Resources

This factsheet focuses on the development of BABE—a low-cost bubble continuous positive airway pressure (bCPAP) device with oxygen blenders to help babies with respiratory distress syndrome. BABE is designed to provide bCPAP therapy to preterm newborns without requiring a power source (i.e., electricity or battery) or medical-grade compressed air.

PATH’s Center for Advocacy and Policy convened a two-part webinar series to examine how Africa can sustain and accelerate maternal, newborn, and child health (MNCH) progress amid shrinking global aid.Part 1: MNCH Financing in Africa – This session explored the shifting aid dynamics shaping MNCH and highlighted the urgent need for sustainable funding, collective action, and innovative partnerships.Part 2: Accelerating Progress Despite Declining Aid – The second session examined what shrinking development assistance means for MNCH in Africa and how countries can adapt. Speakers emphasized the importance of regional leadership, domestic resource mobilization, and innovative partnerships to ensure health systems remain strong and resilient in the face of declining aid.Watch the recordings below to learn more about the evolving aid landscape and strategies to secure a healthier future for women and children in Africa.

According to the World Health Organization, medical oxygen is one of the key essential medicines required for multiple health conditions, including asthma, heart failure, and various newborn complications. Over the last decade, the Ugandan government has worked to improve access to medical oxygen. The National Scale Up of Medical Oxygen Implementation Plan (2018–2022), launched in 2019, guided this progress, which included increasing manufacturing capacity and installing oxygen plants at referral hospitals.

Immunization is one of the most impactful and cost-effective public health interventions available, saving up to 4 million lives every year, according to the World Health Organization (WHO). In addition to its direct impact on the health of populations, immunization brings added value by reducing the burden of disease on individuals, families, and communities.

In Nigeria, Community Health Extension Workers (CHEWs) are essential to providing frontline health care, particularly in rural and underserved areas where physician shortages are most pronounced. However, they face a significant challenge in their limited access to real-time, comprehensive information that could support timely, accurate decision-making for a wide range of health concerns. Studies have shown that poor utilization of primary health care facilities in Nigeria is often attributed to perceived poor quality care, with CHEWs sometimes struggling to access the necessary information to manage patients effectively (Luka-Lawal et al. 2020). Existing research indicates that CHEWs can deliver safe and effective care when given adequate support. A study conducted in South-South Nigeria found that CHEWs had good results when given access to physician consultation via telephone (Ordinioha and Onyenaporo 2010). These findings suggest that providing decision-support resources enhances the ability of CHEWs to manage cases at the community level.Given the demonstrated benefits of telephonic physician support, this study explores whether a system driven by artificial intelligence (AI) could serve a similar role in enhancing CHEW decision-making capabilities. Unlike physician-supervised telephone consultations, which require ongoing human resources, a Large Language Model (LLM)-based system could provide scalable, on-demand access to health care knowledge without relying on direct physician availability. By integrating LLMs into the CHEW workflow, this study seeks to evaluate the feasibility of AI-driven decision support in improving patient outcomes, reducing unnecessary referrals, and strengthening primary health care service delivery in Nigeria.