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- W3046111851 endingPage "110154" @default.
- W3046111851 startingPage "110154" @default.
- W3046111851 abstract "Owing to the pandemic scenario of COVID-19 disease cases all over the world, the outbreak prediction has become extremely complex for the emerging scientific research. Several epidemiological mathematical models of spread are increasing daily to forecast the predictions appropriately. In this study, the classical susceptible-infected-recovered (SIR) modeling approach was employed to study the different parameters of this model for India. This approach was analyzed by considering different governmental lockdown measures in India. Some assumptions were considered to fit the model in the Python simulation for each lockdown scenario. The predicted parameters of the SIR model exhibited some improvement in each case of lockdown in India. In addition, the outcome results indicated that extreme interventions should be performed to tackle this type of pandemic situation in the near future." @default.
- W3046111851 created "2020-08-03" @default.
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- W3046111851 date "2020-11-01" @default.
- W3046111851 modified "2023-10-01" @default.
- W3046111851 title "Estimating the parameters of susceptible-infected-recovered model of COVID-19 cases in India during lockdown periods" @default.
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- W3046111851 doi "https://doi.org/10.1016/j.chaos.2020.110154" @default.
- W3046111851 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7388782" @default.
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