Optimal test-kit based intervention strategy of epidemic spreading in heterogeneous complex networks
arXiv:2010.07649 · doi:10.1063/5.0053262
Abstract
We propose a deterministic compartmental model of infectious disease which considers the test-kits as an important ingredient for the suppression and mitigation of epidemics. A rigorous simulation (with analytical argument) is provided to reveal the effective reduction of final outbreak size and peak of infection as a function of basic reproduction number in a single patch. Further, to study the impact of long and short-distance human migration among the patches, we have considered heterogeneous networks where the linear diffusive connectivity is determined by the network link structure. We numerically confirm that implementation of test-kits in the fraction of nodes (patches) having larger degrees or betweenness centralities can reduce the peak of infection (as well as final outbreak size) significantly. A next-generation matrix based analytical treatment is provided to find out the critical transmission probability in the entire network for the onset of epidemics. Finally, the optimal intervention strategy is validated in two real networks: global airport networks and transportation networks of Kolkata, India.
arXiv comment22 pages, 9 Figures
References in corpus (19)
- The structure and function of complex networks
- Error and attack tolerance of complex networks
- Epidemic processes in complex networks
- The spread of epidemic disease on networks
- A SIDARTHE Model of COVID-19 Epidemic in Italy
- Forecast and Control of Epidemics in a Globalized World
- Reaction-diffusion processes and metapopulation models in heterogeneous networks
- Statistical physics of vaccination
- Predictability and epidemic pathways in global outbreaks of infectious diseases: the SARS case study
- Natural human mobility patterns and spatial spread of infectious diseases
- Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic
- Immunization of networks with community structure
- Impact of intervention on the spread of COVID-19 in India: A model based study
- Beyond ranking nodes: Predicting epidemic outbreak sizes by network centralities
- Dynamical epidemic suppression using stochastic prediction and control
- Random walks in time-varying networks with memory
- Intervention Threshold for Epidemic Control in Susceptible-Infected-Recovered Metapopulation Models
- Discontinuous epidemic transition due to limited testing
- Infection spreading and recovery in a square lattice
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