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
- 15Citations
- 33Captures
- 1Mentions
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Metrics Details
- Citations15
- Citation Indexes14
- 14
- CrossRef4
- Policy Citations1
- Policy Citation1
- Captures33
- Readers33
- 33
- Mentions1
- News Mentions1
- News1
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.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0031320322002710; http://dx.doi.org/10.1016/j.patcog.2022.108790; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85131084763&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/35601479; https://linkinghub.elsevier.com/retrieve/pii/S0031320322002710; https://dx.doi.org/10.1016/j.patcog.2022.108790
Elsevier BV
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