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

By no means we cannot claim the accuracy of the results, due to varying dynamics of the disease the infection rates can change or vary at any time based on the actions taken by the government and populations. Both models sampled above produced relatively similar results with a few variations which may be based on numerical method estimations in excel model, the application above can be used to estimate rates for any given area with a few inputs and following the excel model procedure you can generate same results. The difference between the two models is ease of use, the application can easily be used by anyone, even with less computational skills unlike the excel model which may require prior expert knowledge with Microsoft excel , results predicted in both models may be accurate will smaller populations like for one city but can be in accurate when a big sample space is taken due to variance in dynamics. We hope these models can be employed in different areas and estimate how best to combat the deadly disease and allocate resources based on scientific and statistical facts and we further advise the use of both models at the same time, to get comparative results.