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The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned
On Jan 22, 2020, a day after the USA reported its first COVID-19 case, the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) launched the first global real-time coronavirus surveillance system: the JHU CSSE COVID-19 Dashboard. As of June 1, 2022, the dashboard has served...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432867/ https://www.ncbi.nlm.nih.gov/pubmed/36057267 http://dx.doi.org/10.1016/S1473-3099(22)00434-0 |
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author | Dong, Ensheng Ratcliff, Jeremy Goyea, Tamara D Katz, Aaron Lau, Ryan Ng, Timothy K Garcia, Beatrice Bolt, Evan Prata, Sarah Zhang, David Murray, Reina C Blake, Mara R Du, Hongru Ganjkhanloo, Fardin Ahmadi, Farzin Williams, Jason Choudhury, Sayeed Gardner, Lauren M |
author_facet | Dong, Ensheng Ratcliff, Jeremy Goyea, Tamara D Katz, Aaron Lau, Ryan Ng, Timothy K Garcia, Beatrice Bolt, Evan Prata, Sarah Zhang, David Murray, Reina C Blake, Mara R Du, Hongru Ganjkhanloo, Fardin Ahmadi, Farzin Williams, Jason Choudhury, Sayeed Gardner, Lauren M |
author_sort | Dong, Ensheng |
collection | PubMed |
description | On Jan 22, 2020, a day after the USA reported its first COVID-19 case, the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) launched the first global real-time coronavirus surveillance system: the JHU CSSE COVID-19 Dashboard. As of June 1, 2022, the dashboard has served the global audience for more than 30 consecutive months, totalling over 226 billion feature layer requests and 3·6 billion page views. The highest daily record was set on March 29, 2020, with more than 4·6 billion requests and over 69 million views. This Personal View reveals the fundamental technical details of the entire data system underlying the dashboard, including data collection, data fusion logic, data curation and sharing, anomaly detection, data corrections, and the human resources required to support such an effort. The Personal View also covers the challenges, ranging from data visualisation to reporting standardisation. The details presented here help develop a framework for future, large-scale public health-related data collection and reporting. |
format | Online Article Text |
id | pubmed-9432867 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94328672022-09-01 The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned Dong, Ensheng Ratcliff, Jeremy Goyea, Tamara D Katz, Aaron Lau, Ryan Ng, Timothy K Garcia, Beatrice Bolt, Evan Prata, Sarah Zhang, David Murray, Reina C Blake, Mara R Du, Hongru Ganjkhanloo, Fardin Ahmadi, Farzin Williams, Jason Choudhury, Sayeed Gardner, Lauren M Lancet Infect Dis Personal View On Jan 22, 2020, a day after the USA reported its first COVID-19 case, the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) launched the first global real-time coronavirus surveillance system: the JHU CSSE COVID-19 Dashboard. As of June 1, 2022, the dashboard has served the global audience for more than 30 consecutive months, totalling over 226 billion feature layer requests and 3·6 billion page views. The highest daily record was set on March 29, 2020, with more than 4·6 billion requests and over 69 million views. This Personal View reveals the fundamental technical details of the entire data system underlying the dashboard, including data collection, data fusion logic, data curation and sharing, anomaly detection, data corrections, and the human resources required to support such an effort. The Personal View also covers the challenges, ranging from data visualisation to reporting standardisation. The details presented here help develop a framework for future, large-scale public health-related data collection and reporting. Elsevier Ltd. 2022-12 2022-08-31 /pmc/articles/PMC9432867/ /pubmed/36057267 http://dx.doi.org/10.1016/S1473-3099(22)00434-0 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Personal View Dong, Ensheng Ratcliff, Jeremy Goyea, Tamara D Katz, Aaron Lau, Ryan Ng, Timothy K Garcia, Beatrice Bolt, Evan Prata, Sarah Zhang, David Murray, Reina C Blake, Mara R Du, Hongru Ganjkhanloo, Fardin Ahmadi, Farzin Williams, Jason Choudhury, Sayeed Gardner, Lauren M The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned |
title | The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned |
title_full | The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned |
title_fullStr | The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned |
title_full_unstemmed | The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned |
title_short | The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned |
title_sort | johns hopkins university center for systems science and engineering covid-19 dashboard: data collection process, challenges faced, and lessons learned |
topic | Personal View |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432867/ https://www.ncbi.nlm.nih.gov/pubmed/36057267 http://dx.doi.org/10.1016/S1473-3099(22)00434-0 |
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