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利用捕获-再捕获方法提高枪支伤害监测准确性。

Bolstering gun injury surveillance accuracy using capture-recapture methods.

机构信息

Northwestern Feinberg School of Medicine, Chicago, USA.

Yale Department of Emergency Medicine, New Haven, USA.

出版信息

J Behav Med. 2019 Aug;42(4):674-680. doi: 10.1007/s10865-019-00017-4. Epub 2019 Aug 1.

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.

摘要

使用单一数据源(如警方记录)或结合多个数据源的数据会导致枪支伤害的漏报。为了通过捕获-再捕获方法提高枪支伤害监测的准确性,从执法部门、急诊部门、紧急医疗服务、媒体和法医记录中筛选数据。使用捕获-再捕获来实现数据重叠,以生成未计数的枪支事件的估计数。使用对数线性建模控制数据源之间的依赖关系,以获得准确的估计数。康涅狄格州纽黑文。研究人群包括因枪支弹丸受伤/死亡的受试者。使用捕获-再捕获来衡量发病率。在定义的地理区域内发生了 49 起枪支伤害事件。没有单一的来源记录超过 43 起枪支伤害/死亡事件。对数线性建模估计实际受伤人数为 49.1(95%CI 49-49.9)。由于政府机构数据在每个州内如何汇总,因此在跨越州地理边界的大城市中,捕获-再捕获的效果可能较差。没有单一的数据来源能够实现完整的枪支相关病例确定。对数线性和捕获-再捕获方法显著提高了枪支伤害的估计数。

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