Autism spectrum disorder (ASD) is a neurodevelopmental condition with significant disparities in diagnosis, treatment, and outcomes in the United States. These disparities are shaped by social determinants of health (SDOH), including socioeconomic status, access to healthcare, geographic location, racial and ethnic inequalities, and cultural perceptions. This paper proposes a conceptual public health analytics framework to address these inequities. The framework integrates clinical, demographic, and SDOH sources data to identify patterns and gaps in autism care, employs predictive modeling to allocate resources efficiently, and emphasizes community engagement to ensure culturally sensitive interventions. Policy alignment is also highlighted to translate data insights into actionable reforms for equitable autism care. By addressing SDOH through innovative public health analytics, this framework offers a scalable and adaptable solution to mitigate health disparities, improve early diagnosis, and foster inclusivity in autism care. The findings underscore the importance of interdisciplinary collaboration, robust data systems, and community-driven approaches to achieve equitable outcomes for individuals with autism.
Autism spectrum disorder (ASD), Social determinants of health (SDOH), Health disparities, Public health analytics, Predictive modelling, Equitable healthcare
IRE Journals:
Omotoke Modinat Drakeford , Nkoyo Lynn Majebi
"Social Determinants of Autism in the U.S.: Conceptualizing a Public Health Analytics Framework to Address Health Disparities" Iconic Research And Engineering Journals Volume 8 Issue 6 2024 Page 264-273
IEEE:
Omotoke Modinat Drakeford , Nkoyo Lynn Majebi
"Social Determinants of Autism in the U.S.: Conceptualizing a Public Health Analytics Framework to Address Health Disparities" Iconic Research And Engineering Journals, 8(6)