A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China

A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available m...

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Published inJournal of medical Internet research Vol. 22; no. 9; p. e21685
Main Authors He, Zonglin, Zhang, Casper J P, Huang, Jian, Zhai, Jingyan, Zhou, Shuang, Chiu, Joyce Wai-Ting, Sheng, Jie, Tsang, Winghei, Akinwunmi, Babatunde O, Ming, Wai-Kit
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Published Canada JMIR Publications 17.09.2020
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Abstract A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.
AbstractList A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.
A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.A novel pneumonia-like coronavirus disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 has swept across China and the world. Public health measures that were effective in previous infection outbreaks (eg, wearing a face mask, quarantining) were implemented in this outbreak. Available multidimensional social network data that take advantage of the recent rapid development of information and communication technologies allow for an exploration of disease spread and control via a modernized epidemiological approach. By using spatiotemporal data and real-time information, we can provide more accurate estimates of disease spread patterns related to human activities and enable more efficient responses to the outbreak. Two real cases during the COVID-19 outbreak demonstrated the application of emerging technologies and digital data in monitoring human movements related to disease spread. Although the ethical issues related to using digital epidemiology are still under debate, the cases reported in this article may enable the identification of more effective public health measures, as well as future applications of such digitally directed epidemiological approaches in controlling infectious disease outbreaks, which offer an alternative and modern outlook on addressing the long-standing challenges in population health.
Author Zhai, Jingyan
Huang, Jian
Akinwunmi, Babatunde O
Zhang, Casper J P
Sheng, Jie
Tsang, Winghei
Zhou, Shuang
Chiu, Joyce Wai-Ting
Ming, Wai-Kit
He, Zonglin
AuthorAffiliation 4 MRC Centre for Environment and Health Department of Epidemiology and Biostatistics, School of Public Health, St Mary’s Campus Imperial College London London United Kingdom
2 Faculty of Medicine International School Jinan University Guangzhou China
1 Department of Public Health and Preventive Medicine School of Medicine Jinan University Guangzhou China
5 College of Economics Jinan University Guangzhou China
6 Center for Genomic Medicine Massachusetts General Hospital Harvard University Boston, MA United States
3 School of Public Health LKS Faculty of Medicine The University of Hong Kong Hong Kong China
7 Pulmonary & Critical Care Medicine Unit, Asthma Research Center Brigham and Women’s Hospital Harvard Medical School Boston, MA United States
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Copyright Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.09.2020.
Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.09.2020. 2020
Copyright_xml – notice: Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.09.2020.
– notice: Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.09.2020. 2020
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Keywords COVID-19
epidemiology
China
outbreak
control
risk
case study
public health
digital epidemiology
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License Zonglin He, Casper J P Zhang, Jian Huang, Jingyan Zhai, Shuang Zhou, Joyce Wai-Ting Chiu, Jie Sheng, Winghei Tsang, Babatunde O Akinwunmi, Wai-Kit Ming. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.09.2020.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
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SubjectTerms Betacoronavirus
China - epidemiology
Coronavirus Infections - epidemiology
Coronavirus Infections - virology
COVID-19
Disease Outbreaks - statistics & numerical data
Epidemiologic Methods
Humans
Masks
Pandemics
Pneumonia, Viral - epidemiology
Pneumonia, Viral - virology
Quarantine - statistics & numerical data
SARS-CoV-2
Viewpoint
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