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Detecting infected asymptomatic cases in a stochastic model for spread of Covid-19: the case of Argentina.
Barreiro, N L; Govezensky, T; Bolcatto, P G; Barrio, R A.
  • Barreiro NL; Instituto de Investigaciones Científicas y Técnicas para la Defensa (CITEDEF), Buenos Aires, 1603, Argentina. nadus.barreiro@gmail.com.
  • Govezensky T; Instituto de Invesitgaciones Biomédicas, Universidad Nacional Autónoma de México, 04510, Mexico, Mexico.
  • Bolcatto PG; Instituto de Investigaciones Científicas y Técnicas para la Defensa (CITEDEF), Buenos Aires, 1603, Argentina.
  • Barrio RA; Instituto de Matemática Aplicada del Litoral (IMAL, CONICET/UNL), FHUC, Santa Fe, 3000, Argentina.
Sci Rep ; 11(1): 10024, 2021 05 11.
Article in English | MEDLINE | ID: covidwho-1225517
ABSTRACT
We have studied the dynamic evolution of the Covid-19 pandemic in Argentina. The marked heterogeneity in population density and the very extensive geography of the country becomes a challenge itself. Standard compartment models fail when they are implemented in the Argentina case. We extended a previous successful model to describe the geographical spread of the AH1N1 influenza epidemic of 2009 in two essential ways we added a stochastic local mobility mechanism, and we introduced a new compartment in order to take into account the isolation of infected asymptomatic detected people. Two fundamental parameters drive the dynamics the time elapsed between contagious and isolation of infected individuals ([Formula see text]) and the ratio of people isolated over the total infected ones (p). The evolution is more sensitive to the [Formula see text]parameter. The model not only reproduces the real data but also predicts the second wave before the former vanishes. This effect is intrinsic of extensive countries with heterogeneous population density and interconnection.The model presented has proven to be a reliable predictor of the effects of public policies as, for instance, the unavoidable vaccination campaigns starting at present in the world an particularly in Argentina.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Asymptomatic Diseases / COVID-19 / Models, Theoretical Type of study: Diagnostic study / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: South America / Argentina Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-89517-5

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Asymptomatic Diseases / COVID-19 / Models, Theoretical Type of study: Diagnostic study / Observational study / Prognostic study Topics: Vaccines Limits: Humans Country/Region as subject: South America / Argentina Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-89517-5