Abstract
This paper investigates the influence of extreme weather events on human mobility, and its subsequent impact on the spread of COVID-19, with a focus on the case study of Hurricane Laura, which struck the United States in August 2020. Employing a comprehensive approach, the study integrates data from four key sources: (1) human mobility metrics derived from mobile device locations, (2) track data of Hurricane Laura, (3) daily COVID-19 case numbers, and (4) hurricane evacuation orders issued by public agencies. The aim of this research is to develop a two-stage statistical model that captures the interplay between hurricane, human movement, evacuation orders and the spread of COVID-19, while also considering spatial differences in demographic characteristics within the study area. In the first stage, the study examines the direct impact of Hurricane Laura and its associated evacuation orders on mobility metrics. The second stage further investigates the direct impact of Hurricane Laura and evacuation orders on the spread of COVID-19, but also considers the indirect impact through changes in mobility metrics. In both stages of the analysis, linear mixed-effects models are utilized. The results indicate two key correlations: firstly, a negative correlation between hurricane events and mobility, indicate mobility decreases during such extreme weather events; and secondly, a positive correlation between mobility and the COVID-19 cases, indicates higher mobility is associated with an increase in COVID-19 infections. Additionally, our experimental results reveal that the evacuation orders have a significant direct positive impact on both mobility and COVID-19 cases. Finally, our model reveals that spatial demographic variables are key factors in characterizing the trends of both mobility and COVID-19 cases. © 2025 Elsevier Ltd.
| Original language | English |
|---|---|
| Article number | 104423 |
| Number of pages | 19 |
| Journal | Journal of Transport Geography |
| Volume | 129 |
| Online published | 26 Sept 2025 |
| DOIs | |
| Publication status | Published - Dec 2025 |
Funding
This work was partially funded by a US National Institutes of Health (NIH) award (grant number U54TW012041-02) entitled “Role of Data Streams in Informing Infection Dynamics in Africa – INFORM-Africa”. The views and opinions stated in this paper are those of the authors and do not necessarily reflect the views or positions of the project sponsor.
Research Keywords
- Compound risk
- COVID-19
- Evacuation
- Hurricane
- Linear mixed-effects model
- Mobility
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