Correlation of subway turnstile entries and COVID-19 incidence and deaths in New York City  

作　　者：Sina Fathi-Kazerooni Roberto Rojas-Cessa Ziqian Dong Vatcharapan Umpaichitra 

机构地区：[1]Department of Electrical and Computer Engineering,Newark College of Engineering,New Jersey Institute of Technology,Newark,NJ,07102,USA [2]Department of Electrical and Computer Engineering,College of Engineering and Computing Sciences,New York Institute of Technology,New York,NY,10023,USA [3]Department of Pediatrics,SUNY Downstate Health Sciences University,Brooklyn,NY,11203,USA

出　　处：《Infectious Disease Modelling》2021年第1期183-194,共12页传染病建模（英文）

摘　　要：In this paper,we show a strong correlation between turnstile entries data of the New York City(NYC)subway provided by NYC Metropolitan Transport Authority and COVID-19 deaths and cases reported by the NYC Department of Health from March to May 2020.This correlation is obtained through linear regression and confirmed by the prediction of the number of deaths by a Long Short-Term Memory neural network.The correlation is more significant after considering incubation and symptomatic phases of this disease as experienced by people who died from it.We extend the analysis to each individual NYC borough.We also estimate the dates when the number of COVID-19 deaths and cases would approach zero by using the Auto-Regressive Integrated Moving Average model on the reported deaths and cases.We also backward forecast the dates when the first cases and deaths might have occurred.

关 键 词：COVID-19 Time-series analysis New York city subway SARS-CoV-2 Long short-term memory ARIMA 

分 类 号：R563.1[医药卫生—呼吸系统] R18[医药卫生—内科学]