Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching.

ABSTRACT: Since the coronavirus disease (COVID-19) outbreak in December 2019, studies have been addressing diverse aspects in relation to COVID-19 and Variant of Concern 202012/01 (VOC 202012/01) such as potential symptoms and predictive tools. However, limited work has been performed towards the modelling of complex associations between the combined demographic attributes and varying nature of the COVID-19 infections across the globe. This study presents an intelligent approach to investigate the multi-dimensional associations between demographic attributes and COVID-19 global variations. We gather multiple demographic attributes and COVID-19 infection data (by 8 January 2021) from reliable sources, which are then processed by intelligent algorithms to identify the significant associations and patt

SUBMITTER: Khan W 

PROVIDER: S-EPMC7890495 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature