Abstract
Mathematical models can give us information on number of cases, deaths caused by infectious diseases. In this study, we aimed to predict the effects of Crimean-Congo Hemorrhagic Fever (CCHF), tuberculosis (TB), measles for Turkey and the efficiency of SI and SIS mathematical models were defined in the prediction of the number of infected people for these diseases. In CCHF, predictions for 2014 gave 0% error in both models. As for TB, SIS model predicted the exact number and SI model predicted a few more cases than that of SIS model. Again SI and SIS models gave the exact values for measles. According to these predictions it seems that CCHF and TB cases will continue to increase slightly while measles cases will approach zero. These models can predict exact numbers for each year, in a long term and in normal conditions (unless there are external parameters such as natural disaster, war, emigration and terrorism ) they can predict the trend for the diseases and can tell when to disappear. Therefore, updating data are of importance to achieve the powerful prediction.
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More From: International Journal of Computational and Experimental Science and Engineering
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