An individual-based model for predicting the prevalence of depression
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Carta ao editor
Date
2019
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Ecological Complexity
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4
Authors
Loula R.
Monteiro L.H.A.
Monteiro L.H.A.
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Abstract
© 2019 Elsevier B.V.Major depressive disorder (depression) is a common psychiatric illness. Here, a discrete-time individual-based model is proposed to predict the time evolution of the percentage of people suffering from depression. A normalized index Ii is introduced to reflect the psychological health condition of the ith individual: low values of Ii correspond to mentally healthy; high values, to depressive state. Changes on Ii are driven by rules that depend on the psychiatric histories and socio-demographic features of the individuals, on the risk factors affecting them, and on the recovery rate. Computational simulations were performed by using official data from Brazil and Germany in the latest years. Despite the prevalence in women being higher, the model fits the data only if women are more cognitively resilient to depression compared to men; that is, when exposed to the same risk factors, the value of Ii for women is lower than the value of Ii for men.