0000000000441117

AUTHOR

Claudio Castellano

0000-0002-3773-3801

showing 2 related works from this author

Epidemic spreading and aging in temporal networks with memory

2018

Time-varying network topologies can deeply influence dynamical processes mediated by them. Memory effects in the pattern of interactions among individuals are also known to affect how diffusive and spreading phenomena take place. In this paper we analyze the combined effect of these two ingredients on epidemic dynamics on networks. We study the susceptible-infected-susceptible (SIS) and the susceptible-infected-removed (SIR) models on the recently introduced activity-driven networks with memory. By means of an activity-based mean-field approach we derive, in the long time limit, analytical predictions for the epidemic threshold as a function of the parameters describing the distribution of …

FOS: Computer and information sciencesPhysics - Physics and SocietyComputer scienceAnalytical predictionsEpidemic dynamicsFOS: Physical sciencesPhysics and Society (physics.soc-ph)Network topology01 natural sciences010305 fluids & plasmasNetworks and Complex Systems0103 physical sciencesQuantitative Biology::Populations and EvolutionStatistical physicsLimit (mathematics)010306 general physicsQuantitative Biology - Populations and EvolutionEpidemic controlSocial and Information Networks (cs.SI)Populations and Evolution (q-bio.PE)Computer Science - Social and Information NetworksFunction (mathematics)Computer Science::Social and Information NetworksArticlesDynamic modelsEpidemic thresholdEpidemic spreadingFOS: Biological sciencesMean field approachPhysical Review. E
researchProduct

Stochastic sampling effects favor manual over digital contact tracing.

2020

Isolation of symptomatic individuals, tracing and testing of their nonsymptomatic contacts are fundamental strategies for mitigating the current COVID-19 pandemic. The breaking of contagion chains relies on two complementary strategies: manual reconstruction of contacts based on interviews and a digital (app-based) privacy-preserving contact tracing. We compare their effectiveness using model parameters tailored to describe SARS-CoV-2 diffusion within the activity-driven model, a general empirically validated framework for network dynamics. We show that, even for equal probability of tracing a contact, manual tracing robustly performs better than the digital protocol, also taking into accou…

0301 basic medicinePhysics - Physics and SocietyComputer scienceEpidemiologyScienceComplex networksFOS: Physical sciencesGeneral Physics and AstronomyPhysics and Society (physics.soc-ph)Tracingcomputer.software_genreGeneral Biochemistry Genetics and Molecular BiologyArticleSpecimen Handling03 medical and health sciences0302 clinical medicineHumans030212 general & internal medicineQuantitative Biology - Populations and EvolutionPandemicsCondensed Matter - Statistical Mechanicsstochastic modelProtocol (science)Stochastic ProcessesMultidisciplinaryStatistical Mechanics (cond-mat.stat-mech)Stochastic processDiagnostic Tests RoutineSARS-CoV-2QPopulations and Evolution (q-bio.PE)Sampling (statistics)COVID-19General ChemistryComplex networkModels TheoreticalNetwork dynamics030104 developmental biologyFOS: Biological sciencesScalabilityQuarantineData miningContact TracingcomputerContact tracingAlgorithmsNature communications
researchProduct