tetano
Editor, Senior Moderator
PLoS One
. 2025 Nov 6;20(11):e0329621.
doi: 10.1371/journal.pone.0329621. eCollection 2025. Variant patterns and influence of inter-regional travel during the SARS-CoV-2 expansion in South Africa
Weiyu Luo[SUP] 1 [/SUP], Xin Wu[SUP] 1 [/SUP], Ruohan Li[SUP] 1 [/SUP], Meagan Fitzpatrick[SUP] 2 [/SUP], Man Charurat[SUP] 2 [/SUP], Natalia Blanco[SUP] 2 [/SUP], Kristen A Stafford[SUP] 2 [/SUP], Vivek Naranbhai[SUP] 3 4 [/SUP], Alash'le Abimiku[SUP] 2 5 [/SUP], Anna Winters[SUP] 6 [/SUP]; INFORM Africa Research Study Group for D-SI Africa Consortium; Chenfeng Xiong[SUP] 1 [/SUP]
Affiliations
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.
. 2025 Nov 6;20(11):e0329621.
doi: 10.1371/journal.pone.0329621. eCollection 2025. Variant patterns and influence of inter-regional travel during the SARS-CoV-2 expansion in South Africa
Weiyu Luo[SUP] 1 [/SUP], Xin Wu[SUP] 1 [/SUP], Ruohan Li[SUP] 1 [/SUP], Meagan Fitzpatrick[SUP] 2 [/SUP], Man Charurat[SUP] 2 [/SUP], Natalia Blanco[SUP] 2 [/SUP], Kristen A Stafford[SUP] 2 [/SUP], Vivek Naranbhai[SUP] 3 4 [/SUP], Alash'le Abimiku[SUP] 2 5 [/SUP], Anna Winters[SUP] 6 [/SUP]; INFORM Africa Research Study Group for D-SI Africa Consortium; Chenfeng Xiong[SUP] 1 [/SUP]
Affiliations
- PMID: 41196936
- DOI: 10.1371/journal.pone.0329621
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.