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Age-structured non-pharmaceutical interventions for optimal control of COVID-19 epidemic

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TLDR
It is shown that the optimal control strategy strongly outperforms other strategies such as uniform constant control over the whole populations or over its younger fraction and brings new facts the debate about age-based control interventions and open promising avenues of research, for instance of age- based contact tracing.
Abstract
In an epidemic, individuals can widely differ in the way they spread the infection depending on their age or on the number of days they have been infected for In the absence of pharmaceutical interventions such as a vaccine or treatment, non-pharmaceutical interventions (eg social distancing) are essential to mitigate the pandemic We develop an original approach to identify the optimal age-stratified control strategy to implement as a function of the time since the onset of the epidemic This is based on a model with a double continuous structure in terms of host age and time since infection By applying optimal control theory to this model, we identify a solution that minimizes deaths and costs associated with the implementation of the control strategy itself We also implement this strategy to three countries with contrasted age distributions (Burkina-Faso, France, and Vietnam) Overall, the optimal strategy varies over the course of the epidemic, with a more intense control early on, and depending on host age, with a stronger control for the older population, except in the scenario where the cost associated with the control is low In the latter scenario, we find strong differences across countries because the control extends to younger population in France and Vietnam 2-3 months after the onset of the epidemic, but not in Burkina Faso Finally, we show that the optimal control strategy strongly outperforms constant uniform control of the whole population or over its younger fraction This better understanding of the effect of age-based control interventions opens new perspectives for the field, especially for age-based contact tracing

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Journal ArticleDOI

Optimal Control of the COVID-19 Pandemic with Non-pharmaceutical Interventions

TL;DR: An optimal control analysis of a mathematical model of SARS-CoV-2 transmission found that a major factor that differentiates strategies that prioritize lives saved versus reduced time under control is how quickly control is relaxed once social distancing restrictions expire in May 2020.
Journal ArticleDOI

Beyond just “flattening the curve”: Optimal control of epidemics with purely non-pharmaceutical interventions

TL;DR: In this paper, an extended SEIR (susceptible-exposed-infectious-recovered) model and continuous-time optimal control theory are used to compute the optimal non-pharmaceutical intervention strategy for the case that a vaccine is never found and complete containment (eradication of the epidemic) is impossible.
Journal ArticleDOI

Beyond just "flattening the curve": Optimal control of epidemics with purely non-pharmaceutical interventions

TL;DR: The numerically computed optimal control strategy is a single-intervention scenario that goes beyond heuristically motivated interventions and simple “flattening of the curve” and is in fact a tightrope walk close to the stability boundary of the system, where socio-economic costs and the risk of a new outbreak must be constantly balanced against one another.
Journal ArticleDOI

Optimal control techniques based on infection age for the study of the COVID-19 epidemic

TL;DR: A model for the COVID-19 epidemic where the population is partitioned into classes corresponding to ages (that remain constant during the epidemic) is proposed, to take into account the infection age of the infected population.
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