RISK ANALYSIS AND PREDICTION FOR COVID19 DEMOGRAPHICS IN LOW RESOURCE SETTINGS USING A PYTHON DESKTOP APP AND EXCEL MODELS.

Ali Kyagulanyi; Joel Tibabwetiza Muhanguzi; Oscar Dembe; Sheba Kirabo

In the excel model we have remodeled the SIR differential equation in an excel work sheet and compared. We modelled the same SIR ordinary differential equation input parameters for covid19 disease, this second model can be used as control and it will verify the results of the python algorithm. Both models use the same values of beta, gamma and population of a given area. We have also included the possible number of deaths in this model values of susceptible, infectious and recovered populations can be calculated using the mathematical equations below which are obtained after integration of the ordinary differential equations. They calculate the number of people in each condition today (n), based on the number yesterday (n-1) and the rates of change, ß and γ. The subscript n means the number in one-time interval, and n-1 means the number in the previous interval.