Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework

Jia，Qiong1; Guo，Yue2; Wang，Guanlin1; Barnes，Stuart J.3

2020-08-25

10.3390/ijerph17176161

International journal of environmental research and public health   影响因子和分区

1660-4601

Major public health incidents such as COVID-19 typically have characteristics of being sudden, uncertain, and hazardous. If a government can effectively accumulate big data from various sources and use appropriate analytical methods, it may quickly respond to achieve optimal public health decisions, thereby ameliorating negative impacts from a public health incident and more quickly restoring normality. Although there are many reports and studies examining how to use big data for epidemic prevention, there is still a lack of an effective review and framework of the application of big data in the fight against major public health incidents such as COVID-19, which would be a helpful reference for governments. This paper provides clear information on the characteristics of COVID-19, as well as key big data resources, big data for the visualization of pandemic prevention and control, close contact screening, online public opinion monitoring, virus host analysis, and pandemic forecast evaluation. A framework is provided as a multidimensional reference for the effective use of big data analytics technology to prevent and control epidemics (or pandemics). The challenges and suggestions with respect to applying big data for fighting COVID-19 are also discussed.

big data analysis COVID-19 deep learning epidemic prevention and control major public health incidents predictive analysis visual analysis

SCI ; SSCI

英语

其他

National Natural Science Foundation of China[71872061][71702045] ; Humanities and Social Sciences Foundation of the Ministry of Education in China[16YJC630028][17YJC630047] ; Fundamental Research Funds for the Central Universities[2018B20614][2017B14414]

Environmental Sciences & Ecology ; Public, Environmental & Occupational Health

Environmental Sciences ; Public, Environmental & Occupational Health

WOS:000569786300001

MDPI

2-s2.0-85090008417

Scopus

1.Department of Management,Hohai University,Nanjing,Hohai Business School,211100,China
2.Department of Information System and Management Engineering,Faculty of Business,Southern University of Science and Technology,Shenzhen,1088 Xueyuan Avenue,518055,China
3.CODA Research Centre,King's College London,Bush House,London WC2B 4BG,King's Business School,United Kingdom

Jia，Qiong,Guo，Yue,Wang，Guanlin,et al. Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework[J]. International journal of environmental research and public health,2020,17(17).

Jia，Qiong,Guo，Yue,Wang，Guanlin,&Barnes，Stuart J..(2020).Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework.International journal of environmental research and public health,17(17).

Jia，Qiong,et al."Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework".International journal of environmental research and public health 17.17(2020).