Selected article for: "epidemiological peak and public transport"
Author: Ali Kyagulanyi; Joel Tibabwetiza Muhanguzi; Oscar Dembe; Sheba Kirabo
Title: RISK ANALYSIS AND PREDICTION FOR COVID19 DEMOGRAPHICS IN LOW RESOURCE SETTINGS USING A PYTHON DESKTOP APP AND EXCEL MODELS.
  • Document date: 2020_4_17
    • ID: 7okyyb2m_80
    Snippet: At B = 0.28 This is assumed to be the case for uganda by this date were public transport is banned , the rate of infection is relatively lower than previous assumed rate , until the fourth day significant number of cases are not recorded and the cases sharply rise until the 70 th day were the epidemiological peak can be obtained for the curve to flatten , then cases begin to fall sharply as more people recover or die from the pandemic......
    Document: At B = 0.28 This is assumed to be the case for uganda by this date were public transport is banned , the rate of infection is relatively lower than previous assumed rate , until the fourth day significant number of cases are not recorded and the cases sharply rise until the 70 th day were the epidemiological peak can be obtained for the curve to flatten , then cases begin to fall sharply as more people recover or die from the pandemic.

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