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COVID-19 heterogeneity in islands chain environment

BACKGROUND: It is critical to capture data and modeling from the COVID-19 pandemic to understand as much as possible and prepare for future epidemics and possible pandemics. The Hawaiian Islands provide a unique opportunity to study heterogeneity and demographics in a controlled environment due to t...

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Autores principales: Chyba, Monique, Kunwar, Prateek, Mileyko, Yuriy, Tong, Alan, Lau, Winnie, Koniges, Alice
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9116625/
https://www.ncbi.nlm.nih.gov/pubmed/35584085
http://dx.doi.org/10.1371/journal.pone.0263866
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author Chyba, Monique
Kunwar, Prateek
Mileyko, Yuriy
Tong, Alan
Lau, Winnie
Koniges, Alice
author_facet Chyba, Monique
Kunwar, Prateek
Mileyko, Yuriy
Tong, Alan
Lau, Winnie
Koniges, Alice
author_sort Chyba, Monique
collection PubMed
description BACKGROUND: It is critical to capture data and modeling from the COVID-19 pandemic to understand as much as possible and prepare for future epidemics and possible pandemics. The Hawaiian Islands provide a unique opportunity to study heterogeneity and demographics in a controlled environment due to the geographically closed borders and mostly uniform pandemic-induced governmental controls and restrictions. OBJECTIVE: The goal of the paper is to quantify the differences and similarities in the spread of COVID-19 among different Hawaiian islands as well as several other archipelago and islands, which could potentially help us better understand the effect of differences in social behavior and various mitigation measures. The approach should be robust with respect to the unavoidable differences in time, as the arrival of the virus and promptness of mitigation measures may vary significantly among the chosen locations. At the same time, the comparison should be able to capture differences in the overall pandemic experience. METHODS: We examine available data on the daily cases, positivity rates, mobility, and employ a compartmentalized model fitted to the daily cases to develop appropriate comparison approaches. In particular, we focus on merge trees for the daily cases, normalized positivity rates, and baseline transmission rates of the models. RESULTS: We observe noticeable differences among different Hawaiian counties and interesting similarities between some Hawaiian counties and other geographic locations. The results suggest that mitigation measures should be more localized, that is, targeting the county level rather than the state level if the counties are reasonably insulated from one another. We also notice that the spread of the disease is very sensitive to unexpected events and certain changes in mitigation measures. CONCLUSIONS: Despite being a part of the same archipelago and having similar protocols for mitigation measures, different Hawaiian counties exhibit quantifiably different dynamics of the spread of the disease. One potential explanation is that not sufficiently targeted mitigation measures are incapable of handling unexpected, localized outbreak events. At a larger-scale view of the general spread of the disease on the Hawaiian island counties, we find very interesting similarities between individual Hawaiian islands and other archipelago and islands.
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spelling pubmed-91166252022-05-19 COVID-19 heterogeneity in islands chain environment Chyba, Monique Kunwar, Prateek Mileyko, Yuriy Tong, Alan Lau, Winnie Koniges, Alice PLoS One Research Article BACKGROUND: It is critical to capture data and modeling from the COVID-19 pandemic to understand as much as possible and prepare for future epidemics and possible pandemics. The Hawaiian Islands provide a unique opportunity to study heterogeneity and demographics in a controlled environment due to the geographically closed borders and mostly uniform pandemic-induced governmental controls and restrictions. OBJECTIVE: The goal of the paper is to quantify the differences and similarities in the spread of COVID-19 among different Hawaiian islands as well as several other archipelago and islands, which could potentially help us better understand the effect of differences in social behavior and various mitigation measures. The approach should be robust with respect to the unavoidable differences in time, as the arrival of the virus and promptness of mitigation measures may vary significantly among the chosen locations. At the same time, the comparison should be able to capture differences in the overall pandemic experience. METHODS: We examine available data on the daily cases, positivity rates, mobility, and employ a compartmentalized model fitted to the daily cases to develop appropriate comparison approaches. In particular, we focus on merge trees for the daily cases, normalized positivity rates, and baseline transmission rates of the models. RESULTS: We observe noticeable differences among different Hawaiian counties and interesting similarities between some Hawaiian counties and other geographic locations. The results suggest that mitigation measures should be more localized, that is, targeting the county level rather than the state level if the counties are reasonably insulated from one another. We also notice that the spread of the disease is very sensitive to unexpected events and certain changes in mitigation measures. CONCLUSIONS: Despite being a part of the same archipelago and having similar protocols for mitigation measures, different Hawaiian counties exhibit quantifiably different dynamics of the spread of the disease. One potential explanation is that not sufficiently targeted mitigation measures are incapable of handling unexpected, localized outbreak events. At a larger-scale view of the general spread of the disease on the Hawaiian island counties, we find very interesting similarities between individual Hawaiian islands and other archipelago and islands. Public Library of Science 2022-05-18 /pmc/articles/PMC9116625/ /pubmed/35584085 http://dx.doi.org/10.1371/journal.pone.0263866 Text en © 2022 Chyba et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chyba, Monique
Kunwar, Prateek
Mileyko, Yuriy
Tong, Alan
Lau, Winnie
Koniges, Alice
COVID-19 heterogeneity in islands chain environment
title COVID-19 heterogeneity in islands chain environment
title_full COVID-19 heterogeneity in islands chain environment
title_fullStr COVID-19 heterogeneity in islands chain environment
title_full_unstemmed COVID-19 heterogeneity in islands chain environment
title_short COVID-19 heterogeneity in islands chain environment
title_sort covid-19 heterogeneity in islands chain environment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9116625/
https://www.ncbi.nlm.nih.gov/pubmed/35584085
http://dx.doi.org/10.1371/journal.pone.0263866
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