ArticleJournal of behavioral medicine2019
Bolstering gun injury surveillance accuracy using capture-recapture methods.
Article in Journal of behavioral medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- Epidemiology of fatal and nonfatal community firearm violence in New York City, 2019-2023.Injury epidemiology · 2025Article
- Fatal and non-fatal firearm-related injuries in Canada, 2016-2020: a population-based study using three administrative databases.Injury epidemiology · 2023Article
- Evaluating tools for capture-recapture model selection to estimate the size of hidden populations: it works in practice, but does it work in theory?Annals of epidemiology · 2023Article
- Towards a National Definition and Database for Nonfatal Shooting Incidents.Journal of urban health : bulletin of the New York Academy of Medicine · 2022Article
- Healthcare utilization and mental health outcomes among nonfatal shooting assault victims.Preventive medicine reports · 2022Article
- Using capture-recapture methods to estimate influenza hospitalization incidence rates.Influenza and other respiratory viruses · 2022Article
- Identifying nonfatal firearm assault incidents through linking police data and clinical records: Cohort study in Indianapolis, Indiana, 2007-2016.Preventive medicine · 2021Article
- Dynamic Panel Surveillance of COVID-19 Transmission in the United States to Inform Health Policy: Observational Statistical Study.Journal of medical Internet research · 2020Observational
- Introduction to the special issue on Gun violence: addressing a critical public health challenge.Journal of behavioral medicine · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Using a single source of data, such as police records, or combining data from multiple sources results in an undercount of gun-related injuries. To improve gun-related injury surveillance accuracy by using capture-recapture methods, data were culled from law enforcement, emergency departments, emergency medical services, media, and medical examiner records. The data overlap was operationalized using capture-recapture to generate estimates of uncounted gun incidents. Dependencies between data sources were controlled using log-linear modeling for accurate estimates. New Haven, Connecticut. The study population included subjects injuried/killed from a gun projectile. Incidence was measured using capture-recapture. 49 gun injuries occurred within the defined geography. No single source recorded more than 43 gun-related injuries/deaths. Log-linear modeling estimated the actual number of injuries to be 49.1 (95% CI 49-49.9). Capture-recapture may be less useful in large metropolitan areas that cross state geographical boundaries because of how government agency data are aggregated within each state. No single data source achieves complete gun-related case ascertainment. Log-linear and capture-recapture methods significantly improve gun-related injury estimates.
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Registered trials
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.