Prediction of COVID-19 outbreak based on time-lagged relationship between outbound traffic from Wuhan and COVID-19 incidence in China: A time-series analysis (Preprint)

2020 ◽  
Author(s):  
Zaixing Shi ◽  
Ya Fang

BACKGROUND Mass migration during the holiday season may have accelerated the spread of the 2019 coronavirus disease (COVID-19) outbreak across China. But the complex role of migration has not been fully accounted for in most epidemic models of COVID-19. OBJECTIVE To develop a simple and practical prediction model of COVID-19 based on the geo-temporal relationship between daily outbound traffic from Wuhan and the incidence of COVID-19 in 31 Chinese provinces during January-February 2020. METHODS We collected incidence of confirmed COVID-19 cases from National and Provincial Health Committee reports from January 10 to February 29, 2020. Volume of outbound traffic from Wuhan to other provinces was measured by Baidu Migration Index, a widely used metric that tracks migration based on cellphone location. We used cross-correlation function and autoregressive integrated moving average (ARIMA) model to examine time-lagged association between traffic volume and COVID-19 incidence by province. Contributors to the provincial variation in the temporal associations were investigated. Additionally, we estimated the reduction in cumulative incidence of COVID-19 cases following the travel ban for Wuhan. RESULTS Cross-correlation function analyses suggested that the volume of outbound traffic from Wuhan was positively associated with COVID-19 incidence in all provinces, with correlation coefficients between 0.22-0.78 (all P<0.05). Approximately 42% of provinces showed <1 week of lag between traffic volume and COVID-19 incidence, 39% with 1 week, and 19% with 2-3 weeks. Migration had more prolonged impacts in provinces closer to Wuhan and with more passenger influx from Wuhan, but affected economically advantaged provinces to a lesser extent. We further estimated that the travel ban may have prevented approximately 19,768 COVID-19 cases (95% CI: 13,589, 25,946) outside of Wuhan by February 29, 2020. CONCLUSIONS Outflowing migration from Wuhan facilitated the COVID-19 transmission to other parts of China with varying time-lagged effects dependent on provincial characteristics. The travel ban led to a significant reduction in COVID-19 outside of Wuhan.

Author(s):  
Zaixing Shi ◽  
Ya Fang

ABSTRACTBackgroundThe city of Wuhan is the epicenter of the 2019 coronavirus disease (COVID-19) outbreak and a central Chinese hub for transportation and industry. Mass migration prior to the Chinese New Year may have accelerated the spread of COVID-19 across China. This analysis investigated the temporal relationship between daily outbound traffic from Wuhan and the incidence of COVID-19 in 31 Chinese provinces during January-February 2020.MethodsWe collected incidence of confirmed COVID-19 cases from National and Provincial Health Committee reports from January 10 to February 29, 2020. Volume of outbound traffic from Wuhan to other provinces was measured by Baidu Migration Index, a widely used metric that tracks migration based on cellphone location. We used cross-correlation function and autoregressive integrated moving average (ARIMA) model to examine time-lagged association between traffic volume and COVID-19 incidence by province. Contributors to the provincial variation in the temporal associations were investigated. Additionally, we estimated the reduction in cumulative incidence of COVID-19 cases following the travel ban for Wuhan.ResultsCross-correlation function analyses suggested that the volume of outbound traffic from Wuhan was positively associated with COVID-19 incidence in all provinces, with correlation coefficients between 0.22-0.78 (all P<0.05). Approximately 42% of provinces showed <1 week of lag between traffic volume and COVID-19 incidence, 39% with 1 week, and 19% with 2-3 weeks. Migration had more prolonged impacts in provinces closer to Wuhan and with more passenger influx from Wuhan, but affected economically advantaged provinces to a lesser extent. We further estimated that the travel ban may have prevented approximately 19,768 COVID-19 cases (95% CI: 13,589, 25,946) outside of Wuhan by February 29, 2020.ConclusionsOutflowing migration from Wuhan facilitated the COVID-19 transmission to other parts of China with varying time-lagged effects dependent on provincial characteristics. The travel ban led to a significant reduction in COVID-19 outside of Wuhan.


1987 ◽  
Vol 41 (5) ◽  
pp. 869-874 ◽  
Author(s):  
Jung-Pin Yu ◽  
H. Bruce Friedrich

The odd moments of the autocorrelation function are zero, and the moments of the cross-correlation function for an unknown spectrum with a library entry have been used here to select the best fits. The use of the first moment or average wavenumber in six separate spectral ranges requires only 12 values per library entry, and 24 values are required per library entry if twelve separate ranges are used. The odd moment methods were found to yield results for searches with both library and experimental spectra that were comparable to correlation coefficients in selection of the proper chemical class for the unknown spectra and in making of the proper identification.


2005 ◽  
Vol 636 (1) ◽  
pp. L9-L12 ◽  
Author(s):  
Jeff Cooke ◽  
Arthur M. Wolfe ◽  
Eric Gawiser ◽  
Jason X. Prochaska

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