July 2023 has the dubious distinction of being the planet’s hottest month ever recorded. We can say this with great certainty, thanks to a massive distribution of increasingly sophisticated climate sensors, and a collaborative network of meteorologic and atmospheric monitoring facilities that makes real-time analysis and future projections possible, with incredible precision.

That same network makes it more feasible than ever before for experts to determine where and when climate-sensitive infectious diseases like malaria and dengue are likely to be transmitted and creates the potential for more cost-effective use of the limited resources available to eliminate these diseases entirely.

Global warming threatens to increase the spread and volatility of many infectious diseases.

Rising temperatures, extreme weather events, and changing rainfall patterns all impact the way vector-borne diseases like malaria and dengue are transmitted – complicating global efforts to eliminate these terrible diseases and putting new and more vulnerable communities at risk.

Malaria alone already kills more than 600,000 people every year – most of them young children in sub-Saharan Africa – and experts predict that cases could double by 2050, and triple by 2080. Sixty per cent of the global population is expected to be at risk of contracting dengue fever by 2080.

Even as global warming threatens to increase the spread and volatility of many infectious diseases, our ability to predict and prevent outbreaks is increasing at an amazing pace.

Scientists around the world are using novel sources of climate data, high resolution satellite imagery, and artificial intelligence to create actionable tools for health system decision-makers. These models go far beyond “early warning”, by creating highly precise decision-support tools that equip health systems with the ability to make the best use of the tools they have; dispatching resources where and when they’re most needed to avoid upticks in infection rates, and ultimately eliminating the spread of the disease.

We call this approach precision programming: the “just in time” use of limited domestic and development resources, for maximum progress toward disease elimination.

That level of knowledge, predictive capacity, and actionable intelligence is a big part of what constitutes “climate resilience” in vulnerable health systems.

In 2022, the Forecasting Healthy Futures consortium established what is now the Institute for Health Modelling and Climate Solutions (IMACS). This is a global centre of excellence for climate and disease modelling, dedicated to improving the design, uptake, and utilisation of advanced early warning systems to create operational efficiencies in disease control and elimination programmes worldwide.

IMACS was formally launched at a summit event during last year’s Abu Dhabi Sustainability Week, with financial support from Reaching the Last Mile, a portfolio of global health initiatives funded by Sheikh Mohamed bin Zayed Al Nahyan, President of the United Arab Emirates.

Since then, the Institute has convened a network of more than 30 global experts in climate- and AI-enabled disease prediction models, working to advance the discipline and reduce barriers to implementation in countries on the front lines – the “fault lines” – of climate change and global health

More investment is needed in effective surveillance systems, the use of sophisticated climate data sources, and the application of artificial intelligence to anticipate and avoid the worst effects of climate change on the spread of infectious diseases worldwide.

If we invest wisely, those tools and capabilities could result in real progress toward the elimination of the diseases that plague resource-limited countries throughout Africa and elsewhere today, despite the serious challenges presented by global warming.

We are essentially engaged in a race to use data and technology to advance disease elimination, faster than global warming can set us back. Climate-resilient health systems require sophisticated data systems and the local capacity to apply them effectively. - PA