揭露流行病模式:用通用玛过度分散模型解码意大利COVID-19对死亡率的影响
Danila Azzolina1, Rosanna Comoretto2, Daniela Ferrante3
1Department of Translational Medical Science, Biostatistics and Clinical Trial Methodology Unit, Clinical Research Center DEMeTra, University of Naples Federico II, Naples, Italy.
BMC public health
|November 22, 2025
概括
COVID-19显著影响了意大利的死亡率,意大利北部的死亡率更高,男性和老年人. 到2023年,死亡率恢复正常,但增加的变异性持续存在,表明持续的不可预测性.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 意大利经历了严重的COVID-19影响,给医疗保健带来了压力,并造成了社会破坏.
- 以前的研究集中在早期的流行病死亡率上,忽视了最新的趋势.
- 了解长期过度死亡率对于公共卫生准备至关重要.
研究的目的:
- 分析2015-2023年意大利死亡率趋势,重点关注COVID-19的长期影响.
- 确定影响死亡率模式的人口和地理因素.
- 评估流行病后死亡率变异性的变化.
主要方法:
- 使用了通用化的位置,尺度和形状 (GAMLSS) 附加模型,并使用了通用化的马过度分散模型.
- 分析了按性别,年龄组 (65岁以下,65岁以上) 和地区 (北方与中南部) 分层的死亡率数据.
- 研究了不同流行病阶段的死亡率趋势.
主要成果:
- 观察到2020年初死亡率出现了显著的峰值,随后出现了较小的峰值,并于2023年恢复正常水平.
- 意大利北部,男性和老年人死亡率更高.
- 死亡率模式的过度分散性在流行后持续到2023年.
结论:
- 意大利的COVID-19死亡率影响复杂,区域和人口差异很大.
- 持续的过度分散表明死亡率模式的持续不可预测性.
- 强调需要针对弱势群体进行有针对性的干预,并制定适应性公共卫生战略.
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