Spatial risk assessment and hotspot mapping of free-roaming dog bites in Tehran, Iran: A public health perspective

Abstract

free-roaming dogs pose significant public health and ecological challenges in urban and rural landscapes, particularly in developing countries. In Tehran Province, Iran, the increasing frequency of free-roaming dog bites and their role as potential reservoirs for zoonotic diseases underscore the need for spatially explicit risk assessment. This study utilized the MaxEnt model to predict the spatial distribution of free-roaming dogs and identify high-risk areas for dog bites based on environmental and climatic variables. A dataset of 3,630 free-roaming dog bite incidents recorded for Tehran Province in 2023 was analyzed alongside 13 environmental and 6 climatic predictors. The model demonstrated high predictive accuracy (AUC = 0.934 for training, AUC = 0.931 for testing). Results highlighted distance to roads (74%) and distance to parks (12.1%) as the most influential factors, while climatic variables played a secondary role. The spatial analysis revealed that high-risk areas are concentrated in the north (Districts 1 and 2), southern and eastern outskirts of Tehran City (e.g., Districts 15, 16, 19, and 20) and suburban counties such as Qarchak, Varamin, and Pakdasht. Further hotspot analysis (Getis-Ord Gi) and LISA clustering confirmed significant spatial autocorrelation (Moran’s I = 0.7; p-value ≤ 0.05) and identified critical clusters for intervention. These findings provide valuable insights into the spatial dynamics of free-roaming dog bites, enabling policymakers to prioritize high-risk areas for population control measures, public awareness, and waste management improvements. Integrating these results into urban planning frameworks can mitigate public health risks, reduce human-dog conflicts, and promote sustainable free-roaming dog management strategies.