@article{Erkan Yilmaz_Ekrem Aydiner_Özgur Ökcu_2023, title={COVID-19 Mortality Prediction: A Case Study for Istanbul}, volume={92}, url={https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/8632}, abstractNote={<p>It is well known that it is very difficult to make predictions for the real number of deaths due to any pandemic by using SIR and similar models since the predicted solutions systematically can deviate from real data. On the other hand, death data in the long and effective pandemic period cannot reflect the real case. In order to get more correct solutions and obtain realistic predictions, the parameters of these equations must be determined more precisely. In this study, by using real data depending on all deaths in Istanbul as a case study for 2020-2022 we determined the values of the parameters of the SEIR model and obtained the solution of SEIR equations. Firstly, we show that our numerical solution has a good fit with real data of the deaths due to COVID-19 for 2020 first and second peaks and 2021 first peak. Based on this confirmation, we predicted possible the number of deaths for the 2021 second peak. Furthermore, we see that our results show the number of deaths due to COVID-19 in Istanbul. Our method strongly provides that the model can lead to correct results if the parameters of SEIR models are determined by using excess mortality approximation. Now, we extend the study to predict the number of deaths due to the pandemic effects in 2022-2023. We show that our prediction is still compatible with the number of deaths for each wave. Finally, we predict the number of deaths for the future wave of 2022-2023 and we calculate the number of infected people in Istanbul for herd immunity.</p>}, number={1}, journal={American Scientific Research Journal for Engineering, Technology, and Sciences}, author={Erkan Yilmaz and Ekrem Aydiner and Özgur Ökcu}, year={2023}, month={Mar.}, pages={26–45} }