Early Detection of Cerebral Palsy: From Evidence to Equitable Implementation

Cerebral palsy (CP) is the most common cause of physical disability in childhood worldwide, affecting approximately 1-4 per 1,000 live births, with prevalence significantly higher in low- and middle-income countries (LMICs). Although the condition is difficult to manage, early diagnosis can help prevent disability caused by the condition. Current international guidelines suggest diagnosis as early as 3-5 months of corrected age, using a combination of General Movements Assessment, Hammersmith Infant Neurological Examination, and magnetic resonance imaging. In high-income countries, early diagnosis of CP has demonstrated feasibility and high acceptability among families and professionals. In contrast, it remains severely underutilized in LMICs, where CP prevalence is higher and clinical presentations more severe.


The central challenge is no longer whether early detection is clinically possible, but how to implement it at scale in the settings where it is most needed. This Research Topic seeks to address this implementation gap by bringing together original research, implementation science, health policy analysis, and technological innovation focused on translating early CP detection into sustainable, equitable practice in resource-limited settings. By consolidating evidence across diverse settings and disciplines, it aims to provide a roadmap for health systems worldwide to close the gap between what is clinically possible and what is systematically delivered, ensuring that every infant at risk of CP, regardless of where they are born, has the opportunity for timely diagnosis and intervention during the critical window of neuroplasticity.


We invite contributions on:

(1) contextually adapted early detection pathways, including development, validation, and comparative effectiveness of screening tools (GMA, HINE, simplified assessments) in LMIC populations, and adaptation of international guidelines for low-resource contexts;

(2) implementation strategies addressing health system, workforce, and social barriers, including integration into maternal and child health programs, task-shifting, and cost-effectiveness;

(3) low-cost, scalable technological innovations such as telehealth, AI-assisted screening, and mobile health tools;

(4) health equity and access, particularly for rural and marginalized populations; and

(5) the impact of early diagnosis on child development, family wellbeing, and health systems in resource-constrained environments.

We welcome Original Research, Reviews, Study Protocols, Policy Briefs, and Implementation Case Studies.