Characterizing pandemic-related publications: a retrospective study using spatial citation network analysis

Abstract The COVID-19 pandemic sparked a surge in research across disciplines, offering vital knowledge for addressing the crisis and earning widespread citations. Yet, the spatiotemporal patterns within these citation networks are underexplored. This study uses network analysis to examine pandemic-related publications from 2019 to 2023, building two citation networks: one from internal citations among 7,641 papers and another including their 217,453 external references. The analytical findings reveal a not widespread impact in the citation of pandemic-related publications, suggesting that a small number of studies gained the most of research focus from subsequent studies. Thematically, research shifted from immediate responses (e.g., "lockdown") to broader impacts (e.g., "mental health"), signaling a focus on long-term resilience. Spatially, citations cluster in regions like the eastern U.S., Europe, and East Asia, while areas like Africa and Inner Asia show limited integration, highlighting geographic disparities and imbalanced networks. This analysis sheds light on interdisciplinary and regional collaboration in pandemic research and emphasizes the need for equitable global participation in knowledge networks. These insights offer practical implications for enhancing research dissemination in future health crises.

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Publication Details

Journal
Computational Urban Science
Published
2025-05-08
DOI
https://doi.org/10.1007/s43762-025-00184-y
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
0.00
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article

Characterizing pandemic-related publications: a retrospective study using spatial citation network analysis

Zhiyang Xiao, Xintao Liu, Liyuan Fan, Zidong Yu
Computational Urban Science
Data-Driven Disease Surveillance
article

Characterizing pandemic-related publications: a retrospective study using spatial citation network analysis

Zhiyang Xiao, Xintao Liu, Liyuan Fan, Zidong Yu
article en

Abstract

Abstract The COVID-19 pandemic sparked a surge in research across disciplines, offering vital knowledge for addressing the crisis and earning widespread citations. Yet, the spatiotemporal patterns within these citation networks are underexplored. This study uses network analysis to examine pandemic-related publications from 2019 to 2023, building two citation networks: one from internal citations among 7,641 papers and another including their 217,453 external references. The analytical findings reveal a not widespread impact in the citation of pandemic-related publications, suggesting that a small number of studies gained the most of research focus from subsequent studies. Thematically, research shifted from immediate responses (e.g., "lockdown") to broader impacts (e.g., "mental health"), signaling a focus on long-term resilience. Spatially, citations cluster in regions like the eastern U.S., Europe, and East Asia, while areas like Africa and Inner Asia show limited integration, highlighting geographic disparities and imbalanced networks. This analysis sheds light on interdisciplinary and regional collaboration in pandemic research and emphasizes the need for equitable global participation in knowledge networks. These insights offer practical implications for enhancing research dissemination in future health crises.

Computational Urban ScienceVol. 5(1)
Hong Kong Polytechnic University (HK)
Openalex Percentile: Top 86%
Data-Driven Disease Surveillance
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Characterizing pandemic-related publications: a retrospective study using spatial citation network analysis — Zhiyang Xiao, Xintao Liu, et al. · Computational Urban Science (2025) | TGRS Research Map | TGRS