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The CP‐ABM approach for modelling COVID‐19 infection dynamics and quantifying the effects of non‐pharmaceutical interventions

Pattern Recognition, ISSN: 0031-3203, Vol: 130, Page: 108790
2022
  • 15
    Citations
  • 0
    Usage
  • 33
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    15
  • Captures
    33
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

New Findings from Queen's University Belfast Describe Advances in COVID-19 (The Cp-abm Approach for Modelling Covid-19 Infection Dynamics and Quantifying the Effects of Non-pharmaceutical Interventions)

2023 AUG 17 (NewsRx) -- By a News Reporter-Staff News Editor at NewsRx COVID-19 Daily -- Investigators publish new report on Coronavirus - COVID-19. According

Article Description

The motivation for this research is to develop an approach that reliably captures the disease dynamics of COVID-19 for an entire population in order to identify the key events driving change in the epidemic through accurate estimation of daily COVID-19 cases. This has been achieved through the new CP-ABM approach which uniquely incorporates C hange P oint detection into an A gent B ased M odel taking advantage of genetic algorithms for calibration and an efficient infection centric procedure for computational efficiency. The CP-ABM is applied to the Northern Ireland population where it successfully captures patterns in COVID-19 infection dynamics over both waves of the pandemic and quantifies the significant effects of non-pharmaceutical interventions (NPI) on a national level for lockdowns and mask wearing. To our knowledge, there is no other approach to date that has captured NPI effectiveness and infection spreading dynamics for both waves of the COVID-19 pandemic for an entire country population.

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