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Found 10 papers, 0 papers with code
Modeling and Predicting Epidemic Spread: A Gaussian Process Regression Approach
Gaussian Process Regression excels in using small datasets and providing uncertainty bounds, and both of these properties are critical in modeling and predicting epidemic spreading processes with limited data.
Adaptive Identification of SIS Models
Effective containment of spreading processes such as epidemics requires accurate knowledge of several key parameters that govern their dynamics.
Distributed Reproduction Numbers of Networked Epidemics
These conditions are then used to derive new conditions for the existence, uniqueness, and stability of equilibrium states.
Optimal Mitigation of SIR Epidemics Under Model Uncertainty
Distinct from existing works on leveraging control strategies in epidemic spreading, we propose a testing strategy by overestimating the seriousness of the epidemic and study the feasibility of the system under the impact of model parameter uncertainty.
Modeling and Analysis of a Coupled SIS Bi-Virus Model
We establish a sufficient condition and multiple necessary conditions for local exponential convergence to the boundary equilibrium (i. e., one virus persists, the other one dies out) of each virus.
Peak Infection Time for a Networked SIR Epidemic with Opinion Dynamics
We propose an SIR epidemic model coupled with opinion dynamics to study an epidemic and opinions spreading in a network of communities.
The Impact of Vaccine Hesitancy on Epidemic Spreading
We leverage the concept of carrying capacity to account for vaccine hesitancy by defining a vaccine confidence level $\kappa$, which is the maximum number of people that will become vaccinated during the course of a disease.
Parameter Estimation in Epidemic Spread Networks Using Limited Measurements
We study the problem of estimating the parameters (i. e., infection rate and recovery rate) governing the spread of epidemics in networks.
The Effect of Population Flow on Epidemic Spread: Analysis and Control
We show that the set of healthy states is asymptotically stable, and that the value of the equilibria becomes equal across all sub-populations as a result of the network flow model.
On a Network SIS Epidemic Model with Cooperative and Antagonistic Opinion Dynamics
We propose a mathematical model to study coupled epidemic and opinion dynamics in a network of communities.
