Impact of Network Heterogeneity on Epidemic Mitigation Strategies
11th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2022
; : 428-433, 2022.
Article
in English
| Scopus | ID: covidwho-1919103
ABSTRACT
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. © 2022 IEEE.
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
11th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2022
Year:
2022
Document Type:
Article
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