Assessment of event-triggered policies of nonpharmaceutical interventions based on epidemiological indicators
Date
2021
Type:
Article
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Abstract
Nonpharmaceutical interventions (NPI) such as banning public events or instituting
lockdowns have been widely applied around the world to control the current COVID-
19 pandemic. Typically, this type of intervention is imposed when an epidemiological
indicator in a given population exceeds a certain threshold. Then, the nonpharma-
ceutical intervention is lifted when the levels of the indicator used have decreased
sufficiently. What is the best indicator to use? In this paper, we propose a mathematical
framework to try to answer this question. More specifically, the proposed framework
permits to assess and compare different event-triggered controls based on epidemio-
logical indicators. Our methodology consists of considering some outcomes that are
consequences of the nonpharmaceutical interventions that a decision maker aims to
make as low as possible. The peak demand for intensive care units (ICU) and the total
number of days in lockdown are examples of such outcomes. If an epidemiological
indicator is used to trigger the interventions, there is naturally a trade-off between the
outcomes that can be seen as a curve parameterized by the trigger threshold to be used.
The computation of these curves for a group of indicators then allows the selection
of the best indicator the curve of which dominates the curves of the other indicators.
This methodology is illustrated with indicators in the context of COVID-19 using
deterministic compartmental models in discrete-time, although the framework can be
adapted for a larger class of models.
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Citation
Castillo-Laborde, C., de Wolff, T., Gajardo, P. et al. Assessment of event-triggered policies of nonpharmaceutical interventions based on epidemiological indicators. J. Math. Biol. 83, 42 (2021). https://doi.org/10.1007/s00285-021-01669-0
Keywords
Control epidemics, Event-triggered control, Trade-off, COVID-19