Contact-Based Model for Epidemic Spreading on Temporal Networks

Abstract

We present a contact-based model to study the spreading of epidemics by means of extending the dynamic message passing approach to temporal networks. The shift in perspective from nodeto edge-centric quantities enables accurate modelling of Markovian susceptible-infected-recovered outbreaks on time-varying trees, i.e., temporal networks with a loop-free underlying topology. On arbitrary graphs, the proposed contact-based model incorporates potential structural and temporal heterogeneities of the underlying contact network and improves analytic estimations with respect to the individual-based (node-centric) approach at a low computational and conceptual cost. Within this new framework, we derive an analytical expression for the epidemic threshold on temporal networks and demonstrate the feasibility of this method on empirical data.

Impact of presymptomatic transmission on epidemic spreading in contact networks: A dynamic message-passing analysis

“…However, the drastic simplification based on the independence assumption of probabilities may lead to large approximation errors [26]. One source of errors comes from the mutual infection effect due to this decorrelation assumption [17,29]. For instance, suppose that a node i, having probability P i E (t) in the exposed state, infects its susceptible neighboring node k at time t, then node k can also reinfect node i at time t + 1 with some probability, which is an artifact of neglecting the correlation between nodes i and k. Such effects need to be correctly accounted for to improve accuracy.…”

“…Inset of (b) shows that the critical point βc obtained in MC simulations approaches the one obtained by the DMP approach as the network size increases. and may impact on the estimation of β c through simulations [29]. This is not captured by the theories which only consider averaged quantities.…”

GoCoronaGo: Privacy Respecting Contact Tracing for COVID-19 Management

“…Further, even if the Bluetooth scans were missed by the infected user, successful scans by other proximate devices can be used to alert the relevant contacts, increasing the reliability of detection. In addition, centralized digital contact tracing has the potential to estimate the state of the population using network-based SEIR models, which can be used to assign risk scores and prioritize testing 28,37,55 .…”

Risk Assessment Model: Roadmap to Develop Kolkata into a Smart City

“…Several methods are used to study the transmission of diseases. Perhaps the most crucial decision in building a model is how the population's interactions are portrayed (73). The efficacy of agent-based modelling lies in its dynamic functioning based on customization capacities in heterogeneous populations.…”