Author: Mihir Mehta; Juxihong Julaiti; Paul Griffin; Soundar Kumara
Title: Early Stage Prediction of US County Vulnerability to the COVID-19 Pandemic Document date: 2020_4_11
ID: 901ghexi_15
Snippet: Previous studies have shown angiotensin-converting enzyme 2 (ACE2) facilitates the infection of COVID-19 [35] [36] [37] , and that patients with diabetes, hypertension and cardiovascular diseases have an increased expression of ACE2. 35 County population factors such as density, age, and sex have a significant impact on the spread of an epidemic. 38 Cancer and chronic respiratory diseases have also been shown to increase mortality risk for COVID-.....
Document: Previous studies have shown angiotensin-converting enzyme 2 (ACE2) facilitates the infection of COVID-19 [35] [36] [37] , and that patients with diabetes, hypertension and cardiovascular diseases have an increased expression of ACE2. 35 County population factors such as density, age, and sex have a significant impact on the spread of an epidemic. 38 Cancer and chronic respiratory diseases have also been shown to increase mortality risk for COVID-19. 39 The dataset used for our three-stage model contains correlated variables. For example, diabetes and hypertension prevalence, cancer crude rate and old population. Additionally, the underlying relationship between variables was assumed to be non-linear. For such cases the literature supports 40-47 using gradient tree boosting and deep learning methods for better prediction results.
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