DOI: 10.1049/qtc2.12068 ISSN:

Hybrid‐quantum approach for the optimal lockdown to stop the SARS‐CoV‐2 community spread subject to maximising nation economy globally

Kunal Das, Sahil Zaman, Alex Khan, Arindam Sadhu, Subhasree Bhattacharjee, Faisal Shah Khan, Bikramjit Sarkar
  • Theoretical Computer Science
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computer Networks and Communications
  • Computational Theory and Mathematics


SARS‐CoV‐2 epidemic (severe acute respiratory corona virus 2 syndromes) has caused major impacts on a global scale. Several countries, including India, Europe, U.S.A., introduced a full state/nation lockdown to minimise the disease transmission through human interaction after the virus entered the population and to minimise the loss of human life. Millions of people have gone unemployed due to lockdown implementation, resulting in business and industry closure and leading to a national economic slowdown. Therefore, preventing the spread of the COVID‐19 virus in the world while also preserving the global economy is an essential problem requiring an effective and immediate solution. Using the compartmental epidemiology S, E, I, R or D (Susceptible, Exposed, Infectious, Recovery or Death) model extended to multiple population regions, the authors predict the evolution of the SARS‐CoV‐2 disease and construct an optimally scheduled lockdown calendar to execute lockdown over phases, using the well‐known Knapsack problem. A comparative analysis of both classical and quantum models shows that our model decreases SARS‐CoV‐2 active cases while retaining the average global economic factor, Gross Domestic Product, in contrast to the scenario with no lockdown.

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