Abstract 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.

中文翻译：

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基于个体的抑郁症患病率预测模型

摘要 重度抑郁症（depression）是一种常见的精神疾病。在这里，提出了一种基于离散时间的个体模型来预测抑郁症患者百分比的时间演变。引入归一化指数 Ii 来反映第 i 个个体的心理健康状况：Ii 值低对应心理健康；高值，到抑郁状态。Ii 的变化是由取决于个人的精神病史和社会人口特征、影响他们的风险因素以及恢复率的规则驱动的。计算模拟是使用巴西和德国最近几年的官方数据进行的。尽管女性的患病率更高，但只有当女性在认知上比男性更能适应抑郁症时，该模型才适合数据；