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_34
Snippet: We developed a three-stage machine learning model using publicly available data to predict the five-day vulnerability of a US county. The model estimates the likelihood and impact that a county with no documented COVID-19 cases will have within a five-day period and using them, vulnerability prediction for a county is made. Using data from March 14 th to Marth 31 st , 2020, the model showed a sensitivity over 71.5% and specificity over 94%. We fo.....
Document: We developed a three-stage machine learning model using publicly available data to predict the five-day vulnerability of a US county. The model estimates the likelihood and impact that a county with no documented COVID-19 cases will have within a five-day period and using them, vulnerability prediction for a county is made. Using data from March 14 th to Marth 31 st , 2020, the model showed a sensitivity over 71.5% and specificity over 94%. We found a positive association between affected counties and urban counties as well as top 10% least vulnerable counties and rural counties. Further, counties with higher population density, a greater percentage of 70 years of above age people, higher diabetes, cardiac illness and respiratory diseases prevalence are more vulnerable to COVID-19 than their counterparts.
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