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International Journal of Data Science and Analytics

06-06-2022 | Regular Paper

Exo-SIR: an epidemiological model to analyze the impact of exogenous spread of infection

Authors: Nirmal Kumar Sivaraman, Manas Gaur, Shivansh Baijal, Sakthi Balan Muthiah, Amit Sheth

Published in: International Journal of Data Science and Analytics

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Abstract

Epidemics like Covid-19 and Ebola have impacted people’s lives significantly. The impact of mobility of people across the countries or states in the spread of epidemics has been significant. The spread of disease due to factors local to the population under consideration is termed the endogenous spread. The spread due to external factors like migration, mobility, etc., is called the exogenous spread. In this paper, we introduce the Exo-SIR model, an extension of the popular SIR model and a few variants of the model. The novelty in our model is that it captures both the exogenous and endogenous spread of the virus. First, we present an analytical study. Second, we simulate the Exo-SIR model with and without assuming contact network for the population. Third, we implement the Exo-SIR model on real datasets regarding Covid-19 and Ebola. We found that endogenous infection is influenced by exogenous infection. Furthermore, we found that the Exo-SIR model predicts the peak time better than the SIR model. Hence, the Exo-SIR model would be helpful for governments to plan policy interventions at the time of a pandemic.

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Footnotes
10
The code and all the data used in our experiments will be made openly available upon the acceptance of this paper
 
14
The code and all the data used in our experiments will be made openly available upon the acceptance of this paper
 
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Metadata
Title
Exo-SIR: an epidemiological model to analyze the impact of exogenous spread of infection
Authors
Nirmal Kumar Sivaraman
Manas Gaur
Shivansh Baijal
Sakthi Balan Muthiah
Amit Sheth
Publication date
06-06-2022
Publisher
Springer International Publishing
Published in
International Journal of Data Science and Analytics
Print ISSN: 2364-415X
Electronic ISSN: 2364-4168
DOI
https://doi.org/10.1007/s41060-022-00334-z

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