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International Conference on Similarity Search and Applications

SISAP 2021: Similarity Search and Applications pp 307–320Cite as

Clustering Adverse Events of COVID-19 Vaccines Across the United States

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 13058))

Abstract

We study the similarity of adverse effects of COVID-19 vaccines across different states in the United States. We use data of 300,000 COVID-19 vaccine adverse event reports obtained from the Vaccine Adverse Event Reporting System (VAERS). We extract latent topics from the reported adverse events using a topic modeling approach based on Latent Dirichlet allocation (LDA). This approach allows us to represent each U.S. state as a low-dimensional distribution over topics. Using Moran’s index of spatial autocorrelation we show that some of the topics of adverse events exhibit significant spatial autocorrelation, indicating that there exist spatial clusters of nearby states that exhibit similar adverse events. Using Anselin’s local indicator of spatial association we discover and report these clusters. Our results show that adverse events of COVID-19 vaccines vary across states which justifies further research to understand the underlying causality to better understand adverse effects and to reduce vaccine hesitancy.

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Acknowledgements

This research was prepared or accomplished by Ahmed Askar in his personal capacity. The opinions expressed in this article are the author’s own and do not reflect the view of the U.S. Food and Drug Administration, the Department of Health and Human Services, or the United States government. This research received no external funding.

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Authors and Affiliations

  1. Department of Geography and Geoinformation Science, George Mason University, 4400 University Drive, MS 6C3, Fairfax, VA, 22030, USA

    Ahmed Askar & Andreas Züfle

  2. Food and Drug Administration, Silver Spring, MD, 20993, USA

    Ahmed Askar

Authors
  1. Ahmed Askar
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  2. Andreas Züfle
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Corresponding author

Correspondence to Ahmed Askar .

Editor information

Editors and Affiliations

  1. National University of San Luis, San Luis, Argentina

    Nora Reyes

  2. University of St Andrews, St Andrews, UK

    Richard Connor

  3. University of Vienna, Vienna, Austria

    Nils Kriege

  4. Kiel University, Kiel, Germany

    Daniyal Kazempour

  5. University of Bologna, Bologna, Italy

    Ilaria Bartolini

  6. TU Dortmund University, Dortmund, Germany

    Erich Schubert

  7. TU Dortmund University, Dortmund, Germany

    Jian-Jia Chen

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Askar, A., Züfle, A. (2021). Clustering Adverse Events of COVID-19 Vaccines Across the United States. In: Reyes, N., et al. Similarity Search and Applications. SISAP 2021. Lecture Notes in Computer Science(), vol 13058. Springer, Cham. https://doi.org/10.1007/978-3-030-89657-7_23

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  • DOI: https://doi.org/10.1007/978-3-030-89657-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89656-0

  • Online ISBN: 978-3-030-89657-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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