We study the effectiveness of tracking and testing in mitigating or suppressing epidemic outbreaks, in combination with or as an alternative to quarantines and global lockdowns. We study these intervention methods on a network-based SEIR model, augmented with an additional probability to model symptomatic, asymptomatic and pre-symptomatic cases. Our focus is on the basic trade-offs between economic costs and human lives lost, and how these trade-offs change under different lockdown, quarantine, tracking and testing policies. Our main findings are as follows: (i) Tests combined with patient quarantines reduce both economic costs and mortality, but require a large-scale testing capacity to achieve a significant improvement; (ii) Tracking significantly reduces both economic costs and mortality; (iii) Tracking combined with a limited number of tests can achieve containment without lockdowns; (iv) If there is a small flow of new incoming infections, dynamic "On-Off" lockdowns are more efficient than fixed lockdowns. Our simulation results underline the extreme effectiveness of tracking and testing policies in reducing both economic costs and mortality and their potential to contain epidemic outbreaks without imposing social distancing restrictions. This highlights the difficult social question of trading-off these gains with the privacy loss that tracking necessarily entails.

中文翻译：

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关于 SEIR 模型中跟踪和测试的有效性

我们研究了跟踪和测试在减轻或抑制流行病爆发方面的有效性，结合或替代隔离和全球封锁。我们在基于网络的 SEIR 模型上研究这些干预方法，并增加了对有症状、无症状和症状前病例进行建模的额外概率。我们的重点是经济成本和人命损失之间的基本权衡，以及这些权衡在不同的锁定、隔离、跟踪和测试政策下如何变化。我们的主要发现如下： (i) 检测与患者隔离相结合可降低经济成本和死亡率，但需要大规模检测能力才能实现显着改善；㈡ 追踪大大降低了经济成本和死亡率；(iii) 跟踪结合有限数量的测试可以实现无封锁的遏制；(iv) 如果有少量新传入感染，动态“开-关”锁定比固定锁定更有效。我们的模拟结果强调了跟踪和测试政策在降低经济成本和死亡率方面的极端有效性，以及它们在不施加社会疏远限制的情况下遏制流行病爆发的潜力。这凸显了在这些收益与跟踪必然带来的隐私损失之间进行权衡的困难社会问题。我们的模拟结果强调了跟踪和测试政策在降低经济成本和死亡率方面的极端有效性，以及它们在不施加社会疏远限制的情况下遏制流行病爆发的潜力。这凸显了在这些收益与跟踪必然带来的隐私损失之间进行权衡的困难社会问题。我们的模拟结果强调了跟踪和测试政策在降低经济成本和死亡率方面的极端有效性，以及它们在不施加社会疏远限制的情况下遏制流行病爆发的潜力。这凸显了在这些收益与跟踪必然带来的隐私损失之间进行权衡的困难社会问题。