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

is the (which was not peer-reviewed) The copyright holder for this preprint . https: //doi.org/10.1101 //doi.org/10. /2020 used the probailities of an infection choosing an individual given that he is from that age bracket.That probability multiplied by the number of total infectious individuals will generate the infections per particular age bracket.The average mortality rates we earlier on calculated for the four age brackets , will be multiplied multipled with the number of infectious individuals in that age bracked we are able to obtain the number of deaths for a given day.This applies the bayes theorem and conditional probabilities to generate the number of the death. Now we were able to determine, the number of deaths based on the consistence of the mortality per a particular age bracket. From the mortality rate ratios by the number of people infected in a population the first death is expected to occur on the, after the first death it means that the SIR model would have . CC-BY-NC-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.