疾病-死亡模型作为慢性疾病负担预测的框架:应用于心理健康流行病学
Chisato Ito1, Tobias Kurth1, Bernhard T Baune2,3,4
1Institute of Public Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
这项研究引入了一种新的疾病死亡模型来预测慢性疾病负担,发现到2030年在德国,女性患焦虑症的数量将减少,而男性患焦虑症的数量将增加. 这种疾病建模方法有助于公共卫生规划.
科学领域:
- 公共卫生和流行病学
- 数学建模的数学建模
- 慢性疾病管理 慢性疾病管理
背景情况:
- 准确估计未来的疾病负担对于有效的公共卫生决策至关重要.
- 慢性疾病的多状态建模,虽然在历史上被探索过,但在当前的应用中存在局限性.
- 现有的模型往往不能完全考虑疾病缓解,特别适用于心理健康状况.
研究的目的:
- 引入一个离散时间疾病死亡模型,采用一种新型的递归公式来预测慢性疾病负担.
- 调整模型用于潜在缓解的疾病,以焦虑障碍为例.
- 预测从2019年到2030年在德国的焦虑障碍负担.
主要方法:
- 开发了一种离散时间疾病死亡模型,其中包含了慢性疾病和缓解的复发公式.
- 利用了2019年全球疾病负担研究数据和德国人口预测进行分析.
- 将回归模型应用于历史流行和发病数据,模拟差异性死亡风险和缓解.
主要成果:
- 疾病死亡模型预计,到2030年,德国女性病例将减少52,114例,男性病例将增加166,870.
- 简单的流行率外推得出明显不同的预测:女性病例增加了381,770例,男性病例增加了272,446例.
- 该模型证明适用于不可逆转的慢性疾病和缓解的疾病,如焦虑症.
结论:
- 离散时间疾病死亡模型为预测未来的疾病负担提供了一个强大的框架,考虑了缓解.
- 调查结果突出了德国预计的焦虑症负担的性别特异性趋势.
- 这种建模技术可以通过变化的过渡概率来扩展到模拟,帮助制定公共卫生战略.
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