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使用计算机模型预测预防政策结果。

Using Computer Models to Predict Prevention Policy Outcomes.

作者信息

Holder Harold D

机构信息

Harold D. Holder, Ph.D., is director of and senior scientist at the Prevention Research Center, Berkeley, California.

出版信息

Alcohol Health Res World. 1996;20(4):252-260.

PMID:31798151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6876517/
Abstract

Computer simulation, or modeling, can illuminate the potential costs and effects of policy alternatives. The SimCom (Simulated Community) model has been under development for more than a decade and has been increasingly successful in simulating the effects of alcohol prevention policy. A recent application of SimCom to a northern California community's prevention efforts projected the results of an intervention designed to change the perceived risk of arrest for driving under the influence. SimCom simulated the effect of this intervention on the rate of alcohol-involved injury crashes and was able to generate crash estimates for 1993 to 1995 that later closely matched actual data for the same period. Statistical analyses of the northern California (i.e., experimental) site compared with data from a matched comparison site showed significantly fewer crashes in the experimental community. Although the complexity of computer models may present many more data collection, communication, and technical challenges than traditional policy research, with further refinement, computer simulations are likely to become vital components of prevention efforts to reduce alcohol-related problems.

摘要

计算机模拟,即建模,可以阐明政策替代方案的潜在成本和影响。SimCom(模拟社区)模型已经开发了十多年,并且在模拟酒精预防政策的影响方面越来越成功。最近,SimCom在加利福尼亚北部一个社区的预防工作中的应用预测了一项旨在改变酒后驾车被捕感知风险的干预措施的结果。SimCom模拟了这项干预措施对涉及酒精的伤害事故发生率的影响,并能够生成1993年至1995年的事故估计数,这些估计数后来与同一时期的实际数据非常吻合。对加利福尼亚北部(即实验)地点与匹配的对照地点的数据进行的统计分析表明,实验社区的事故明显减少。尽管计算机模型的复杂性可能比传统政策研究带来更多的数据收集、沟通和技术挑战,但随着进一步完善,计算机模拟很可能成为减少与酒精相关问题的预防工作的重要组成部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/8b30fcb3cb67/arhw-20-4-252f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/1ef02cf7483d/arhw-20-4-252f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/51dc1a63284e/arhw-20-4-252f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/17a2cb0736f5/arhw-20-4-252f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/70fb376bca0b/arhw-20-4-252f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/8b30fcb3cb67/arhw-20-4-252f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/1ef02cf7483d/arhw-20-4-252f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/51dc1a63284e/arhw-20-4-252f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/17a2cb0736f5/arhw-20-4-252f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/70fb376bca0b/arhw-20-4-252f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3354/6876517/8b30fcb3cb67/arhw-20-4-252f5.jpg

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