How to Measure the Controllability of an Infectious Disease?,Physical Review X

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How to Measure the Controllability of an Infectious Disease?
Physical Review X ( IF 11.6 ) Pub Date : 2024-09-04 , DOI: 10.1103/physrevx.14.031041
Kris V. Parag _{1,

2}

Affiliation

Quantifying how difficult it is to control an emerging infectious disease is crucial to public health decision-making, providing valuable evidence on if targeted interventions, e.g., quarantine and isolation, can contain spread or when population wide controls, e.g., lockdowns, are warranted. The disease reproduction number

𝑅

or growth rate

𝑟

are universally assumed to measure controllability because

𝑅 = 1

and

𝑟 = 0

define when infections stop growing and hence the state of critical stability. Outbreaks with larger

𝑅

𝑟

are therefore interpreted as less controllable and requiring more stringent interventions. We prove this common interpretation is impractical and incomplete. We identify a positive feedback loop among infections intrinsically underlying disease transmission and evaluate controllability from how interventions disrupt this loop. The epidemic gain and delay margins, which, respectively, define how much we can scale infections (this scaling is known as gain) or delay interventions on this loop before stability is lost, provide rigorous measures of controllability. Outbreaks with smaller margins necessitate more control effort. Using these margins, we quantify how presymptomatic spread, surveillance limitations, variant dynamics, and superspreading shape controllability and demonstrate that

𝑅

and

𝑟

measure controllability only when interventions do not alter timings between the infections and are implemented without delay. Our margins are easily computed, interpreted, and reflect complex relationships among interventions, their implementation, and epidemiological dynamics.

中文翻译：

如何衡量传染病的可控性？

量化控制新发传染病的难度对于公共卫生决策至关重要，为有针对性的干预措施（例如检疫隔离和隔离）是否可以遏制传播或何时需要进行人群控制（例如封锁）提供有价值的证据。疾病繁殖数

R

或生长速率

r

通常被认为是衡量可控性的，因为

R=1

和

r=0

定义了感染何时停止生长，从而定义了临界稳定状态。因此，

R 或

r

较大的暴发被解释为更难控制，需要更严格的干预。我们证明这种常见的解释是不切实际和不完整的。我们在疾病传播的内在基础感染中确定了一个正反馈循环，并从干预措施如何破坏该循环中评估可控性。流行病增益和延迟边际分别定义了我们可以扩大感染的规模（这种规模称为增益）或在失去稳定性之前延迟对这个循环的干预，提供了严格的可控性措施。幅度较小的疫情需要更多的控制工作。利用这些边际，我们量化了症状前传播、监测限制、变异动力学和超级传播形状可控性，并证明只有当干预措施不会改变感染之间的时间并且毫不拖延地实施时，