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Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City
OBJECTIVE: New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118998/ https://www.ncbi.nlm.nih.gov/pubmed/35601690 http://dx.doi.org/10.1093/jamiaopen/ooac029 |
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author | Ngai, Stephanie Sell, Jessica Baig, Samia Iqbal, Maryam Eddy, Meredith Culp, Gretchen Montesano, Matthew McGibbon, Emily Johnson, Kimberly Devinney, Katelynn Baumgartner, Jennifer Huynh, Mary Mathes, Robert Van Wye, Gretchen Fine, Annie D Thompson, Corinne N |
author_facet | Ngai, Stephanie Sell, Jessica Baig, Samia Iqbal, Maryam Eddy, Meredith Culp, Gretchen Montesano, Matthew McGibbon, Emily Johnson, Kimberly Devinney, Katelynn Baumgartner, Jennifer Huynh, Mary Mathes, Robert Van Wye, Gretchen Fine, Annie D Thompson, Corinne N |
author_sort | Ngai, Stephanie |
collection | PubMed |
description | OBJECTIVE: New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for internal use by other surveillance and epidemiology experts. MATERIALS AND METHODS: Existing surveillance databases and systems were leveraged to create daily analytic datasets of COVID-19 case and testing information, aggregated by week and key demographics. The dashboard was developed iteratively using R, and includes interactive graphs, tables, and maps summarizing recent COVID-19 epidemiologic trends. Additional data and interactive features were incorporated to provide further information on the spread of COVID-19 in NYC. RESULTS: The dashboard allows key staff to quickly review situational data, identify concerning trends, and easily maintain granular situational awareness of COVID-19 epidemiology in NYC. DISCUSSION: The dashboard is used to inform weekly surveillance summaries and alleviated the burden of manual report production on infectious disease epidemiologists. The system was built by and for epidemiologists, which is critical to its utility and functionality. Interactivity allows users to understand broad and granular data, and flexibility in dashboard development means new metrics and visualizations can be developed as needed. CONCLUSIONS: Additional investment and development of public health informatics tools, along with standardized frameworks for local health jurisdictions to analyze and visualize data in emergencies, are warranted. |
format | Online Article Text |
id | pubmed-9118998 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91189982022-05-20 Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City Ngai, Stephanie Sell, Jessica Baig, Samia Iqbal, Maryam Eddy, Meredith Culp, Gretchen Montesano, Matthew McGibbon, Emily Johnson, Kimberly Devinney, Katelynn Baumgartner, Jennifer Huynh, Mary Mathes, Robert Van Wye, Gretchen Fine, Annie D Thompson, Corinne N JAMIA Open Application Notes OBJECTIVE: New York City (NYC) experienced a large first wave of coronavirus disease 2019 (COVID-19) in the spring of 2020, but the Health Department lacked tools to easily visualize and analyze incoming surveillance data to inform response activities. To streamline ongoing surveillance, a group of infectious disease epidemiologists built an interactive dashboard using open-source software to monitor demographic, spatial, and temporal trends in COVID-19 epidemiology in NYC in near real-time for internal use by other surveillance and epidemiology experts. MATERIALS AND METHODS: Existing surveillance databases and systems were leveraged to create daily analytic datasets of COVID-19 case and testing information, aggregated by week and key demographics. The dashboard was developed iteratively using R, and includes interactive graphs, tables, and maps summarizing recent COVID-19 epidemiologic trends. Additional data and interactive features were incorporated to provide further information on the spread of COVID-19 in NYC. RESULTS: The dashboard allows key staff to quickly review situational data, identify concerning trends, and easily maintain granular situational awareness of COVID-19 epidemiology in NYC. DISCUSSION: The dashboard is used to inform weekly surveillance summaries and alleviated the burden of manual report production on infectious disease epidemiologists. The system was built by and for epidemiologists, which is critical to its utility and functionality. Interactivity allows users to understand broad and granular data, and flexibility in dashboard development means new metrics and visualizations can be developed as needed. CONCLUSIONS: Additional investment and development of public health informatics tools, along with standardized frameworks for local health jurisdictions to analyze and visualize data in emergencies, are warranted. Oxford University Press 2022-05-18 /pmc/articles/PMC9118998/ /pubmed/35601690 http://dx.doi.org/10.1093/jamiaopen/ooac029 Text en Published by Oxford University Press on behalf of the American Medical Informatics Association 2022. This work is written by (a) US Government employee(s) and is in the public domain in the US. |
spellingShingle | Application Notes Ngai, Stephanie Sell, Jessica Baig, Samia Iqbal, Maryam Eddy, Meredith Culp, Gretchen Montesano, Matthew McGibbon, Emily Johnson, Kimberly Devinney, Katelynn Baumgartner, Jennifer Huynh, Mary Mathes, Robert Van Wye, Gretchen Fine, Annie D Thompson, Corinne N Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City |
title | Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City |
title_full | Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City |
title_fullStr | Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City |
title_full_unstemmed | Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City |
title_short | Built by epidemiologists for epidemiologists: an internal COVID-19 dashboard for real-time situational awareness in New York City |
title_sort | built by epidemiologists for epidemiologists: an internal covid-19 dashboard for real-time situational awareness in new york city |
topic | Application Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118998/ https://www.ncbi.nlm.nih.gov/pubmed/35601690 http://dx.doi.org/10.1093/jamiaopen/ooac029 |
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