Resources

PATH, in collaboration with the Maharashtra Department of Health and Family Welfare, conducted a biomedical equipment survey in health facilities across the state in January 2024. This report analyzes data collected through facility assessments to provide a snapshot of the medical oxygen ecosystem of 34 health facilities in 27 of Maharashtra’s 36 districts. The purpose of this work is to quantify existing oxygen delivery and production equipment, consumables for administering oxygen therapy, bed capacity, and facility infrastructure characteristics.

PATH, in collaboration with the Uttar Pradesh Department of Health and Family Welfare, conducted a biomedical equipment survey in health facilities across the state in January 2024. This report analyzes data collected through facility assessments to provide a snapshot of the medical oxygen ecosystem of 149 health facilities in 65 districts across Uttar Pradesh, India. The purpose of this work is to quantify existing oxygen delivery and production equipment, consumables for administering oxygen therapy, bed capacity, and facility infrastructure characteristics.

This slide provides a snapshot of the respiratory syncytial virus (RSV) vaccine and monoclonal antibody (mAb) technology landscape, in the effort to track the development of RSV vaccine and mAb candidates and provide a summary of the various vaccine approaches being worked on around the world.This snapshot pairs with the RSV and mAb Trial Tracker, which provides publicly available information on clinical trials of RSV candidate vaccines and mAbs intended for prevention.To share any updates or corrections to the snapshot, please contact rsvsnapshot@path.org.

This spreadsheet provides publicly available information on clinical trials of respiratory syncytial virus (RSV) candidate vaccines and monoclonal antibodies intended for prevention.Sources of information for these trials are clinicaltrials.gov; who.int/clinical-trials-registry-platform; clinicaltrialsregister.eu; and anzctr.org.au, which includes clinical trial registries from 17 countries.Some information is also obtained through contact with investigators, sponsors, and funders of vaccine trials. This spreadsheet pairs with the RSV Vaccine and mAb Snapshot, which provides a summary of the RSV vaccine and mAb candidates in development worldwide.To share any updates or corrections to the tracker, please contact rsvsnapshot@path.org.

The integration of artificial intelligence (AI) technologies into clinical practice stands as a defining challenge and opportunity for global health in the coming decade. While use cases such as clinical documentation and diagnostic support are becoming increasingly common in high-resource settings, where over half of clinicians now report using AI tools, much less is known about frontline clinicians’ experiences, barriers, and real-world needs in low- and middle-income countries (LMICs).In LMIC contexts, large language model (LLM)-enabled clinical decision support systems (CDSSs) offer the potential to extend high-quality decision support to settings with limited human and technical resources. Yet they also carry significant risks, including language bias, inequitable access, limited local capacity for oversight, and the possibility of recommendations that are misaligned with local medical guidelines that undermine patient safety or trust.Over the past two years, rapid advances in generative AI have outpaced the establishment of evidence, governance, and capacity frameworks required for responsible use. Health systems and policymakers are now faced with urgent questions:How can AI tools be evaluated for clinical safety and contextual relevance?What data infrastructures and regulatory mechanisms are needed for equitable deployment?And how can local researchers and health institutions lead, not just participate, in AI innovation?These questions form the basis of this CDSS Learning Agenda, which aims to generate collective insight and actionable evidence to guide safe, effective, and equitable integration of AI into health systems. The agenda identifies six thematic priorities—localization and language equity; evaluation and real-world evidence; voice-enabled and multimodal tools; capacity and local ownership; governance and trust; and infrastructure and enabling environments—that collectively define the ecosystem required for sustainable AI adoption in LMICs.