美国各县和州的COVID-19周期性和可预测性的差异反映了保护措施的有效性
Claudio Bozzuto1, Anthony R Ives2
1Wildlife Analysis GmbH, Oetlisbergstrasse 38, 8053, Zurich, Switzerland. bozzuto@wildlifeanalysis.ch.
Scientific reports
|August 31, 2023
概括
预测COVID-19的传播受到不可预测动态的限制. 强有力的公共卫生措施减少了疾病传播,但也降低了可预测性,这是对安全的权衡.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 公共卫生 公共卫生
背景情况:
- 量化模型被广泛用于预测COVID-19在疫情期间的传播.
- 预测准确性本质上受到不可预测的疾病动态的限制.
研究的目的:
- 分析来自美国的COVID-19数据,以解释疾病传播可预测性跨司法管辖区的变化.
- 为了确定影响COVID-19传播率可预测性的因素,r(t).
主要方法:
- 利用统计和模拟模型的组合来分析COVID-19传播数据.
- 研究了随着时间的推移在美国各县和州的传播率,r (t) 的可预测性.
主要成果:
- COVID-19传播率,r(t),最多可预测9周 (县) 和8周 (州),占周期的40%和35%.
- 高可预测性与高周期性r (t) 相相关,并且与初始R0值负相关.
- 具有严重初始爆发和强有力的保护措施的司法管辖区显示,可预测性下降.
结论:
- 减少COVID-19传播的可预测性是有效的公共卫生干预措施的副产品.
- 持续的保护措施虽然有利于制疾病,但降低了传播预测的准确性.
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