Forecasting High-risk Areas of COVID-19 Infection Through Socioeconomic and Static Spatial Analysis-Reference-Cited by-同舟云学术

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Forecasting High-risk Areas of COVID-19 Infection Through Socioeconomic and Static Spatial Analysis

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE International Conference on Big Data (Big Data)
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Author:

Alhamadani Abdulaziz,Sarkar Shailik,Zhang Lei,Alkulaib Lulwah,Lu Chang-Tien

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9671263/9671273/09671896.pdf?arnumber=9671896

Reference51 articles.

1. Hospitalization and Mortality among Black Patients and White Patients with Covid-19

2. Ethnicity, comorbidity, socioeconomic status, and their associations with covid-19 infection in england: a cohort analysis of uk biobank data;prats-uribe;medRxiv,2020

3. Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile

4. Multiple Ensemble Neural Network Models with Fuzzy Response Aggregation for Predicting COVID-19 Time Series: The Case of Mexico

5. The effect of area deprivation on covid-19 risk in louisiana;madhav;medRxiv,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Explainable Prediction of the Severity of COVID-19 Outbreak for US Counties;2022 IEEE International Conference on Big Data (Big Data);2022-12-17

2. DOD-Explainer: Explainable Drug Overdose Deaths Predictor from Crime and Socioeconomic Data;2022 IEEE International Conference on Big Data (Big Data);2022-12-17

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