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Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States

BACKGROUND: COVID-19 is an important public health concern due to its high morbidity, mortality and socioeconomic impact. Its burden varies by geographic location affecting some communities more than others. Identifying these disparities is important for guiding health planning and service provision...

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Autores principales: Deb Nath, Nirmalendu, Khan, Md Marufuzzaman, Schmidt, Matthew, Njau, Grace, Odoi, Agricola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116449/
https://www.ncbi.nlm.nih.gov/pubmed/37081453
http://dx.doi.org/10.1186/s12889-023-15571-5
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author Deb Nath, Nirmalendu
Khan, Md Marufuzzaman
Schmidt, Matthew
Njau, Grace
Odoi, Agricola
author_facet Deb Nath, Nirmalendu
Khan, Md Marufuzzaman
Schmidt, Matthew
Njau, Grace
Odoi, Agricola
author_sort Deb Nath, Nirmalendu
collection PubMed
description BACKGROUND: COVID-19 is an important public health concern due to its high morbidity, mortality and socioeconomic impact. Its burden varies by geographic location affecting some communities more than others. Identifying these disparities is important for guiding health planning and service provision. Therefore, this study investigated geographical disparities and temporal changes of the percentage of positive COVID-19 tests and COVID-19 incidence risk in North Dakota. METHODS: COVID-19 retrospective data on total number of tests and confirmed cases reported in North Dakota from March 2020 to September 2021 were obtained from the North Dakota COVID-19 Dashboard and Department of Health, respectively. Monthly incidence risks of the disease were calculated and reported as number of cases per 100,000 persons. To adjust for geographic autocorrelation and the small number problem, Spatial Empirical Bayesian (SEB) smoothing was performed using queen spatial weights. Identification of high-risk geographic clusters of percentages of positive tests and COVID-19 incidence risks were accomplished using Tango’s flexible spatial scan statistic. ArcGIS was used to display and visiualize the geographic distribution of percentages of positive tests, COVID-19 incidence risks, and high-risk clusters. RESULTS: County-level percentages of positive tests and SEB incidence risks varied by geographic location ranging from 0.11% to 13.67% and 122 to 16,443 cases per 100,000 persons, respectively. Clusters of high percentages of positive tests were consistently detected in the western part of the state. High incidence risks were identified in the central and south-western parts of the state, where significant high-risk spatial clusters were reported. Additionally, two peaks (August 2020-December 2020 and August 2021-September 2021) and two non-peak periods of COVID-19 incidence risk (March 2020-July 2020 and January 2021-July 2021) were observed. CONCLUSION: Geographic disparities in COVID incidence risks exist in North Dakota with high-risk clusters being identified in the rural central and southwest parts of the state. These findings are useful for guiding intervention strategies by identifying high risk communities so that resources for disease control can be better allocated to communities in need based on empirical evidence. Future studies will investigate predictors of the identified disparities so as to guide planning, disease control and health policy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15571-5.
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spelling pubmed-101164492023-04-21 Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States Deb Nath, Nirmalendu Khan, Md Marufuzzaman Schmidt, Matthew Njau, Grace Odoi, Agricola BMC Public Health Research BACKGROUND: COVID-19 is an important public health concern due to its high morbidity, mortality and socioeconomic impact. Its burden varies by geographic location affecting some communities more than others. Identifying these disparities is important for guiding health planning and service provision. Therefore, this study investigated geographical disparities and temporal changes of the percentage of positive COVID-19 tests and COVID-19 incidence risk in North Dakota. METHODS: COVID-19 retrospective data on total number of tests and confirmed cases reported in North Dakota from March 2020 to September 2021 were obtained from the North Dakota COVID-19 Dashboard and Department of Health, respectively. Monthly incidence risks of the disease were calculated and reported as number of cases per 100,000 persons. To adjust for geographic autocorrelation and the small number problem, Spatial Empirical Bayesian (SEB) smoothing was performed using queen spatial weights. Identification of high-risk geographic clusters of percentages of positive tests and COVID-19 incidence risks were accomplished using Tango’s flexible spatial scan statistic. ArcGIS was used to display and visiualize the geographic distribution of percentages of positive tests, COVID-19 incidence risks, and high-risk clusters. RESULTS: County-level percentages of positive tests and SEB incidence risks varied by geographic location ranging from 0.11% to 13.67% and 122 to 16,443 cases per 100,000 persons, respectively. Clusters of high percentages of positive tests were consistently detected in the western part of the state. High incidence risks were identified in the central and south-western parts of the state, where significant high-risk spatial clusters were reported. Additionally, two peaks (August 2020-December 2020 and August 2021-September 2021) and two non-peak periods of COVID-19 incidence risk (March 2020-July 2020 and January 2021-July 2021) were observed. CONCLUSION: Geographic disparities in COVID incidence risks exist in North Dakota with high-risk clusters being identified in the rural central and southwest parts of the state. These findings are useful for guiding intervention strategies by identifying high risk communities so that resources for disease control can be better allocated to communities in need based on empirical evidence. Future studies will investigate predictors of the identified disparities so as to guide planning, disease control and health policy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-023-15571-5. BioMed Central 2023-04-20 /pmc/articles/PMC10116449/ /pubmed/37081453 http://dx.doi.org/10.1186/s12889-023-15571-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Deb Nath, Nirmalendu
Khan, Md Marufuzzaman
Schmidt, Matthew
Njau, Grace
Odoi, Agricola
Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States
title Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States
title_full Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States
title_fullStr Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States
title_full_unstemmed Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States
title_short Geographic disparities and temporal changes of COVID-19 incidence risks in North Dakota, United States
title_sort geographic disparities and temporal changes of covid-19 incidence risks in north dakota, united states
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116449/
https://www.ncbi.nlm.nih.gov/pubmed/37081453
http://dx.doi.org/10.1186/s12889-023-15571-5
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