Epidemic surveillance on networks: who to test to monitor an epidemic?

Introduction

Network epidemic models are used to predict the spread of a disease and to evaluate the effect of interventions. These models assume that both the epidemic parameters and the infection state of all individuals are known at a certain time. In practice, the infection state is only known through tests, which are imprecise, sparse and incomplete. Since testing capacity is limited, the choice of which individuals to test determines how well the epidemic can be observed, predicted and ultimately contained.

Project

The aim of this project is to find which nodes/individuals should be tested to best observe an epidemic on a network. You will combine the theory of observability with network epidemic models and compare testing strategies (random, degree- or centrality-based, adaptive) on synthetic and real contact networks.

Skills: modelling, inference, simulation

Contact

Federico Ravazzolo, This email address is being protected from spambots. You need JavaScript enabled to view it.

References

N. A. Christakis & J. H. Fowler, "Social network sensors for early detection of contagious outbreaks", PLoS ONE 5(9), e12948 (2010).

 A. Baker et al., "Epidemic mitigation by statistical inference from contact tracing data", PNAS 118(32), e2106548118 (2021).