Big data analytics as a tool for fighting pandemics: a systematic review of literature

被引:0
作者
Alana Corsi
Fabiane Florencio de Souza
Regina Negri Pagani
João Luiz Kovaleski
机构
[1] Federal University of Technology-Paraná (UTFPR) Câmpus Ponta Grossa,
来源
Journal of Ambient Intelligence and Humanized Computing | 2021年 / 12卷
关键词
Big data; Big data analytics; Pandemics; Epidemics; Systematic review of literature; COVID-19;
D O I
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中图分类号
学科分类号
摘要
Infectious and contagious diseases represent a major challenge for health systems worldwide, either in private or public sectors. More recently, with the increase in cases related to these problems, combined with the recent global pandemic of COVID-19, the need to study strategies to treat these health disturbs is even more latent. Big Data, as well as Big Data Analytics techniques, have been addressed in this context with the possibility of predicting, mapping, tracking, monitoring, and raising awareness about these epidemics and pandemics. Thus, the purpose of this study is to identify how BDA can help in cases of pandemics and epidemics. To achieve this purpose, a systematic review of literature was carried out using the methodology Methodi Ordinatio. The rigorous search resulted in a portfolio of 45 articles, retrived from scientific databases. For the collection and analysis of data, the softwares NVivo 12 and VOSviewer were used. The content analysis sought to identify how Big Data and Big Data Analytics can help fighting epidemics and pandemics. The types and sources of data used in cases of previous epidemics and pandemics were identified, as well as techniques for treating these data. The results showed that the main sources of data come from social media and Internet search engines. The most common techniques for analyzing these data involve the use of statistics, such as correlation and regression, combined with other techniques. Results shows that there is a fruitiful field of study to be explored by both areas, Big Data and Health.
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页码:9163 / 9180
页数:17
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