Evidence map›Paper›PMID 41013465›Full record

ArticleInternational journal of health geographics2025

Analyzing the stability of gun violence patterns during the COVID-19 pandemic in Syracuse, New York.

Peng Gao, Sarah E Van Horne, David A Larsen, Robert A Rubinstein, Sandra D Lane

Abstract read
In one paragraph

Article in International journal of health geographics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Peng GaoDepartment of Geography and the Environment, Syracuse University, Syracuse, NY, 13244, USA. pegao@syr.edu.
Sarah E Van HorneSchool of Architecture, Syracuse University, Syracuse, NY, 13244, USA.
David A LarsenDepartment of Public Health, Syracuse University, Syracuse, NY, 13244, USA.
Robert A RubinsteinDepartment of Anthropology, Syracuse University, Syracuse, NY, 13244, USA.
Sandra D LaneDepartment of Public Health, Syracuse University, Syracuse, NY, 13244, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gun violence is a leading cause of death in the United States. Understanding the geospatial patterns of gun violence and how the COVID-19 pandemic may have affected them is essential for developing evidence-based prevention strategies. This study investigates whether COVID-19 altered the geospatial patterns of gun violence in Syracuse, New York. To assess spatial and temporal trends, we analyzed the annual total gunshots (ATG) from 2009-2023 aggregated in census block groups and applied geospatial techniques including mean center, standard distance, Moran's I, and Getis-Ord Gi*. The ATG number was higher before the pandemic than during the pandemic, something not observed in other studies. Its geographic centers before and during the pandemic clustered within or near one census block and the associated standard distance remained similar between the two periods. Both global patterns and local clusters of ATG in the two periods not only showed similar patterns and consistent local hotspots located in similar areas, but also logarithmically related to the ATG number with statistical significance, suggesting that gun violence rates intensified within established areas rather than spreading citywide and demonstrated a similar distance-decay effect in both periods. This effect suggests that the incidence of gunshots diminished with increasing distance from the core concentrated zone, challenging assumptions of spatial spillover or contagion models in crime studies. These findings suggest that entrenched structural conditions, such as neighborhood-level socioeconomic disparities, are the primary drivers of gun violence patterns, rather than temporary pandemic-related policies. Methodologically, the study highlights the importance of long-term, meso-scale geospatial analyses to uncover persistent violence dynamics and guide preventive interventions. We argue that future violence prevention strategies should focus on enduring geospatial patterns of gun violence and their underlying structural determinants, rather than reacting solely to short-term fluctuations in incident frequency.

Indexed as

COVID-19FirearmsGun ViolenceHumansNew YorkPandemicsAnd COVID-19 pandemicGeospatial analysisGun violenceHot spotsSpatial clustering

Identifiers

PMID41013465
PMCPMC12465400

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.