Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
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
_version_ 1784710618957217792
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
work_keys_str_mv AT ngaistephanie builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT selljessica builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT baigsamia builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT iqbalmaryam builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT eddymeredith builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT culpgretchen builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT montesanomatthew builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT mcgibbonemily builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT johnsonkimberly builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT devinneykatelynn builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT baumgartnerjennifer builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT huynhmary builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT mathesrobert builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT vanwyegretchen builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT fineannied builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity
AT thompsoncorinnen builtbyepidemiologistsforepidemiologistsaninternalcovid19dashboardforrealtimesituationalawarenessinnewyorkcity