Living evidence map & synthesis of climate-related health impacts in cities

The evidence base on how climate change affects urban health is fragmented, uneven and hard to access. To change this, our living evidence map and synthesis on climate-related health impacts in cities builds directly on our work to develop a comprehensive living repository of the global climate and health literature. For Impact Case 2 (IC2) we use the repository as a foundation, drawing on the full evidence base that Impact Case 1 (IC1) assembles to extract and focus on studies relevant to cities and human settlements. This includes informal settlements, which face some of the greatest climate risks but are least represented in the literature. Having a dedicated impact case for cities addresses the specific characteristics of urban contexts (density, infrastructure, governance structures and social dynamics) that require a city-level synthesis rather than a global review. Alongside the evidence map, we will produce a gap map with a structured picture of where knowledge is missing. For informed decision-making, knowing where the evidence is weak is as important as knowing where it is strong.

A protocol for this impact case will be submitted by November 2026. The living evidence map and gap map are planned to be completed by the end of 2027. Finally, an evidence transfer framework will be completed in early 2028 based on previous results. These outputs are designed to give city stakeholders and networks the evidence they need to make faster and better-informed decisions on climate and health.

In parallel, we respond to a fundamental gap in how climate and health research is distributed globally. Most climate and health research has been conducted in data-rich, higher-resource settings, while cities in lower-income countries, often most exposed to climate hazards, have less evidence available for decision makers to draw on . We aim to develop an evidence transfer methodology to identify which findings from data-rich cities can be meaningfully applied to data-poor cities , based on shared characteristics such as climate profile, urban structure and health system capacity.