Selected article for: "International license and long time"
Author: Debashree Ray; Maxwell Salvatore; Rupam Bhattacharyya; Lili Wang; Shariq Mohammed; Soumik Purkayastha; Aritra Halder; Alexander Rix; Daniel Barker; Michael Kleinsasser; Yiwang Zhou; Peter Song; Debraj Bose; Mousumi Banerjee; Veerabhadran Baladandayuthapani; Parikshit Ghosh; Bhramar Mukherjee
Title: Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms
  • Document date: 2020_4_18
    • ID: 3a3c8ee1_66
    Snippet: Our statistical modeling and forecasts are not without limitations. We have very few data points and a long time-window to extrapolate for the long-term forecasts. The uncertainty in our predictions is large due to many unknowns arising from model assumptions, population . CC-BY-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity......
    Document: Our statistical modeling and forecasts are not without limitations. We have very few data points and a long time-window to extrapolate for the long-term forecasts. The uncertainty in our predictions is large due to many unknowns arising from model assumptions, population . CC-BY-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

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