Early Identification of Autism Spectrum Disorder (ASD): Strategies for Use in Local Communities

Area of Science:

• Developmental Pediatrics
• Global Health
• Neurodevelopmental Disorders

Background:

• Early diagnosis of autism spectrum disorder (ASD) is critical for intervention and improved outcomes.
• Limited data exists on ASD prevalence in low- and middle-income countries (LMIC), potentially delaying early identification.
• Existing disparities in ASD identification are often exacerbated in LMIC settings.

Purpose of the Study:

• To review recent studies on early ASD detection strategies and prevalence in LMIC.
• To discuss limitations in early ASD identification within LMIC communities.
• To recommend culturally appropriate, scientifically valid, and community-integrated models for early ASD identification.

Main Methods:

• Systematic review of recent literature on ASD early detection and prevalence in LMIC.
• Analysis of limitations and challenges in early ASD identification in resource-limited settings.
• Identification and evaluation of screening tools and strategies suitable for LMIC.

Main Results:

• Paucity of data on ASD prevalence in LMIC necessitates further research.
• Cultural appropriateness and community integration are key factors for successful screening tools.
• Simplified, demystified identification processes and strong community connections are vital.

Conclusions:

• Culturally sensitive and scientifically valid screening models are needed to reduce disparities in early ASD identification in LMIC.
• Community-based approaches can strengthen systems and improve outcomes for children with ASD.
• Local initiatives in simplifying ASD identification can inform global policy and practice.