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| Title | Multi-city modeling of epidemics using spatial networks: Application to 2019-nCov (COVID-19) coronavirus in India |
| Author/s |
Bhalchandra S. Pujari
Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411 007 India Snehal M. Shekatkar Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411 007 India |
| Abstract | The ongoing pandemic of 2019-nCov (COVID-19) coronavirus has made reliable epidemi-ological modeling an urgent necessity. Unfortunately, most of the existing models are eithertoo fine-grained to be efficient or too coarse-grained to be reliable. Here we propose acomputationally efficient hybrid approach that uses SIR model for individual cities whichare in turn coupled via empirical transportation networks that facilitate migration amongthem. The treatment presented here differs from existing models in two crucial ways: first,self-consistent determination of coupling parameters so as to maintain the populations ofindividual cities, and second, the incorporation of distance dependent temporal delays inmigration. We apply our model to Indian aviation as well as railway networks taking intoaccount populations of more than 300 cities. Our results project that through the domestictransportation, the significant population is poised to be exposed within 90 days of the onsetof epidemic. Thus, serious supervision of domestic transport networks is warranted evenafter restricting international migration. |
| Keywords | epidemiology, SIR, Networks |
| Download | [1.3M pdf] |
| Citing This Document | Bhalchandra S. Pujari, Snehal M. Shekatkar , Multi-city modeling of epidemics using spatial networks: Application to 2019-nCov (COVID-19) coronavirus in India. Technical Report CMS-TR-20200316 of the Centre for Modeling and Simulation, Savitribai Phule Pune University, Pune 411007, India (2020); available at http://864230.efsst.group/reports/. |
| Notes, Published Reference, Etc. | |
| Contact | [email protected] |
| Supplementary Material |