Optimization strategies of human mobility during the COVID-19 pandemic: A review

Soumyajyoti Biswas; Amit Kr Mandal; Soumyajyoti Biswas; Amit Kr Mandal

doi:10.3934/mbe.2021395

Mathematical Biosciences and Engineering

2021, Volume 18, Issue 6: 7965-7978. doi: 10.3934/mbe.2021395

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Optimization strategies of human mobility during the COVID-19 pandemic: A review

Soumyajyoti Biswas ^{1
,
,},
Amit Kr Mandal ²

1.
Department of Physics, SRM University, AP-Amaravati 522502, Andhra Pradesh, India
2.
Department of Computer Science and Engineering, SRM University-AP, Andhra Pradesh 522502, India

Academic Editor: Giuseppe Toscani

Received: 31 May 2021 Accepted: 30 August 2021 Published: 13 September 2021

The impact of the ongoing COVID-19 pandemic is being felt in all spheres of our lives – cutting across the boundaries of nation, wealth, religions or race. From the time of the first detection of infection among the public, the virus spread though almost all the countries in the world in a short period of time. With humans as the carrier of the virus, the spreading process necessarily depends on the their mobility after being infected. Not only in the primary spreading process, but also in the subsequent spreading of the mutant variants, human mobility plays a central role in the dynamics. Therefore, on one hand travel restrictions of varying degree were imposed and are still being imposed, by various countries both nationally and internationally. On the other hand, these restrictions have severe fall outs in businesses and livelihood in general. Therefore, it is an optimization process, exercised on a global scale, with multiple changing variables. Here we review the techniques and their effects on optimization or proposed optimizations of human mobility in different scales, carried out by data driven, machine learning and model approaches.
- epidemic model,
- movement optimization,
- machine learning,
- SIR model
Citation: Soumyajyoti Biswas, Amit Kr Mandal. Optimization strategies of human mobility during the COVID-19 pandemic: A review[J]. Mathematical Biosciences and Engineering, 2021, 18(6): 7965-7978. doi: 10.3934/mbe.2021395

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Abstract

The impact of the ongoing COVID-19 pandemic is being felt in all spheres of our lives – cutting across the boundaries of nation, wealth, religions or race. From the time of the first detection of infection among the public, the virus spread though almost all the countries in the world in a short period of time. With humans as the carrier of the virus, the spreading process necessarily depends on the their mobility after being infected. Not only in the primary spreading process, but also in the subsequent spreading of the mutant variants, human mobility plays a central role in the dynamics. Therefore, on one hand travel restrictions of varying degree were imposed and are still being imposed, by various countries both nationally and internationally. On the other hand, these restrictions have severe fall outs in businesses and livelihood in general. Therefore, it is an optimization process, exercised on a global scale, with multiple changing variables. Here we review the techniques and their effects on optimization or proposed optimizations of human mobility in different scales, carried out by data driven, machine learning and model approaches.

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