Impact of Network Heterogeneity on Epidemic Mitigation Strategies

We formulate an optimal control problem to find best vaccination and treatment policies to minimize the impact of an epidemic on the population. Epidemic spread on heterogeneous human contact networks is modeled using the degree based compartmental model for susceptible-infected-recovered epidemic....

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Bibliographic Details
Published in2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT) pp. 428 - 433
Main Authors Devendra, Jagtap Kalyani, Kandhway, Kundan
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.04.2022
Subjects
Epidemic
Epidemics
heterogeneous networks
Human factors
Optimal control
Power measurement
Social factors
social networks
Sociology
Vaccines
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Summary:We formulate an optimal control problem to find best vaccination and treatment policies to minimize the impact of an epidemic on the population. Epidemic spread on heterogeneous human contact networks is modeled using the degree based compartmental model for susceptible-infected-recovered epidemic. Our formulation allows us to study the impact of varying network heterogeneity on the mitigation strategies. Network heterogeneity is varied by using different degree distributions for the network, such as, power law, power law with exponential cut-off, and Poisson. Network heterogeneity is a proxy for social distancing measures applied on the population-as restrictions tightens, high degree hubs disappear, thus, the nature of degree distribution changes from power law to Poisson. We find that high degree nodes assume less importance in mitigating epidemics as the network heterogeneity decreases. Also, epidemics are easier to control with decrease in network heterogeneity.
DOI:10.1109/CSNT54456.2022.9787646