Abstract
In this paper we model the dynamics of a spreading pandemic over a country using a new dynamical and decentralised differential model with the main objective of studying the effect of different policies of social isolation (social distancing) over the population to control the spread of the pandemic. A probabilistic infection process with time lags is introduced in the dynamics with the main contribution being the proposed model to explicitly look at levels of interaction between towns and regions within the considered country. We believe the strategies and findings here will help practitioners, planners and Governments to put in place better strategies to control the spread of pandemics, thus saving lives and minimizing the impact of pandemia on socio-economic development and the populations livelihood.
Subject
Management Science and Operations Research,Computer Science Applications,Theoretical Computer Science
Cited by
3 articles.
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