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J Theor Biol. 2019 Jun 7;470:20-29. doi: 10.1016/j.jtbi.2019.03.004. Epub 2019 Mar 6.

Increased infection severity in downstream cities in infectious disease transmission and tourists surveillance analysis.

Author information

1
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China. Electronic address: zhangnan@hku.hk.
2
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
3
Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong, China. Electronic address: liyg@hku.hk.

Abstract

Infectious disease severely threatens human life. Human mobility and travel patterns influence the spread of infection between cities and countries. We find that the infection severity in downstream cities during outbreaks is related to transmission rate, recovery rate, travel rate, travel duration and the average number of person-to-person contacts per day. The peak value of the infected population in downstream cities is slightly higher than that in source cities. However, as the number of cities increases, the severity increase percentage during outbreaks between end and source cities is constant. The surveillance of important nodes connecting cities, such as airports and train stations, can help delay the occurrence time of infection outbreaks. The city-entry surveillance of hub cities is not only useful to these cities, but also to cities that are strongly connected (i.e., have a high travel rate) to them. The city-exit surveillance of hub cities contributes to other downstream cities, but only slightly to itself. Surveillance conducted in hub cities is highly efficient in controlling infection transmission. Only strengthening the individual immunity of frequent travellers is not efficient for infection control. However, reducing the number of person-to-person contacts per day effectively limits the spread of infection.

KEYWORDS:

City; Human mobility; Infectious disease transmission; SIR model; Severity increase percentage; Travel pattern

PMID:
30851275
DOI:
10.1016/j.jtbi.2019.03.004

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