A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing

Gevertz, Jana L.; Greene, James M.; Sanchez-Tapia, Cynthia; Sontag, Eduardo D.

doi:10.1016/j.jtbi.2020.110539

Cited by 57 publications

(43 citation statements)

References 34 publications

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“…One study of the 37 Organization of Economic Cooperation and Development member countries found that implementing school closures and gathering bans 1 week earlier could have reduced mortality by 44% (7). A modeling study highlighted a "window of opportunity" for implementing social distancing directives, suggesting that even small delays could lead to much higher incidence rates (8). An observational study of 43 U.S. states and 41 countries that implemented stay-at-home orders, found that jurisdictions that delayed those orders experienced more prolonged outbreaks (9).…”

Section: Discussionmentioning

confidence: 99%

Mitigation Policies and COVID-19–Associated Mortality — 37 European Countries, January 23–June 30, 2020

Fuller

Hakim

Victory

et al. 2021

MMWR Morb. Mortal. Wkly. Rep.

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Section: Discussionmentioning

confidence: 99%

Mitigation Policies and COVID-19–Associated Mortality — 37 European Countries, January 23–June 30, 2020

Fuller

Hakim

Victory

et al. 2021

MMWR Morb. Mortal. Wkly. Rep.

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“…We completed and released this research early in the initial stages of the COVID-19 pandemic (at the end of February 2020) [20], but did not immediately pursue it further due to other pressing questions. In the interim, a number of other papers have emerged studying related questions, including [21][22][23][24][25]. It is clear from much of this work that nonpharmaceutical interventions are an important part of epidemic control.…”

Section: Introductionmentioning

confidence: 99%

Optimal timing of one-shot interventions for epidemic control

2021

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The interventions and outcomes in the ongoing COVID-19 pandemic are highly varied. The disease and the interventions both impose costs and harm on society. Some interventions with particularly high costs may only be implemented briefly. The design of optimal policy requires consideration of many intervention scenarios. In this paper we investigate the optimal timing of interventions that are not sustainable for a long period. Specifically, we look at at the impact of a single short-term non-repeated intervention (a “one-shot intervention”) on an epidemic and consider the impact of the intervention’s timing. To minimize the total number infected, the intervention should start close to the peak so that there is minimal rebound once the intervention is stopped. To minimise the peak prevalence, it should start earlier, leading to initial reduction and then having a rebound to the same prevalence as the pre-intervention peak rather than one very large peak. To delay infections as much as possible (as might be appropriate if we expect improved interventions or treatments to be developed), earlier interventions have clear benefit. In populations with distinct subgroups, synchronized interventions are less effective than targeting the interventions in each subcommunity separately.

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“…Intervention optimization has been proposed as a method to allow policymakers to fine-tune the characteristics of an intervention to minimize epidemiologically relevant outcome measures. Optimization has been explored for a range of potential COVID-19 NPI strategies, including single time-limited reductions to transmission [9,10], intermittent pulsing of NPIs [11,12] and gradual ramping-down of intervention measures following an initial reduction to transmission [12][13][14]. This has been explored in the context of minimizing the peak incidence or prevalence, analogous to 'flattening the curve' of an outbreak.…”

Section: Introductionmentioning

confidence: 99%

“…Despite theoretically optimal interventions being identified in a number of optimization analyses for COVID-19, the ability for policymakers to achieve these results in practice has been questioned [10]. This stems from the narrow windows for optimal implementation, with minor deviations from the optimal intervention timing, duration or magnitude often greatly reducing the efficacy of the NPI and therefore having severe human health consequences [10,13]. This sensitivity to implementation error is likely to be amplified in emerging outbreak situations such as the COVID-19 pandemic, with imperfect epidemiological knowledge of uncharacterized, novel pathogens preventing policymakers from fine-tuning NPIs to a narrow optimal parameter space.…”

Section: Introductionmentioning

confidence: 99%

Optimizing time-limited non-pharmaceutical interventions for COVID-19 outbreak control

Morgan

Woolhouse

Medley

et al. 2021

Phil. Trans. R. Soc. B

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Retrospective analyses of the non-pharmaceutical interventions (NPIs) used to combat the ongoing COVID-19 outbreak have highlighted the potential of optimizing interventions. These optimal interventions allow policymakers to manage NPIs to minimize the epidemiological and human health impacts of both COVID-19 and the intervention itself. Here, we use a susceptible–infectious–recovered (SIR) mathematical model to explore the feasibility of optimizing the duration, magnitude and trigger point of five different NPI scenarios to minimize the peak prevalence or the attack rate of a simulated UK COVID-19 outbreak. An optimal parameter space to minimize the peak prevalence or the attack rate was identified for each intervention scenario, with each scenario differing with regard to how reductions to transmission were modelled. However, we show that these optimal interventions are fragile, sensitive to epidemiological uncertainty and prone to implementation error. We highlight the use of robust, but suboptimal interventions as an alternative, with these interventions capable of mitigating the peak prevalence or the attack rate over a broader, more achievable parameter space, but being less efficacious than theoretically optimal interventions. This work provides an illustrative example of the concept of intervention optimization across a range of different NPI strategies. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’.

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A novel COVID-19 epidemiological model with explicit susceptible and asymptomatic isolation compartments reveals unexpected consequences of timing social distancing

Cited by 57 publications

References 34 publications

Mitigation Policies and COVID-19–Associated Mortality — 37 European Countries, January 23–June 30, 2020

Mitigation Policies and COVID-19–Associated Mortality — 37 European Countries, January 23–June 30, 2020

Optimal timing of one-shot interventions for epidemic control

Optimizing time-limited non-pharmaceutical interventions for COVID-19 outbreak control

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