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 in | Journal of medical Internet research Vol. 22; no. 9; p. e21685 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
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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. |
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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 |
AuthorAffiliation_xml | – name: 5 College of Economics Jinan University Guangzhou China – name: 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 – name: 3 School of Public Health LKS Faculty of Medicine The University of Hong Kong Hong Kong China – name: 6 Center for Genomic Medicine Massachusetts General Hospital Harvard University Boston, MA United States – name: 7 Pulmonary & Critical Care Medicine Unit, Asthma Research Center Brigham and Women’s Hospital Harvard Medical School Boston, MA United States – name: 1 Department of Public Health and Preventive Medicine School of Medicine Jinan University Guangzhou China – name: 2 Faculty of Medicine International School Jinan University Guangzhou China |
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Cites_doi | 10.1109/mpul.2016.2627238 10.1111/gwao.12471 10.1111/irv.12226 10.21203/rs.3.rs-26576/v1 10.1371/journal.pmed.0050074 10.21037/atm.2018.11.55 10.1093/infdis/jiw400 10.1109/access.2019.2902905 10.1038/s41591-020-0832-5 10.1038/nature07634 10.2139/ssrn.1926431 10.2196/19284 10.1503/cmaj.1090215 10.1038/s41598-017-05957-y 10.1186/s40504-017-0065-7 10.1371/journal.pntd.0005295 10.1097/EDE.0000000000000274 10.1371/journal.pone.0139701 10.1186/s40504-017-0062-x 10.1371/journal.pone.0011596 10.1140/epjst/e2008-00640-0 10.1186/s13756-018-0359-4 10.1001/jama.2020.6602 10.1056/nejmp1307752 10.2196/publichealth.9136 10.2196/19359 10.1186/s40504-017-0063-9 10.1073/pnas.1006219107 10.1007/s11434-014-0499-8 10.1103/physreve.84.059904 10.1109/tsp.2013.2256902 10.1056/nejmp0900702 10.1007/bf02464422 |
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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 |
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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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Title | A New Era of Epidemiology: Digital Epidemiology for Investigating the COVID-19 Outbreak in China |
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