Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic

K. Nah; S. Chen; Y. Xiao; B. Tang; N. L. Bragazzi; J. M. Heffernan; A. Asgary; N. H. Ogden; J. Wu

doi:10.29020/nybg.ejpam.v13i3.3792

Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic

K. Nah
, S. Chen
, Y. Xiao
, B. Tang
, N. L. Bragazzi
, J. M. Heffernan
, A. Asgary
, N. H. Ogden
, J. Wu

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

We introduce a novel approach to inform the re-opening plan followed by a post-pandemic lockdown by integrating a stochastic optimization technique with a disease transmission model. We assess Ontarios re-opening plans as a case-study. Taking into account the uncertainties in contact rates during different re-opening phases, we find the optimal timing for the upcoming re-opening phase that maximizes the relaxation of social contacts under uncertainties, while not overwhelming the health system capacity before the arrival of effective therapeutics or vaccines.

Original language	English
Pages (from-to)	710-729
Number of pages	20
Journal	European Journal of Pure and Applied Mathematics
Volume	13
Issue number	3
DOIs	https://doi.org/10.29020/nybg.ejpam.v13i3.3792
State	Published - Jul 2020
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

COVID-19 social distancing
Lockdown exit strategy
Re-opening
Scenario tree
Stochastic optimization
Transmission dynamics model

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10.29020/nybg.ejpam.v13i3.3792

Cite this

Nah, K., Chen, S., Xiao, Y., Tang, B., Bragazzi, N. L., Heffernan, J. M., Asgary, A., Ogden, N. H., & Wu, J. (2020). Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic. European Journal of Pure and Applied Mathematics, 13(3), 710-729. https://doi.org/10.29020/nybg.ejpam.v13i3.3792

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title = "Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic",

abstract = "We introduce a novel approach to inform the re-opening plan followed by a post-pandemic lockdown by integrating a stochastic optimization technique with a disease transmission model. We assess Ontarios re-opening plans as a case-study. Taking into account the uncertainties in contact rates during different re-opening phases, we find the optimal timing for the upcoming re-opening phase that maximizes the relaxation of social contacts under uncertainties, while not overwhelming the health system capacity before the arrival of effective therapeutics or vaccines.",

keywords = "COVID-19 social distancing, Lockdown exit strategy, Re-opening, Scenario tree, Stochastic optimization, Transmission dynamics model",

author = "K. Nah and S. Chen and Y. Xiao and B. Tang and Bragazzi, \{N. L.\} and Heffernan, \{J. M.\} and A. Asgary and Ogden, \{N. H.\} and J. Wu",

year = "2020",

month = jul,

doi = "10.29020/nybg.ejpam.v13i3.3792",

language = "英语",

volume = "13",

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journal = "European Journal of Pure and Applied Mathematics",

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}

Nah, K, Chen, S, Xiao, Y, Tang, B, Bragazzi, NL, Heffernan, JM, Asgary, A, Ogden, NH & Wu, J 2020, 'Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic', European Journal of Pure and Applied Mathematics, vol. 13, no. 3, pp. 710-729. https://doi.org/10.29020/nybg.ejpam.v13i3.3792

TY - JOUR

T1 - Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic

AU - Nah, K.

AU - Chen, S.

AU - Xiao, Y.

AU - Tang, B.

AU - Bragazzi, N. L.

AU - Heffernan, J. M.

AU - Asgary, A.

AU - Ogden, N. H.

AU - Wu, J.

PY - 2020/7

Y1 - 2020/7

N2 - We introduce a novel approach to inform the re-opening plan followed by a post-pandemic lockdown by integrating a stochastic optimization technique with a disease transmission model. We assess Ontarios re-opening plans as a case-study. Taking into account the uncertainties in contact rates during different re-opening phases, we find the optimal timing for the upcoming re-opening phase that maximizes the relaxation of social contacts under uncertainties, while not overwhelming the health system capacity before the arrival of effective therapeutics or vaccines.

AB - We introduce a novel approach to inform the re-opening plan followed by a post-pandemic lockdown by integrating a stochastic optimization technique with a disease transmission model. We assess Ontarios re-opening plans as a case-study. Taking into account the uncertainties in contact rates during different re-opening phases, we find the optimal timing for the upcoming re-opening phase that maximizes the relaxation of social contacts under uncertainties, while not overwhelming the health system capacity before the arrival of effective therapeutics or vaccines.

KW - COVID-19 social distancing

KW - Lockdown exit strategy

KW - Re-opening

KW - Scenario tree

KW - Stochastic optimization

KW - Transmission dynamics model

UR - https://www.scopus.com/pages/publications/85089905843

U2 - 10.29020/nybg.ejpam.v13i3.3792

DO - 10.29020/nybg.ejpam.v13i3.3792

M3 - 文章

AN - SCOPUS:85089905843

SN - 1307-5543

VL - 13

SP - 710

EP - 729

JO - European Journal of Pure and Applied Mathematics

JF - European Journal of Pure and Applied Mathematics

IS - 3

ER -

Scenario tree and adaptive decision making on optimal type and timing for intervention and social-economic activity changes to manage the COVID-19 pandemic

Abstract

UN SDGs

Keywords

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