Introduction. Traditional geospatial analysis of crime incidence is usually based on kernel density models and physical contiguity analysis to explain the displacement of violence, under the assumption of the so-called "neighborhood effect". However, this approach is insufficient to capture the nature of complex systemic phenomena where violence does not necessarily spread through proximity, but rather through nodes of functional connectivity and flows of human mobility. Recent literature on the geography of crime has begun to suggest that spatial models based solely on proximity omit the underlying dynamics that interconnect non-contiguous territories. This study proposes a comprehensive methodology based on network analysis to evaluate the geospatial dynamics of femicide in the 46 municipalities of the state of Guanajuato, Mexico. This approach allows us to transcend the static view of the territory and visualize the state as an interconnected system of dynamic risks, offering a perspective that integrates temporal synchronization variables on the spatial structure.
Methodology. The research starts from the construction of a topological network where the nodes represent the municipalities and the edges symbolize the intensity of the Hurdle temporal correlation (r) between their respective historical series of femicides. To filter out statistical noise and focus on strong relationships, a dynamic threshold of statistical synchrony (|r| > 0.4) was applied to municipalities with more than 3 feminicides. Subsequently, the Louvain community detection algorithm was implemented, a heuristic method designed to optimize network modularity and segment the territory into clusters based on synchronous criminal behaviors, regardless of their geographical location. To facilitate the exploration of this data, a dynamic geovisualization tool was developed (implemented using advanced web visualization libraries). This platform allows for real-time interaction: users can adjust correlation thresholds, visualize the weight of nodes (based on the cumulative total of cases), and examine the network topology through an intuitive interface. This functionality allows a transition from traditional static analysis to high-level visual analytics, facilitating the identification of patterns hidden from the naked eye. Results. An interesting disconnect is revealed between territorial proximity and criminal dynamics, questioning the hegemony of the spatial contagion model. Three distinct criminal ecologies were identified through network analysis: 1) The Isolation of Industrial Epicenters: This geospatial anomaly is maintained in the absolute epicenters of violence: León, Celaya and Irapuato. These municipalities, which concentrate a high volume of accumulated cases, operate under an apparent endemic temporary isolation. Topological analysis (output-input degree of the nodes) shows that these centers, despite being focal points of greater nominal incidence, maintain weak or negative correlations with their immediate periphery. This suggests that femicidal violence in these centers responds to structural, demographic and internal security factors specific to the urban core, characterized by a constant saturation that does not always fluctuate in sync with the rest of the state. 2) The "Strategic Periphery" and the Territorial Conflict: A critical finding is the identification of an extensive cluster that connects municipalities that, historically, are not part of the conventional industrial corridor, but are located on the borders of the state. This group includes Comonfort, Apaseo el Grande, Cortazar, Guanajuato and San Miguel de Allende, exhibiting robust internal connectivity. This network extends towards Tarimoro, San José Iturbide and Salvatierra. The configuration of this cluster is revealing: being located on the state peripheries, these municipalities have been, for years, the scene of an intense territorial dispute between criminal organizations (cartel war). The synchronicity in criminal behavior in this bloc is not accidental, but appears to be a byproduct of territorial control dynamics, where instability derived from high-impact conflict escalates to levels of gender violence, creating an ecosystem of shared insecurity in these border corridors. 3) Functional and Proximity Correlations: Finally, the model captures correlations that, while following contiguity logics, reinforce the validity of the network model by reflecting transport dynamics and population flow. The Salamanca-Yuriria and Acámbaro-Pénjamo axes stand out as "sensitive" or intuitive correlations. These connections demonstrate how administrative and regional mobility dynamics influence the spread of violence, allowing us to observe that the risk of femicide is not always random, but is channeled through established communication axes. Taken together, these findings demonstrate that femicide risk operates under a hybrid network logic: influenced by contiguity in functional communication axes, but dominated by a geopolitics of violence in border areas where conflict between criminal actors alters the municipal social fabric. Conclusions. The structuring of public prevention policies should not be limited to containment in geographically adjacent areas nor should it focus exclusively on the municipalities with the highest absolute volume of cases. Geospatial analysis, enhanced by analysis through graph theory algorithms, as well as interactive visualization, allows the discovery of non-contiguous corridors of violence (temporal clusters with r > 0.4). This evidence compels us to redefine intervention strategies towards an asymmetric and anticipatory model, where prevention is coordinated simultaneously in municipalities that, although distant on the map, share an identical criminal rate. This approach allows for the optimization of resources and action on the nodes of the network that function as precursors to violence in the state territory.