Big data analytics as a tool for fighting pandemics: a systematic review of literature
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ORIGINAL RESEARCH
Big data analytics as a tool for fighting pandemics: a systematic review of literature Alana Corsi1 · Fabiane Florencio de Souza1 · Regina Negri Pagani1 · João Luiz Kovaleski1 Received: 10 June 2020 / Accepted: 10 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract 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. Keywords Big data · Big data analytics · Pandemics · Epidemics · Systematic review of literature · COVID-19
1 Introduction The term Big Data has become widely used to describe the exponential growth of data in recent years (Yu et al. 2017; Wasim et al. 2019). Due to its popularity, its meaning is quite diverse. It can be understood as a huge volume of data, with high speed, diversity of topics, and variety, coming from different sources, such as cell phones, social networks,
* Alana Corsi [email protected] Fabiane Florencio de Souza [email protected] Regina Negri Pagani [email protected] João Luiz Kovaleski [email protected] 1
Federal University of Technology-Paraná (UTFPR) Câmpus Ponta Grossa, Av. Monteiro Lobato, s/n‑Km 04, Ponta Grossa, PR 84016‑210, Brazil
sensors, and other devices, which need specific techniques and tools for their processing (Manogaran and Lopez 2018). In this context, on a broader approach, Big Data Science is the study that encompasses different aspects of Big Data, including data storage capacity, and analysis speed, for instance. It can be employed on the study of different areas,
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