{"id":{"repo_id":"duke","oai_identifier":"oai:dukespace.lib.duke.edu:10161/23747"},"canonical_url":"https://search.dev.ndltd.org/etd/duke/oai:dukespace.lib.duke.edu:10161/23747","repository":{"repo_id":"duke","name":"Duke University","base_url":"https://dukespace.lib.duke.edu/server/oai/request"},"display":{"title":"Epidemics on Evolving Graphs","abstract":"<p>The evoSIR model is a modification of the usual SIR process on a graph $G$ in which $S$-$I$ connections are broken at rate $\\rho$ and the $S$ connects to a randomly chosen vertex. The evoSI model is the same as evoSI but recovery is impossible. In \\cite{DOMath} the critical value for evoSIR was computed and simulations showed that when $G$ is an Erd\\H os-R\\'enyi graph with mean degree 5 the system has a discontinuous phase transition, i.e., as the infection rate $\\lambda$ decreases to $\\lambda_c$, the final fraction of once infected individuals does not converge to 0. In this paper we study evoSI dynamics on graphs generated by the configuration model. We show that there is a quantity $\\Delta$ determined by the first three moments of the degree distribution, so that the transition is discontinuous if $\\Delta>0$ and continuous if $\\Delta<0$.</p>","abstract_html":"&lt;p&gt;The evoSIR model is a modification of the usual SIR process on a graph $G$ in which $S$-$I$ connections are broken at rate $\\rho$ and the $S$ connects to a randomly chosen vertex. The evoSI model is the same as evoSI but recovery is impossible. In \\cite{DOMath} the critical value for evoSIR was computed and simulations showed that when $G$ is an Erd\\H os-R\\&#x27;enyi graph with mean degree 5 the system has a discontinuous phase transition, i.e., as the infection rate $\\lambda$ decreases to <span class=\"etd-inline-math\">\\lambda<sub>c</sub></span>, the final fraction of once infected individuals does not converge to 0. In this paper we study evoSI dynamics on graphs generated by the configuration model. We show that there is a quantity $\\Delta$ determined by the first three moments of the degree distribution, so that the transition is discontinuous if $\\Delta&gt;0$ and continuous if $\\Delta&lt;0$.&lt;/p&gt;","abstract_has_math":true,"creators":["Yao, Dong"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Durrett, Richard"],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021","date_published":"2021","updated_at":"2026-07-24T02:07:01Z","subjects":["Mathematics","epidemics","evolving graphs"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10161/23747","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Durrett, Richard"]},{"key":"dc:creator","label":"Author","values":["Yao, Dong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-09-14T15:08:30Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-09-14T15:08:30Z"]},{"key":"dc:date.issued","label":"Date","values":["2021"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Mathematics","epidemics","evolving graphs"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10161/23747"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>The evoSIR model is a modification of the usual SIR process on a graph $G$ in which $S$-$I$ connections are broken at rate $\\rho$ and the $S$ connects to a randomly chosen vertex. The evoSI model is the same as evoSI but recovery is impossible. In \\cite{DOMath} the critical value for evoSIR was computed and simulations showed that when $G$ is an Erd\\H os-R\\'enyi graph with mean degree 5 the system has a discontinuous phase transition, i.e., as the infection rate $\\lambda$ decreases to $\\lambda_c$, the final fraction of once infected individuals does not converge to 0. In this paper we study evoSI dynamics on graphs generated by the configuration model. We show that there is a quantity $\\Delta$ determined by the first three moments of the degree distribution, so that the transition is discontinuous if $\\Delta>0$ and continuous if $\\Delta<0$.</p>"]},{"key":"dc:title","label":"Title","values":["Epidemics on Evolving Graphs"]}]}],"canonical_facts":{"dc:contributor.advisor":["Durrett, Richard"],"dc:creator":["Yao, Dong"],"dc:date.accessioned":["2021-09-14T15:08:30Z"],"dc:date.available":["2021-09-14T15:08:30Z"],"dc:date.issued":["2021"],"dc:description.abstract":["<p>The evoSIR model is a modification of the usual SIR process on a graph $G$ in which $S$-$I$ connections are broken at rate $\\rho$ and the $S$ connects to a randomly chosen vertex. The evoSI model is the same as evoSI but recovery is impossible. In \\cite{DOMath} the critical value for evoSIR was computed and simulations showed that when $G$ is an Erd\\H os-R\\'enyi graph with mean degree 5 the system has a discontinuous phase transition, i.e., as the infection rate $\\lambda$ decreases to $\\lambda_c$, the final fraction of once infected individuals does not converge to 0. In this paper we study evoSI dynamics on graphs generated by the configuration model. We show that there is a quantity $\\Delta$ determined by the first three moments of the degree distribution, so that the transition is discontinuous if $\\Delta>0$ and continuous if $\\Delta<0$.</p>"],"dc:identifier.uri":["https://hdl.handle.net/10161/23747"],"dc:subject":["Mathematics","epidemics","evolving graphs"],"dc:title":["Epidemics on Evolving Graphs"],"dc:type":["Dissertation"]},"updated_at":"2026-07-24T02:07:01Z"}