Assessment of event-triggered policies of nonpharmaceutical interventions based on epidemiological indicators

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dc.contributor.authorde Wolff, Taco
dc.contributor.authorCastillo, Carla
dc.contributor.authorGajardo, Pedro
dc.contributor.authorLecaros, Rodrigo
dc.contributor.authorOlivar, Gerard
dc.contributor.authorRamírez, Héctor
dc.date.accessioned2022-02-28T20:17:17Z
dc.date.available2022-02-28T20:17:17Z
dc.date.issued2021
dc.description.abstractNonpharmaceutical 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.es
dc.description.versionVersión publicadaes
dc.identifier.citationCastillo-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/s00285-021-01669-0es
dc.identifier.urihttps://doi.org/10.1007/s00285-021-01669-0es
dc.identifier.urihttp://hdl.handle.net/11447/5622
dc.language.isoenes
dc.subjectControl epidemicses
dc.subjectEvent-triggered controles
dc.subjectTrade-offes
dc.subjectCOVID-19es
dc.titleAssessment of event-triggered policies of nonpharmaceutical interventions based on epidemiological indicatorses
dc.typeArticlees
dcterms.sourceJournal of Mathematical Biologyes

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