e-space
Manchester Metropolitan University's Research Repository

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

    Khan, Wasiq, Hussain, Abir, Khan, Sohail Ahmed, Al-Jumailey, Mohammed, Nawaz, Raheel ORCID logoORCID: https://orcid.org/0000-0001-9588-0052 and Liatsis, Panos (2021) Analysing the impact of global demographic characteristics over the COVID-19 spread using class rule mining and pattern matching. Royal Society Open Science, 8 (1). p. 201823.

    [img]
    Preview
    Published Version
    Available under License Creative Commons Attribution.

    Download (2MB) | Preview

    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 patterns within the data. Statistical results and experts' reports indicate strong associations between COVID-19 severity levels across the globe and certain demographic attributes, e.g. female smokers, when combined together with other attributes. The outcomes will aid the understanding of the dynamics of disease spread and its progression, which in turn may support policy makers, medical specialists and society, in better understanding and effective management of the disease.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    216Downloads
    6 month trend
    136Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record