BIG DATA IN THE PANDEMIC: CLUSTERING, PREDICTIVE MODELS AND COVID-19 CONTROL STRATEGIES

• DOI: https://doi.org/10.22533/at.ed.1595125030115

• Palavras-chave: Big data or BigData, Covid-19, IA

• Keywords: Big data or BigData, Covid-19, AI

• Abstract:

  Introduction: The COVID-19 pandemic, which began in 2019, has brought substantial challenges to health systems, requiring rapid and effective responses. In this context, the use of Big Data and Artificial Intelligence (AI) technologies has emerged as a promising tool for analyzing and controlling the spread of the virus. This study presents a systematic review on the applications of Big Data and AI in the fight against COVID-19, with a focus on predictive modeling, social mobility and optimization of health resources. Objectives: The main objective of this study is to assess the impact and applications of these technologies in the management of the pandemic, identifying their potential and limitations, with a view to proposing a framework to help respond to future public health crises. Materials and Methods: Following the PRISMA methodology, a search was carried out in the PubMed and Embase databases to identify relevant studies between 2020 and 2024 using the descriptors "(Big Data) AND (COVID-19[MeSH Terms])" and ('big data'/exp OR 'big data' OR (big AND data)) AND ('covid 19'/exp OR 'covid 19') respectively, with a title filter, resulting in 309 articles. Rayyan4 software was used for screening, identifying 233 duplicates, giving a total of 182 articles. Strict inclusion and exclusion criteria were applied, resulting in a selection of 20 articles dealing with everything from modeling viral spread to analyzing data from mobility. Results: The analysis showed that predictive modeling with Big Data made it possible to identify patterns in the spread of the virus and predict the demand for health resources, such as hospital beds and ventilators. Studies have also shown that the use of mobility data has been key to understanding the impact of lockdown policies and identifying areas of greater risk. In terms of resource allocation, AI has been essential for optimizing the distribution of medical supplies, contributing to more effective management of available resources. However, the application of these technologies faces ethical and logistical challenges, such as data privacy and the need for a robust technological infrastructure. Conclusion: Big Data and AI have played a crucial role in the response to COVID-19, offering valuable insights and helping to formulate effective mitigation strategies. Despite the challenges, these technologies have proven indispensable for managing public health crises, highlighting the importance of continued investment in technological innovation. The lessons learned can guide the development of monitoring and response systems that are better prepared for future health emergencies.