Evidence map›Paper›PMID 38603180›Full record

ArticleCriminal justice review2023

COVID-19 and Gun Violence: Keeping Unknown Shocks and Volatility in Perspective.

Dae-Young Kim

Abstract read
In one paragraph

Article in Criminal justice review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Trends and Disparities in Firearm Homicides in the USA, 2018-2024.Journal of general internal medicine · 2026
    Article
  2. Article
  3. Article
  4. Article
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

1 author.

Dae-Young KimState University of New York - Buffalo State.ORCID https://orcid.org/0000-0002-7932-4627

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current study estimates the varying effects of the pandemic on gun violence by social distancing type, fatality, and location. Interrupted time series analyses are used to examine weekly crime data from 2016 to 2020 in New York City. Box-Cox power transformation and GARCH techniques are used to address the problems of non-normality and heteroscedasticity in the models. There were significant increases in fatal and non-fatal shootings during the relaxation of social distancing. The impact of the BLM protests and depolicing is significant for non-fatal shootings. The pandemic led to greater increases in gun violence in The Bronx, Brooklyn, Manhattan, and Queens, as opposed to Staten Island. In addition, there is some evidence of increases in the volatility of gun violence during the pandemic. High volatility implies crime rates are in severe flux, which then leads to greater uncertainty and fear for public safety. This paper surfaces useful information for guiding policy and practice.

Indexed as

ARCH/GARCHCOVID-19gun violenceshootingssocial distancing

Identifiers

PMID38603180
PMCPMC8948002

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.