Revealing human mobility trends during the SARS-CoV-2 pandemic in Nigeria via a data-driven approach

Authors

  • Weiyu Luo Department of Civil and Environmental Engineering, College of Engineering, Villanova University, Philadelphia, Pennsylvania, USA https://orcid.org/0000-0002-7987-2199
  • Chenfeng Xiong Department of Civil and Environmental Engineering, College of Engineering, Villanova University, Philadelphia, Pennsylvania, USA https://orcid.org/0000-0003-4237-1750
  • Jiajun Wan Carnegie Mellon University, Pittsburgh, Pennsylvania, USA https://orcid.org/0000-0003-3018-7999
  • Ziteng Feng Department of Civil and Environmental Engineering, College of Engineering, Villanova University, Philadelphia, Pennsylvania, USA
  • Olawole Ayorinde Institute of Human Virology Nigeria (IHVN), Abuja, Nigeria
  • Natalia Blanco 1.University of Maryland School of Medicine Institute of Human Virology, Baltimore, Maryland, USA; 2.Center for International Health Education and Biosecurity, University of Maryland School of Medicine, Baltimore, Maryland, USA https://orcid.org/0000-0002-3157-1119
  • Man Charurat 1.University of Maryland School of Medicine Institute of Human Virology, Baltimore, Maryland, USA; 2.Center for International Health Education and Biosecurity, University of Maryland School of Medicine, Baltimore, Maryland, USA; 3.Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA https://orcid.org/0000-0002-1719-2796
  • Vivek Naranbhai 1.Centre for the AIDS Programme of Research in South Africa (CAPRISA), Nelson R. Mandela School of Medicine, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa; 2.HIV Pathogenesis Programme, Nelson R. Mandela School of Medicine, Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa https://orcid.org/0000-0003-4281-8882
  • Christina Riley Akros, Lusaka, Zambia
  • Anna Winters Akros, Lusaka, Zambia
  • Fati Murtala-Ibrahim Institute of Human Virology Nigeria (IHVN), Abuja, Nigeria https://orcid.org/0000-0001-9943-8958
  • Alash’le Abimiku 1.Institute of Human Virology Nigeria (IHVN), Abuja, Nigeria; 2.University of Maryland School of Medicine Institute of Human Virology, Baltimore, Maryland, USA; 3.Center for International Health Education and Biosecurity, University of Maryland School of Medicine, Baltimore, Maryland, USA https://orcid.org/0000-0003-2213-0204

DOI:

https://doi.org/10.17159/sajs.2023/14727

Keywords:

SARS-CoV-2, human mobility, trips, policy, Nigeria

Abstract

We employed emerging smartphone-based location data and produced daily human mobility measurements using Nigeria as an application site. A data-driven analytical framework was developed for rigorously producing such measures using proven location intelligence and data-mining algorithms. Our study demonstrates the framework at the beginning of the SARS-CoV-2 pandemic and successfully quantifies human mobility patterns and trends in response to the unprecedented public health event. Another highlight of the paper is the assessment of the effectiveness of mobility-restricting policies as key lessons learned from the pandemic. We found that travel bans and federal lockdown policies failed to restrict trip-making behaviour, but had a significant impact on distance travelled. This paper contributes a first attempt to quantify daily human travel behaviour, such as trip-making behaviour and travelling distances, and how mobility-restricting policies took effect in sub-Saharan Africa during the pandemic. This study has the potential to enable a wide spectrum of quantitative studies on human mobility and health in sub-Saharan Africa using well-controlled, publicly available large data sets.

Significance:

  • The mobility measurements in this study are new and have filled a major data gap in understanding the change in travel behaviour during the SARS-CoV-2 pandemic in Nigeria. These measurements are derived from high-quality data samples by state-of-the-art data-driven methodologies and could be further adopted by other quantitative research related to human mobility.
  • Additionally, this study evaluates the impact of mobility-restricting policies and the heterogeneous effects of socio-economic and socio-demographic factors by a time-dependent random effect model on human mobility. The quantitative model provides a decision-making basis for the Nigerian government to provide travel-related guidance and make decisions in future public health events.

Open data set: https://github.com/villanova-transportation/Nigeria-mobility-COVID19-SAJS

Published

2023-05-30

Issue

Section

Research Article

How to Cite

Luo, W., Xiong, C., Wan, J., Feng, Z., Ayorinde, O., Blanco, N., Charurat, M., Naranbhai, V., Riley, C., Winters, A., Murtala-Ibrahim, F., & Abimiku, A. (2023). Revealing human mobility trends during the SARS-CoV-2 pandemic in Nigeria via a data-driven approach. South African Journal of Science, 119(5/6). https://doi.org/10.17159/sajs.2023/14727

Funding data

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