论文标题
非药物干预对Covid-19的估计影响有多稳健？
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
论文作者
论文摘要
非药物干预措施（NPI）的有效性估计值在多大程度上受我们模型所做的假设影响的COVID-19的有效性估计？为了回答这个问题，我们研究了2个最先进的NPI有效性模型，并提出了6种具有不同结构假设的变体。特别是，我们研究了NPI有效性估计对看不见的国家的推广程度及其对未观察到的因素的敏感性。解释疾病传播中噪声的模型比较有利。我们进一步评估了流行病学参数和数据的不同选择的稳健估计。专注于假设传输噪声的模型，我们发现先前发布的结果在这些变量中非常健壮。最后，当某些共同的假设不成立时，我们从数学上讲，我们对NPI有效性估计值的解释为基础。
To what extent are effectiveness estimates of nonpharmaceutical interventions (NPIs) against COVID-19 influenced by the assumptions our models make? To answer this question, we investigate 2 state-of-the-art NPI effectiveness models and propose 6 variants that make different structural assumptions. In particular, we investigate how well NPI effectiveness estimates generalise to unseen countries, and their sensitivity to unobserved factors. Models that account for noise in disease transmission compare favourably. We further evaluate how robust estimates are to different choices of epidemiological parameters and data. Focusing on models that assume transmission noise, we find that previously published results are remarkably robust across these variables. Finally, we mathematically ground the interpretation of NPI effectiveness estimates when certain common assumptions do not hold.
