The Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard: data collection process, challenges faced, and lessons learned
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, 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
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.
Conflict of interest statement
Declaration of interests We declare no competing interests.
Copyright © 2022 Elsevier Ltd. All rights reserved.
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Source: PubMed