Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts
Abstract The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed...
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2021-02-01
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Online Access: | https://doi.org/10.1038/s41598-021-82873-2 |
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doaj-aeaecb332b854397b7c90b64e5bad4822021-02-14T12:36:40ZengNature Publishing GroupScientific Reports2045-23222021-02-0111111310.1038/s41598-021-82873-2Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contactsTamer Oraby0Michael G. Tyshenko1Jose Campo Maldonado2Kristina Vatcheva3Susie Elsaadany4Walid Q. Alali5Joseph C. Longenecker6Mustafa Al-Zoughool7School of Mathematical and Statistical Sciences, The University of Texas Rio Grande ValleyMcLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of OttawaSchool of Medicine, The University of Texas Rio Grande ValleySchool of Mathematical and Statistical Sciences, The University of Texas Rio Grande ValleyDepartment of Pathology and Laboratory Medicine, Faculty of Medicine, University of OttawaDepartment of Epidemiology and Biostatistics, Faculty of Public Health, Kuwait UniversityDepartment of Public Health Practice, Faculty of Public Health, Kuwait UniversityDepartment of Environmental and Occupational Health, Faculty of Public Health, Kuwait UniversityAbstract The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the $${R}_{0}$$ R 0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible $${R}_{0}$$ R 0 for the 152 countries and chose one country from each quarter as a representative for four social contact categories (Canada, China, Mexico, and Niger). The model was then used to predict the effects of lockdown timing in those four categories through the representative countries. The analysis for the effect of a lockdown was performed without the influence of the other control measures, like social distancing and mask wearing, to quantify its absolute effect. Hypothetical lockdown timing was shown to be the critical parameter in ameliorating pandemic peak incidence. More importantly, we found that well-timed lockdowns can split the peak of hospitalizations into two smaller distant peaks while extending the overall pandemic duration. The timing of lockdowns reveals that a “tunneling” effect on incidence can be achieved to bypass the peak and prevent pandemic caseloads from exceeding hospital capacity.https://doi.org/10.1038/s41598-021-82873-2 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Tamer Oraby Michael G. Tyshenko Jose Campo Maldonado Kristina Vatcheva Susie Elsaadany Walid Q. Alali Joseph C. Longenecker Mustafa Al-Zoughool |
spellingShingle |
Tamer Oraby Michael G. Tyshenko Jose Campo Maldonado Kristina Vatcheva Susie Elsaadany Walid Q. Alali Joseph C. Longenecker Mustafa Al-Zoughool Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts Scientific Reports |
author_facet |
Tamer Oraby Michael G. Tyshenko Jose Campo Maldonado Kristina Vatcheva Susie Elsaadany Walid Q. Alali Joseph C. Longenecker Mustafa Al-Zoughool |
author_sort |
Tamer Oraby |
title |
Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts |
title_short |
Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts |
title_full |
Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts |
title_fullStr |
Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts |
title_full_unstemmed |
Modeling the effect of lockdown timing as a COVID-19 control measure in countries with differing social contacts |
title_sort |
modeling the effect of lockdown timing as a covid-19 control measure in countries with differing social contacts |
publisher |
Nature Publishing Group |
series |
Scientific Reports |
issn |
2045-2322 |
publishDate |
2021-02-01 |
description |
Abstract The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the $${R}_{0}$$ R 0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible $${R}_{0}$$ R 0 for the 152 countries and chose one country from each quarter as a representative for four social contact categories (Canada, China, Mexico, and Niger). The model was then used to predict the effects of lockdown timing in those four categories through the representative countries. The analysis for the effect of a lockdown was performed without the influence of the other control measures, like social distancing and mask wearing, to quantify its absolute effect. Hypothetical lockdown timing was shown to be the critical parameter in ameliorating pandemic peak incidence. More importantly, we found that well-timed lockdowns can split the peak of hospitalizations into two smaller distant peaks while extending the overall pandemic duration. The timing of lockdowns reveals that a “tunneling” effect on incidence can be achieved to bypass the peak and prevent pandemic caseloads from exceeding hospital capacity. |
url |
https://doi.org/10.1038/s41598-021-82873-2 |
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