COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq

The prediction of diseases caused by viral infections is a complex medical task where many real data that consists different variables must be employed. As known, COVID-19 the most dangerous disease worldwide; nowhere, an effective drug has been found yet. To limit its spread, it essential to find rational method shows spread this virus relying on infected people’s data. A model consisting three artificial neural networks’ (ANN) functions was developed predict separation in Iraq based infection supplied public health department at Iraqi Ministry Health. performance efficiency evaluated, reached 81.6% when employed four statistical error criteria as mean absolute percentage (MAPE), root square (RMSE), coefficient determination (R2), and Nash-Sutcliffe (NC). severity virus’s across assessed short term (in next 6 months), results show will intensify 17.1%, average death cases increase 8.3%. These clarified creating spatial distribution maps for are simulated employing Geographic Information System (GIS) environment used useful database developing plans combating viruses Iraq.