SheffWHO 2026 Theme Guide

AI Futures: Advancing Global Equity

Equity means no one is held back by unfair, avoidable gaps – income, location, background. Global health equity aims for the best possible health for everyone, but demand is rising faster than resources.

AI learns from data to spot patterns and support decisions. In health, it can strengthen diagnosis, surveillance, and forecasting – something COVID-19 made impossible to ignore.

The stakes are rising: climate change is shifting disease risks and straining services, and primary care needs are growing fast. AI could help predict threats and target support, but only if it is reliable, transparent, and fair – and does not deepen bias or exclude vulnerable groups.

That’s why the 2026 SheffWHO World Health Assembly simulation will test both the promise and the pitfalls of AI across infectious diseases, primary care, and climate change – plus the real economics of using AI in public health.

Economics of AI for Public Health Programs

AI can deliver faster, more efficient public health analysis, but without careful economic planning it risks widening global health inequalities.

Its integration into public health systems requires smart decisions on cost-effectiveness, funding, and resource allocation to ensure equity, accountability, and long-term sustainability across prevention, surveillance, and service delivery.

AI for Climate Resilient Healthcare

Climate change is a major global threat to health, and while healthcare already accounts for around 4.4% of global emissions, the expansion of AI infrastructure adds further pressure.

When designed responsibly, AI can dramatically cut emissions, strengthen climate-informed early warning and prediction, and – through equitable investment, global collaboration, and strong governance – support climate-resilient health systems rather than deepen existing inequalities.

AI for Infectious Disease Detection and Response

Infectious diseases remain a major global health challenge, and AI is transforming outbreak detection and response by turning complex data into earlier, more accurate warnings. However, these gains depend on strong infrastructure, high-quality data, and ethical governance – without them, AI risks widening gaps instead of strengthening preparedness.

AI Applications in Primary Care

Primary Health Care (PHC) is the heartbeat of any national health system. However, the system is currently "clogged." Between a global shortage of 10 million health workers and the administrative "paperwork mountain," the front line is under immense pressure.

Integrating AI at this level, can help to optimize these overstretched workflows.