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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

Authors :
Ensheng Dong
Jeremy Ratcliff
Tamara D Goyea
Aaron Katz
Ryan Lau
Timothy K Ng
Beatrice Garcia
Evan Bolt
Sarah Prata
David Zhang
Reina C Murray
Mara R Blake
Hongru Du
Fardin Ganjkhanloo
Farzin Ahmadi
Jason Williams
Sayeed Choudhury
Lauren M Gardner
Source :
The Lancet Infectious Diseases. 22:e370-e376
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

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.

Details

ISSN :
14733099
Volume :
22
Database :
OpenAIRE
Journal :
The Lancet Infectious Diseases
Accession number :
edsair.doi.dedup.....dadf5dd4dfa4b6022a70f04b845e1261
Full Text :
https://doi.org/10.1016/s1473-3099(22)00434-0