{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T16:37:31Z","timestamp":1783787851693,"version":"3.55.0"},"reference-count":25,"publisher":"World Scientific Pub Co Pte Ltd","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Bifurcation Chaos"],"published-print":{"date-parts":[[2009,2]]},"abstract":"<jats:p>We present a time-delayed SIS model on complex networks to study epidemic spreading. We found that the existence of delay will affect, and oftentimes enhance, both outbreak and prevalence of infectious diseases in the networks. For small-world networks, we found that the epidemic threshold and the delay time have a power-law relation. For scale-free networks, we found that for a given transmission rate, the epidemic prevalence has an exponential form, which can be analytically obtained, and it decays as the delay time increases. We confirm all results by sufficient numerical simulations.<\/jats:p>","DOI":"10.1142\/s021812740902324x","type":"journal-article","created":{"date-parts":[[2009,5,8]],"date-time":"2009-05-08T11:52:17Z","timestamp":1241783537000},"page":"623-628","source":"Crossref","is-referenced-by-count":20,"title":["THE SIS MODEL WITH TIME DELAY ON COMPLEX NETWORKS"],"prefix":"10.1142","volume":"19","author":[{"given":"XIN-JIAN","family":"XU","sequence":"first","affiliation":[{"name":"Department of Mathematics, College of Science, Shanghai University, Baoshan Area, Shanghai 200444, P. R. China"},{"name":"Departamento de F\u00edsica da Universidade de Aveiro, 3810-193 Aveiro, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"GUANRONG","family":"CHEN","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, P. R. 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