{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:08:49Z","timestamp":1753880929802,"version":"3.41.2"},"reference-count":26,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Info. Know. Mgmt."],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:p> Mathematical models involving complex formulations are used for solving estimation problems across various disciplines. Epidemiological models like susceptible\u2013infected\u2013removed (SIR), and its variations like susceptible\u2013exposed\u2013infected\u2013removed (SEIR) and others are traditionally used for estimating the progression of viral outbreaks. But, real-life situations adapt and respond to ever-changing surroundings and social norms in precise or random or in complex manners. The mathematical formulation-based compartmental models suffer from drawbacks that lead to inaccuracy in predictions. To address this gap, a deep learning (DL)-based hybrid architecture namely residual leaky network (LeakyNet) has been proposed for the first time to the best of authors\u2019 knowledge. This DL-based hybrid architecture is capable of analysing various aspects of the pandemic by training on short-term data to generate probable future trends. Using this hybrid architecture as a building block, a DL-based epidemiological model namely vulnerable\u2013contaminated\u2013immuned (VCI) model has been formulated to analyse short-term historical data of COVID-19. The DL empowered compartmental model has been implemented on an ongoing real-life scenario and the results reveal that the proposed model performs reasonably well in comparison to the contemporary models. The predicted data have been observed to be in good agreement with the actual pandemic data. The prediction models considered in this study have been evaluated using mean absolute percentage error (MAPE). <\/jats:p>","DOI":"10.1142\/s021964922350020x","type":"journal-article","created":{"date-parts":[[2023,7,12]],"date-time":"2023-07-12T05:13:46Z","timestamp":1689138826000},"source":"Crossref","is-referenced-by-count":0,"title":["Recursive Stacked LeakyNet-Based Compartmental Model for Analysis of COVID-19 Transmission Dynamics"],"prefix":"10.1142","volume":"22","author":[{"given":"Soumya Jyoti","family":"Raychaudhuri","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, M. S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2358-3443","authenticated-orcid":false,"given":"C. Narendra","family":"Babu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, M. S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India"}]}],"member":"219","published-online":{"date-parts":[[2023,7,12]]},"reference":[{"issue":"3","key":"S021964922350020XBIB001","first-page":"201","volume":"24","author":"Abbey H","year":"1952","journal-title":"Human Biology"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB004","DOI":"10.1007\/s12046-016-0508-5"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB005","DOI":"10.1002\/rmv.443"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB006","DOI":"10.1016\/j.mjafi.2020.03.022"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB009","DOI":"10.1038\/s41591-020-0883-7"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB011","DOI":"10.1038\/nrmicro1845"},{"volume-title":"Epidemiology Old and New","year":"1928","author":"Hamer W","key":"S021964922350020XBIB012"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB013","DOI":"10.1109\/CVPR.2016.90"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB015","DOI":"10.2307\/j.ctvcm4gk0"},{"issue":"1","key":"S021964922350020XBIB016","first-page":"33","volume":"53","author":"Kermack W","year":"1991","journal-title":"Bulletin of Mathematical Biology"},{"issue":"1","key":"S021964922350020XBIB017","first-page":"57","volume":"53","author":"Kermack W","year":"1991","journal-title":"Bulletin of Mathematical Biology"},{"issue":"1","key":"S021964922350020XBIB018","first-page":"89","volume":"53","author":"Kermack W","year":"1991","journal-title":"Bulletin of Mathematical Biology"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB019","DOI":"10.1109\/VTC2020-Spring48590.2020.9128719"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB020","DOI":"10.1016\/j.econlet.2011.08.010"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB022","DOI":"10.1016\/S2468-2667(20)30073-6"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB023","DOI":"10.1016\/j.idm.2020.03.001"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB024","DOI":"10.1016\/j.idm.2020.02.002"},{"volume-title":"The Prevention of Malaria","year":"1910","author":"Ross R","key":"S021964922350020XBIB025"},{"key":"S021964922350020XBIB026","first-page":"258","volume-title":"Epidemiology in Veterinary Practice","author":"Schwabe CW","year":"1977"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB027","DOI":"10.1016\/j.chaos.2020.110212"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB033","DOI":"10.3390\/bioengineering10010065"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB035","DOI":"10.1016\/S0140-6736(20)30526-2"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB040","DOI":"10.1145\/3209978.3210077"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB041","DOI":"10.3390\/electronics12020253"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB042","DOI":"10.21037\/jtd.2020.02.64"},{"doi-asserted-by":"publisher","key":"S021964922350020XBIB043","DOI":"10.1007\/s40484-020-0199-0"}],"container-title":["Journal of Information &amp; Knowledge Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S021964922350020X","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T00:41:34Z","timestamp":1702946494000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/10.1142\/S021964922350020X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,12]]},"references-count":26,"journal-issue":{"issue":"05","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["10.1142\/S021964922350020X"],"URL":"https:\/\/doi.org\/10.1142\/s021964922350020x","relation":{},"ISSN":["0219-6492","1793-6926"],"issn-type":[{"type":"print","value":"0219-6492"},{"type":"electronic","value":"1793-6926"}],"subject":[],"published":{"date-parts":[[2023,7,12]]},"article-number":"2350020"}}