What is it about?
The prediction of diseases caused by viral infections is a complex medical task where many real data that consists of different variables must be employed. As known, COVID-19 is the most dangerous disease worldwide; nowhere, an effective drug has been found yet. To limit its spread, it is essential to find a rational method that shows the spread of this virus by relying on many infected people’s data. A model consisting of three artificial neural networks’ (ANN) functions was developed to predict COVID-19 separation in Iraq based on real infection data supplied by the public health department at the Iraqi Ministry of Health.
Photo by CDC on Unsplash
Why is it important?
The maps created in this study enable decision-makers in the health and government sectors to anticipate events to develop proactive plans to combat this disease or request the international community’s assistance if the health situation gets out of control. This study’s procedure can offer more accurate results in future studies when several parameters or information such as age, gender, ethnicity, occupation, pre-existing health conditions, and the local weather tacking into account.
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This page is a summary of: COVID-19 prediction analysis using artificial intelligence procedures and GIS spatial analyst: a case study for Iraq, Applied Geomatics, March 2021, Springer Science + Business Media, DOI: 10.1007/s12518-021-00365-4.
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