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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21258907

RESUMO

Owing to the SARS-CoV-2 epidemic (severe acute respiratory coronavirus 2 syndromes), the global situation has changed drastically. Several countries, including India, Europe, U.S.A., introduced a full state/nation lockdown to minimize the disease transmission through human interaction after the virus entered the population and to minimize 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 we 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, GDP, in contrast to the scenario with no lockdown.

3.
Phys Rev D Part Fields ; 53(10): 5856-5865, 1996 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-10019873
4.
Phys Rev D Part Fields ; 51(12): 6901-6908, 1995 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-10018452
6.
Phys Rev D Part Fields ; 38(10): 3105-3111, 1988 Nov 15.
Artigo em Inglês | MEDLINE | ID: mdl-9959055
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8.
Phys Rev Lett ; 56(25): 2664-2667, 1986 Jun 23.
Artigo em Inglês | MEDLINE | ID: mdl-10033059
9.
Phys Rev D Part Fields ; 31(10): 2704-2707, 1985 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-9955583
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