Generating evidence on delivering community-based interventions for vulnerable populations affected by climate change in Pakistan

About this project

Climate change, especially heat-related emergencies and consequences such as floods, have been shown to disproportionately affect the health (including mental health) and wellbeing of women and children. Pakistan is one of the countries that is most vulnerable to the effects of climate change. This project aims to develop appropriate community-based intervention packages targeting the adaptation and resilience-building priorities for action in two climate-affected districts in the north and south of Pakistan. The project will then work with the public sector’s Lady Health Workers Program to assess the feasibility of implementing these proposed intervention packages. Subsequently, the effectiveness of these interventions will be evaluated in terms of community resilience and health and nutrition in vulnerable women and children. The project will generate academic publications with accompanying evidence summaries and briefs targeted for different audiences, focused on results of the quantitative and qualitative analyses and their implication for community-based adaptation and resilience in Pakistan as well as other settings. Training materials and tools will be developed for community health workers, other community-based personnel and primary health care facility staff that could be adapted for training and implementation in other settings. The findings of this body of work will help bridge important global evidence gaps and inform national and global policies for promoting r…

Published by

International Development Research Centre · Other public sector

Countries

Pakistan

Sectors

Health policy and administrative management

Focus

Gender equality · Also contributesClimate adaptation · Main focusMaternal, newborn and child health · Main focus

Published by International Development Research Centre to the International Aid Transparency Initiative (IATI), last updated 1 Sept 2026 and imported automatically. IATI identifier: XM-DAC-301-2-110524-001.

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