Spatial clustering of autism spectrum disorders in Kelantan, Malaysia: Urban hotspots and rural gaps

Abstract

The geographic distribution of autism spectrum disorders (ASD) remains poorly characterized in many developing settings, including Malaysia, where rural populations face notable healthcare access gaps. We mapped spatial clustering of ASD subtypes (severe, high-functioning and mild) in Kelantan, a predominantly rural Malaysian state, to examine diagnostic disparities. In this cross-sectional spatial epidemiological study, 103 ASD cases (2022–2024) from two major Kelantan centers were analyzed at the district level. Global Moran’s I assessed overall spatial autocorrelation and optimized Hot Spot Analysis (Getis-Ord Gi*) identified local clusters of high or low ASD incidence. Moran’s I revealed significant positive clustering for mild (I≈0.065, p<0.001) and high-functioning ASD (I≈0.039, p=0.0096) cases reflecting urban concentration but no significant autocorrelation for severe ASD. Optimized hotspot analysis localized statistically significant high-incidence clusters in Kota Bharu and surrounding districts, while rural districts emerged as cold spots. This urban-rural pattern mirrors known disparities (ASD diagnoses concentrate where healthcare access is better) and suggests underdiagnosis in underserved areas. Uneven geographic distribution of diagnostic resources likely drives these patterns. These results reveal service-related inequalities in ASD diagnosis in Kelantan and reinforce the need for targeted healthcare interventions and expanded screening in rural communities to ensure equitable care.