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Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019

For several decades, the World Health Organization has collected, maintained, and distributed invaluable country-specific disease surveillance data that allow experts to develop new analytical tools for disease tracking and forecasting. To capture the extent of available data within these sources, w...

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Autores principales: Simpson, Ryan B., Gottlieb, Jordyn, Zhou, Bingjie, Hartwick, Meghan A., Naumova, Elena N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804328/
https://www.ncbi.nlm.nih.gov/pubmed/33437025
http://dx.doi.org/10.1038/s41598-020-80842-9
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author Simpson, Ryan B.
Gottlieb, Jordyn
Zhou, Bingjie
Hartwick, Meghan A.
Naumova, Elena N.
author_facet Simpson, Ryan B.
Gottlieb, Jordyn
Zhou, Bingjie
Hartwick, Meghan A.
Naumova, Elena N.
author_sort Simpson, Ryan B.
collection PubMed
description For several decades, the World Health Organization has collected, maintained, and distributed invaluable country-specific disease surveillance data that allow experts to develop new analytical tools for disease tracking and forecasting. To capture the extent of available data within these sources, we proposed a completeness metric based on the effective time series length. Using FluNet records for 29 Pan-American countries from 2005 to 2019, we explored whether completeness was associated with health expenditure indicators adjusting for surveillance system heterogeneity. We observed steady improvements in completeness by 4.2–6.3% annually, especially after the A(H1N1)-2009 pandemic, when 24 countries reached > 95% completeness. Doubling in decadal health expenditure per capita was associated with ~ 7% increase in overall completeness. The proposed metric could navigate experts in assessing open access data quality and quantity for conducting credible statistical analyses, estimating disease trends, and developing outbreak forecasting systems.
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spelling pubmed-78043282021-01-13 Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019 Simpson, Ryan B. Gottlieb, Jordyn Zhou, Bingjie Hartwick, Meghan A. Naumova, Elena N. Sci Rep Article For several decades, the World Health Organization has collected, maintained, and distributed invaluable country-specific disease surveillance data that allow experts to develop new analytical tools for disease tracking and forecasting. To capture the extent of available data within these sources, we proposed a completeness metric based on the effective time series length. Using FluNet records for 29 Pan-American countries from 2005 to 2019, we explored whether completeness was associated with health expenditure indicators adjusting for surveillance system heterogeneity. We observed steady improvements in completeness by 4.2–6.3% annually, especially after the A(H1N1)-2009 pandemic, when 24 countries reached > 95% completeness. Doubling in decadal health expenditure per capita was associated with ~ 7% increase in overall completeness. The proposed metric could navigate experts in assessing open access data quality and quantity for conducting credible statistical analyses, estimating disease trends, and developing outbreak forecasting systems. Nature Publishing Group UK 2021-01-12 /pmc/articles/PMC7804328/ /pubmed/33437025 http://dx.doi.org/10.1038/s41598-020-80842-9 Text en © The Author(s) 2021 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/.
spellingShingle Article
Simpson, Ryan B.
Gottlieb, Jordyn
Zhou, Bingjie
Hartwick, Meghan A.
Naumova, Elena N.
Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019
title Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019
title_full Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019
title_fullStr Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019
title_full_unstemmed Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019
title_short Completeness of open access FluNet influenza surveillance data for Pan-America in 2005–2019
title_sort completeness of open access flunet influenza surveillance data for pan-america in 2005–2019
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7804328/
https://www.ncbi.nlm.nih.gov/pubmed/33437025
http://dx.doi.org/10.1038/s41598-020-80842-9
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