The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Initial evidence on the relationship between the coronavirus pandemic and crime in the United States
Open accessAbstract
The COVID-19 pandemic led to substantial changes in the daily activities of millions of Americans, with many businesses and schools closed, public events cancelled and states introducing stay-at-home orders. This article used police-recorded open crime data to understand how the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020. Seasonal auto-regressive integrated moving average (SARIMA) models of crime in previous years were used to forecast the expected frequency of crime in 2020 in the absence of the pandemic. The forecasts from these models were then compared to the actual frequency of crime during the early months of the pandemic. There were no significant changes in the frequency of serious assaults in public or (contrary to the concerns of policy makers) any change to the frequency of serious assaults in residences. In some cities, there were reductions in residential burglary but little change in non-residential burglary. Thefts of motor vehicles decreased in some cities while there were diverging patterns of thefts from motor vehicles. These results are used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
An interactive web-based dashboard to track COVID-19 in real time
Dong, E., Du, H., & Gardner, L. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30120-1 · Cited by 10,048
Social Change and Crime Rate Trends: A Routine Activity Approach
Cohen, L. E., & Felson, M. (1979) · American Sociological Review · doi:10.2307/2094589 · Cited by 8,856
First case of 2019 novel coronavirus in the United States
Holshue, M. L., DeBolt, C., Lindquist, S., Lofy, K. H., Wiesman, J., Bruce, H., Spitters, C., Ericson, K., Wilkerson, S., Tural, A., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001191 · Cited by 6,030
Social Change and Crime Rate Trends: A Routine Activity Approach (1979)
(2010) · Classics in Environmental Criminology · doi:10.4324/9781439817803-12 · Cited by 5,951
Another look at measures of forecast accuracy
Hyndman, R. J., & Koehler, A. B. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.03.001 · Cited by 5,757
Automatic Time Series Forecasting: The forecast Package for R
Hyndman, R. J., & Khandakar, Y. (2008) · Journal of Statistical Software · doi:10.18637/jss.v027.i03 · Cited by 3,511
Kontopantelis, E., Doran, T., Springate, D. A., Buchan, I., & Reeves, D. (2015) · BMJ · doi:10.1136/bmj.h2750 · Cited by 1,001
On the overlap between victimization and offending: A review of the literature
Jennings, W. G., Piquero, A. R., & Reingle, J. M. (2012) · Aggression and Violent Behavior · doi:10.1016/j.avb.2011.09.003 · Cited by 708
Community Mitigation Guidelines to Prevent Pandemic Influenza — United States, 2017
Qualls, N., Levitt, A., Kanade, N., Wright-Jegede, N., Dopson, S., Biggerstaff, M., Reed, C., Uzicanin, A., CDC Community Mitigation Guidelines Work Group, Levitt, A., et al. (2017) · MMWR. Recommendations and Reports · doi:10.15585/mmwr.rr6601a1 · Cited by 471
Cited by
Domestic violence during the COVID-19 pandemic—evidence from a systematic review and meta-analysis
Piquero, A. R., Jennings, W. G., Jemison, E., Kaukinen, C., & Knaul, F. M. (2021) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2021.101806 · Cited by 759
Staying Home, Staying Safe? A Short-Term Analysis of COVID-19 on Dallas Domestic Violence
Piquero, A. R., Riddell, J. R., Bishopp, S. A., Narvey, C., Reid, J. A., & Piquero, N. L. (2020) · American Journal of Criminal Justice · doi:10.1007/s12103-020-09531-7 · Cited by 357
Has COVID-19 Changed Crime? Crime Rates in the United States during the Pandemic
Boman, J. H., & Gallupe, O. (2020) · American Journal of Criminal Justice · doi:10.1007/s12103-020-09551-3 · Cited by 250
Impact of COVID-19 lockdown policy on homicide, suicide, and motor vehicle deaths in Peru.
Calderon-Anyosa, R. J., & Kaufman, J. S. (2020) · doi:10.1101/2020.07.11.20150193 · Cited by 212
Empty streets, busy internet: a time-series analysis of cybercrime and fraud trends during COVID-19
Kemp, S., Buil-Gil, D., Moneva, A., Miró-Llinares, F., & Díaz-Castaño, N. (2021) · Journal of Contemporary Criminal Justice · doi:10.1177/10439862211027986 · Cited by 125
Metadata
- Authors
- Ashby, M. P. J.
- Venue
- Crime Science
- Published
- 2020-05-18
- Volume
- 9
- Issue
- 1
- Pages
- 6-6
- ISSN
- 2193-7680 (ISSN-L)
- OpenAlex
- W3032520020
- Cited by
- 312
- References
- 21
- FWCI
- 79.98
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Initial evidence on the relationship between the coronavirus pandemic and crime in the United States. https://app.cochat.ai/papers/10.1186/s40163-020-00117-6
- The paper
- Ashby, M. P. J. (2020). Initial evidence on the relationship between the coronavirus pandemic and crime in the United States. Crime Science. https://doi.org/10.1186/s40163-020-00117-6
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
