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Containing pandemics through targeted testing of households

BACKGROUND: While invasive social distancing measures have proven efficient to control the spread of pandemics failing wide-scale deployment of vaccines, they carry vast societal costs. The development of a diagnostic methodology for identifying COVID-19 infection through simple testing was a realit...

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Autores principales: Voigt, André, Martyushenko, Nikolay, Karlsen, Emil, Hall, Martina, Nyhamar, Kristen, Omholt, Stig William, Almaas, Eivind
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189703/
https://www.ncbi.nlm.nih.gov/pubmed/34107917
http://dx.doi.org/10.1186/s12879-021-06256-8
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author Voigt, André
Martyushenko, Nikolay
Karlsen, Emil
Hall, Martina
Nyhamar, Kristen
Omholt, Stig William
Almaas, Eivind
author_facet Voigt, André
Martyushenko, Nikolay
Karlsen, Emil
Hall, Martina
Nyhamar, Kristen
Omholt, Stig William
Almaas, Eivind
author_sort Voigt, André
collection PubMed
description BACKGROUND: While invasive social distancing measures have proven efficient to control the spread of pandemics failing wide-scale deployment of vaccines, they carry vast societal costs. The development of a diagnostic methodology for identifying COVID-19 infection through simple testing was a reality only a few weeks after the novel virus was officially announced. Thus, we were interested in exploring the ability of regular testing of non-symptomatic people to reduce cases and thereby offer a non-pharmaceutical tool for controlling the spread of a pandemic. METHODS: We developed a data-driven individual-based epidemiological network model in order to investigate epidemic countermeasures. This models is based on high-resolution demographic data for each municipality in Norway, and each person in the model is subject to Susceptible-Exposed-Infectious-Recovered (SEIR) dynamics. The model was calibrated against hospitalization data in Oslo, Norway, a city with a population of 700k which we have used as the simulations focus. RESULTS: Finding that large households function as hubs for the propagation of COVID-19, we assess the intervention efficiency of targeted pooled household testing (TPHT) repeatedly. For an outbreak with reproductive number R=1.4, we find that weekly TPHT of the 25% largest households brings R below unity. For the case of R=1.2, our results suggest that TPHT with the largest 25% of households every three days in an urban area is as effective as a lockdown in curbing the outbreak. Our investigations of different disease parameters suggest that these results are markedly improved for disease variants that more easily infect young people, and when compliance with self-isolation rules is less than perfect among suspected symptomatic cases. These results are quite robust to changes in the testing frequency, city size, and the household-size distribution. Our results are robust even with only 50% of households willing to participate in TPHT, provided the total number of tests stay unchanged. CONCLUSIONS: Pooled and targeted household testing appears to be a powerful non-pharmaceutical alternative to more invasive social-distancing and lock-down measures as a localized early response to contain epidemic outbreaks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12879-021-06256-8).
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spelling pubmed-81897032021-06-10 Containing pandemics through targeted testing of households Voigt, André Martyushenko, Nikolay Karlsen, Emil Hall, Martina Nyhamar, Kristen Omholt, Stig William Almaas, Eivind BMC Infect Dis Research BACKGROUND: While invasive social distancing measures have proven efficient to control the spread of pandemics failing wide-scale deployment of vaccines, they carry vast societal costs. The development of a diagnostic methodology for identifying COVID-19 infection through simple testing was a reality only a few weeks after the novel virus was officially announced. Thus, we were interested in exploring the ability of regular testing of non-symptomatic people to reduce cases and thereby offer a non-pharmaceutical tool for controlling the spread of a pandemic. METHODS: We developed a data-driven individual-based epidemiological network model in order to investigate epidemic countermeasures. This models is based on high-resolution demographic data for each municipality in Norway, and each person in the model is subject to Susceptible-Exposed-Infectious-Recovered (SEIR) dynamics. The model was calibrated against hospitalization data in Oslo, Norway, a city with a population of 700k which we have used as the simulations focus. RESULTS: Finding that large households function as hubs for the propagation of COVID-19, we assess the intervention efficiency of targeted pooled household testing (TPHT) repeatedly. For an outbreak with reproductive number R=1.4, we find that weekly TPHT of the 25% largest households brings R below unity. For the case of R=1.2, our results suggest that TPHT with the largest 25% of households every three days in an urban area is as effective as a lockdown in curbing the outbreak. Our investigations of different disease parameters suggest that these results are markedly improved for disease variants that more easily infect young people, and when compliance with self-isolation rules is less than perfect among suspected symptomatic cases. These results are quite robust to changes in the testing frequency, city size, and the household-size distribution. Our results are robust even with only 50% of households willing to participate in TPHT, provided the total number of tests stay unchanged. CONCLUSIONS: Pooled and targeted household testing appears to be a powerful non-pharmaceutical alternative to more invasive social-distancing and lock-down measures as a localized early response to contain epidemic outbreaks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s12879-021-06256-8). BioMed Central 2021-06-09 /pmc/articles/PMC8189703/ /pubmed/34107917 http://dx.doi.org/10.1186/s12879-021-06256-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Voigt, André
Martyushenko, Nikolay
Karlsen, Emil
Hall, Martina
Nyhamar, Kristen
Omholt, Stig William
Almaas, Eivind
Containing pandemics through targeted testing of households
title Containing pandemics through targeted testing of households
title_full Containing pandemics through targeted testing of households
title_fullStr Containing pandemics through targeted testing of households
title_full_unstemmed Containing pandemics through targeted testing of households
title_short Containing pandemics through targeted testing of households
title_sort containing pandemics through targeted testing of households
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8189703/
https://www.ncbi.nlm.nih.gov/pubmed/34107917
http://dx.doi.org/10.1186/s12879-021-06256-8
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