Analyzing municipal patterns of suicide and depression in Mexico: a multilayer network approach

This study analyzes the territorial patterns of suicide and depression in Mexican municipalities from 2015 to 2020 using a multilayer network approach. A panel dataset was constructed with variables grouped into three categories: mental health cases (suicide and depression rates), substance use (alcoholism, tobacco use, and drug use), and infrastructure availability (mental health services and resources). Cosine similarity was used to generate multilayer graphs, and the Infomap algorithm was applied to identify clusters of municipalities with similar structural characteristics. The results show clear differences across clusters in both levels and temporal dynamics of the indicators. Notably, Clusters 1 and 2 consistently exhibited higher rates of substance use and mental health indicators. These findings highlight the value of network-based approaches to understanding the territorial and temporal dimensions of mental health.