Variant patterns and influence of inter-regional travel during the SARS-CoV-2 expansion in South Africa

We evaluated the dynamic impacts of three types of human mobilities-provincial inflows, cross-district flows, and within-district flows-on daily reported COVID-19 cases for 2020. Using a structural equation modeling approach, we conducted regressions on dynamic panel datasets. Our findings indicate that these three types of mobility influenced daily new COVID-19 case numbers in distinct and sometimes overlapping ways during the early stages of the epidemic. Within-district flows played a particularly significant role in increasing cases during the spreading stage. During the epidemic stage, we observed a sustained but gradually declining impact of within-district mobility on daily new cases, potentially highlighting the effectiveness of non-pharmaceutical interventions (NPIs). In addition, signs of social distancing fatigue were evident. Our model further shows that the first and most stringent lockdown policy significantly curtailed human mobility, whereas the second, less restrictive lockdown had negligible impact on human mobility.

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Publication Details

Journal
PLoS ONE
Published
2025-11-06
DOI
https://doi.org/10.1371/journal.pone.0329621
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

Variant patterns and influence of inter-regional travel during the SARS-CoV-2 expansion in South Africa

Anna Winters, Natalia Blanco, Alash’le Abimiku, Chenfeng Xiong et al.
PLoS ONE
COVID-19 epidemiological studies
article

Variant patterns and influence of inter-regional travel during the SARS-CoV-2 expansion in South Africa

Anna Winters, Natalia Blanco, Alash’le Abimiku, Chenfeng Xiong, Kristen A. Stafford, Weiyu Luo, Meagan C. Fitzpatrick, Vivek Naranbhai, Manhattan Charurat, Ruohan Li, Xin Wu
article en

Abstract

We evaluated the dynamic impacts of three types of human mobilities-provincial inflows, cross-district flows, and within-district flows-on daily reported COVID-19 cases for 2020. Using a structural equation modeling approach, we conducted regressions on dynamic panel datasets. Our findings indicate that these three types of mobility influenced daily new COVID-19 case numbers in distinct and sometimes overlapping ways during the early stages of the epidemic. Within-district flows played a particularly significant role in increasing cases during the spreading stage. During the epidemic stage, we observed a sustained but gradually declining impact of within-district mobility on daily new cases, potentially highlighting the effectiveness of non-pharmaceutical interventions (NPIs). In addition, signs of social distancing fatigue were evident. Our model further shows that the first and most stringent lockdown policy significantly curtailed human mobility, whereas the second, less restrictive lockdown had negligible impact on human mobility.

PLoS ONEVol. 20(11)
University of Maryland, Baltimore (US), Centre for the AIDS Programme of Research in South Africa (ZA), Golden Valley Agricultural Research Trust (ZM), Institute of Human Virology (NG), Monash University (AU), Villanova University (US)
Openalex Percentile: Top 63%
COVID-19 epidemiological studies
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