynamics; spatiotemporal analysis; statistical model; virology; Cell Phone Use; COVID-19; Forecasting; Humans; Machine Learning; Models, Statistical; Population Dynamics; SARS-CoV-2; Spatio-Temporal Analysis
来源期刊	Nature Communications
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/251312
作者单位	Department of Geography, University of Colorado Boulder, Boulder, United States; Social and Behavioral Science Research, Population Council, New York, United States
推荐引用方式 GB/T 7714	Vahedi B.,Karimzadeh M.,Zoraghein H.. Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions[J],2021,12(1).
APA	Vahedi B.,Karimzadeh M.,&Zoraghein H..(2021).Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions.Nature Communications,12(1).
MLA	Vahedi B.,et al."Spatiotemporal prediction of COVID-19 cases using inter- and intra-county proxies of human interactions".Nature Communications 12.1(2021).