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A multilayer network model of Covid-19: Implications in public health policy in Costa Rica

Successful partnerships between researchers, experts, and public health authorities have been critical to navigate the challenges of the Covid-19 pandemic worldwide. In this collaboration, mathematical models have played a decisive role in informing public policy, with findings effectively translate...

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Autores principales: Sanchez, Fabio, Calvo, Juan G., Mery, Gustavo, García, Yury E., Vásquez, Paola, Barboza, Luis A., Pérez, María Dolores, Rivas, Tania
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9116977/
https://www.ncbi.nlm.nih.gov/pubmed/35636309
http://dx.doi.org/10.1016/j.epidem.2022.100577
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author Sanchez, Fabio
Calvo, Juan G.
Mery, Gustavo
García, Yury E.
Vásquez, Paola
Barboza, Luis A.
Pérez, María Dolores
Rivas, Tania
author_facet Sanchez, Fabio
Calvo, Juan G.
Mery, Gustavo
García, Yury E.
Vásquez, Paola
Barboza, Luis A.
Pérez, María Dolores
Rivas, Tania
author_sort Sanchez, Fabio
collection PubMed
description Successful partnerships between researchers, experts, and public health authorities have been critical to navigate the challenges of the Covid-19 pandemic worldwide. In this collaboration, mathematical models have played a decisive role in informing public policy, with findings effectively translated into public health measures that have shaped the pandemic in Costa Rica. As a result of interdisciplinary and cross-institutional collaboration, we constructed a multilayer network model that incorporates a diverse contact structure for each individual. In July 2020, we used this model to test the effect of lifting restrictions on population mobility after a so-called “epidemiological fence” imposed to contain the country’s first big wave of cases. Later, in August 2020, we used it to predict the effects of an open and close strategy (the Hammer and Dance). Scenarios constructed in July 2020 showed that lifting restrictions on population mobility after less than three weeks of epidemiological fence would produce a sharp increase in cases. Results from scenarios in August 2020 indicated that the Hammer and Dance strategy would only work with 50% of the population adhering to mobility restrictions. The development, evolution, and applications of a multilayer network model of Covid-19 in Costa Rica has guided decision-makers to anticipate implementing sanitary measures and contributed to gain valuable time to increase hospital capacity.
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spelling pubmed-91169772022-05-19 A multilayer network model of Covid-19: Implications in public health policy in Costa Rica Sanchez, Fabio Calvo, Juan G. Mery, Gustavo García, Yury E. Vásquez, Paola Barboza, Luis A. Pérez, María Dolores Rivas, Tania Epidemics Article Successful partnerships between researchers, experts, and public health authorities have been critical to navigate the challenges of the Covid-19 pandemic worldwide. In this collaboration, mathematical models have played a decisive role in informing public policy, with findings effectively translated into public health measures that have shaped the pandemic in Costa Rica. As a result of interdisciplinary and cross-institutional collaboration, we constructed a multilayer network model that incorporates a diverse contact structure for each individual. In July 2020, we used this model to test the effect of lifting restrictions on population mobility after a so-called “epidemiological fence” imposed to contain the country’s first big wave of cases. Later, in August 2020, we used it to predict the effects of an open and close strategy (the Hammer and Dance). Scenarios constructed in July 2020 showed that lifting restrictions on population mobility after less than three weeks of epidemiological fence would produce a sharp increase in cases. Results from scenarios in August 2020 indicated that the Hammer and Dance strategy would only work with 50% of the population adhering to mobility restrictions. The development, evolution, and applications of a multilayer network model of Covid-19 in Costa Rica has guided decision-makers to anticipate implementing sanitary measures and contributed to gain valuable time to increase hospital capacity. The Author(s). Published by Elsevier B.V. 2022-06 2022-05-18 /pmc/articles/PMC9116977/ /pubmed/35636309 http://dx.doi.org/10.1016/j.epidem.2022.100577 Text en © 2022 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Sanchez, Fabio
Calvo, Juan G.
Mery, Gustavo
García, Yury E.
Vásquez, Paola
Barboza, Luis A.
Pérez, María Dolores
Rivas, Tania
A multilayer network model of Covid-19: Implications in public health policy in Costa Rica
title A multilayer network model of Covid-19: Implications in public health policy in Costa Rica
title_full A multilayer network model of Covid-19: Implications in public health policy in Costa Rica
title_fullStr A multilayer network model of Covid-19: Implications in public health policy in Costa Rica
title_full_unstemmed A multilayer network model of Covid-19: Implications in public health policy in Costa Rica
title_short A multilayer network model of Covid-19: Implications in public health policy in Costa Rica
title_sort multilayer network model of covid-19: implications in public health policy in costa rica
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9116977/
https://www.ncbi.nlm.nih.gov/pubmed/35636309
http://dx.doi.org/10.1016/j.epidem.2022.100577
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