What is it about?

This study investigates the impact of individual human mobility on the spread of infectious disease infections and how this impact can be incorporated into epidemic models. The authors integrate a classical SEIR individual-based model with a model of individual human mobility to understand how human mobility affects the spread of epidemics, using the relative attractiveness to characterize the landscape of human mobility and the time of the first arrival of infection to provide a geo-temporal spreading pattern of epidemics. The study explores intervention strategies at the individual level, such as travel restrictions of symptomatic infectious individuals.

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Why is it important?

This study highlights the crucial role of human mobility in the spread of infectious diseases and emphasizes the need to incorporate this factor into epidemic models to obtain more accurate predictions of disease spread. By integrating an individual human mobility model with an epidemic model, the study provides a more realistic representation of disease transmission dynamics, which can be useful for designing effective disease control strategies such as vaccination or travel restriction. The study also explores the impact of individual waiting time and intervention strategies at the individual level, providing insights into how these factors can affect epidemic dynamics. The findings of this study could be helpful in the preparedness plans for future epidemics and could have practical applications in public health decision-making.


This study highlights the importance of incorporating individual human mobility into epidemic models for more accurate predictions of disease spread. By exploring the impact of human mobility and intervention strategies at the individual level, this study provides valuable insights that could inform public health decision-making and preparedness plans for future epidemics.

Charin Modchang
Mahidol University

Read the Original

This page is a summary of: How the individual human mobility spatio-temporally shapes the disease transmission dynamics, Scientific Reports, July 2020, Springer Science + Business Media, DOI: 10.1038/s41598-020-68230-9.
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