Integrating County-Level Socioeconomic Data for COVID-19 Forecasting in the United States

被引:7
|
作者
Lucic, Michael C. [1 ]
Ghazzai, Hakim [1 ]
Lipizzi, Carlo [1 ]
Massoud, Yehia [2 ]
机构
[1] Stevens Inst Technol, Hoboken, NJ 07030 USA
[2] King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Thuwal 239556900, Saudi Arabia
来源
IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY | 2021年 / 2卷
关键词
ARIMA; COVID-19; data analytics; k-means clustering; time series analysis; INFECTIOUS-DISEASE; MODEL; TRANSMISSION; SPREAD; PHASE;
D O I
10.1109/OJEMB.2021.3096135
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Goal: The United States (US) is currently one of the countries hardest-hit by the novel SARS-CoV-19 virus. One key difficulty in managing the outbreak at the national level is that due to the US' diversity, geographic spread, and economic inequality, the COVID-19 pandemic in the US acts more as a series of diverse regional outbreaks rather than a synchronized homogeneous one. Method: In order to determine how to assess regional risk related to COVID-19, a two-phase modeling approach is developed while considering demographic and economic criteria. First, an unsupervised clustering technique, specifically k-means, is employed to group US counties based on demographic and economic similarities. Then, time series forecasting of each cluster of counties is developed to assess the short-run viral transmissibility risk. Results: To this end, we test ARIMA and Seasonal Trend Random Walk forecasts to determine which is more appropriate for modeling the spread and lethality of COVID-19. From our analysis, we then utilize the superior ARIMA models to forecast future COVID-19 trends in the clusters, and present the areas in the US which have the highest COVID-19 related risk heading into the winter of 2020. Conclusion: Including sub-national socioeconomic characteristics to data-driven COVID-19 infection and fatality forecasts may play a key role in assessing the risk associated with changes in infection patterns at the national level.
引用
收藏
页码:235 / 248
页数:14
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