Dynamic modeling of major depressive disorder: Calculating the rate of occurrence and recurrence

The major depressive disorder is a long-lasting disorder that results in major functional and social disorders. According to the World Health Organization, the major depressive disorder will become the second leading cause of disease worldwide in 2020. The purpose of the present study was to present a second-orderer nonlinear dynamic model underlying depression disorder using computational modeling that can justify the conditions of occurrence and recurrence of depression.

In this model, two mathematical equations were presented which consisted of several effective quantities in the generation of major depressive disorder such as the volume of the hippocampus, serotonin levels, amygdala volume, psychological external factors and unpredictable processes and the history of previous periods of the patient were considered. The data were analyzed on the 1002 depressed people periods, over a 64-year normal life span.

The results of the presented model show that in the dynamic model, the duration curve of depression in patients under the antidepressant drugs and the third wave cognitive behavioral therapy was widespread, with an average of 1019 days.

The study developed a mathematical framework, which will eventually lead to the development of more detailed models for a major depressive disorder and a better perception of the major depressive disorder and its effects on cognitive processes.