most citedThe impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: a mean-field model perspective

7 citations · 7 across the 1 of their papers we have counts for

collaborators

5 papers

physics.soc-ph2020

Beyond COVID-19: Network science and sustainable exit strategies

James Bell, Ginestra Bianconi, David Butler +11

On May and , a two day workshop was held virtually, facilitated by the Beyond Center at ASU and Moogsoft Inc. The aim was to bring together leading scientists wi…

eess.SY2020

Covid-19 and Flattening the Curve: a Feedback Control Perspective

Francesco Di Lauro, István Z. Kiss, Daniela Rus +1

Many of the control policies that were put into place during the Covid-19 pandemic had a common goal: to flatten the curve of the number of infected people so that its peak remains…

q-bio.PE2020★ 7 cited

The impact of network properties and mixing on control measures and disease-induced herd immunity in epidemic models: a mean-field model perspective

Francesco Di Lauro, Luc Berthouze, Matthew D. Dorey +2

The contact structure of a population plays an important role in transmission of infection. Many ``structured models'' capture aspects of the contact structure through an underlyin…

q-bio.PE2020

PDE-limits of stochastic SIS epidemics on networks

Francesco Di Lauro, Jean-Charles Croix, Luc Berthouze +1

Stochastic epidemic models on networks are inherently high-dimensional and the resulting exact models are intractable numerically even for modest network sizes. Mean-field models p…

q-bio.PE2019

Network Inference from Population-Level Observation of Epidemics

F. Di Lauro, J. -C. Croix, M. Dashti +2

Using the continuous-time susceptible-infected-susceptible (SIS) model on networks, we investigate the problem of inferring the class of the underlying network when epidemic data i…