论文标题
印度锁定避免死亡吗？
Did the Indian lockdown avert deaths?
论文作者
论文摘要
在SEIR模型的背景下，我们考虑了在流行病的早期阶段施加和解除的锁定。我们表明，在这些模型中，尽管这样的锁定可能会延迟死亡，但最终并没有避免大量死亡。因此，在这些模型中，不能通过简单地将锁定结束时死亡的数字与预计的数字进行比较而在同一日期中而没有锁定的情况下的死亡数字来衡量锁定的功效。我们提供了一个简单但强大的启发式论点，以解释为什么此结论应该推广到更精细的隔间模型。我们定性地讨论了锁定的一些重要影响，这些影响超出了简单模型的范围，但可能导致其增加或减少流行病的最终损失。鉴于这些影响在印度的重要性以及当前可用数据的局限性，我们得出结论，简单的流行病学模型不能用于可靠地量化印度锁定对COVID-19造成的死亡的影响。
Within the context of SEIR models, we consider a lockdown that is both imposed and lifted at an early stage of an epidemic. We show that, in these models, although such a lockdown may delay deaths, it eventually does not avert a significant number of fatalities. Therefore, in these models, the efficacy of a lockdown cannot be gauged by simply comparing figures for the deaths at the end of the lockdown with the projected figure for deaths by the same date without the lockdown. We provide a simple but robust heuristic argument to explain why this conclusion should generalize to more elaborate compartmental models. We qualitatively discuss some important effects of a lockdown, which go beyond the scope of simple models, but could cause it to increase or decrease an epidemic's final toll. Given the significance of these effects in India, and the limitations of currently available data, we conclude that simple epidemiological models cannot be used to reliably quantify the impact of the Indian lockdown on fatalities caused by the COVID-19 pandemic.
