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Climate Resilience Measurement Lab

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Climate change is exacerbating poverty in low- and middle-income countries (LMICs), with the poorest populations hit hardest. Even when broader populations remain unaffected, vulnerable groups in these countries face the brunt of environmental shocks like natural disasters, losing wealth and experiencing higher mortality rates.  

The urgency for poverty alleviation is clear: Climate adaptation strategies are essential to combat the growing threats of food insecurity, income loss, health impacts, and displacement. However, a lack of robust data on climate resilience in LMICs is hindering efforts to identify the most vulnerable populations and assess the effectiveness of adaptation measures.

While global frameworks like the UN’s Global Goal on Adaptation set action areas, existing measures of climate resilience focus mainly on national-level disaster management. They do not capture the nuanced effects on individuals and households – critical data needed to inform effective interventions.

The Climate Resilience Measurement Lab aims to create standardized tools for measuring resilience at the individual and household levels. By integrating these tools into other ongoing large-scale surveys, this effort could transform how governments, NGOs, and researchers understand and respond to climate impacts. 

Initial research will be conducted starting in Bangladesh with the International Centre for Diarrhoeal Disease Research, Bangladesh. The lab’s long-term goal is to produce high-resolution maps and actionable data, enabling targeted interventions that better prepare populations for climate hazards. Eventually expanding to other countries and by linking socioeconomic factors and health outcomes, these tools could catalyze policy changes and evaluate the effectiveness of adaptation strategies, ultimately offering a path forward for reducing the climate-driven poverty that disproportionately affects the world’s most vulnerable populations. 

Team

Selected Work

Papers

Flooding and elevated prenatal depression in a climate-sensitive community in rural Bangladesh: a mixed methods study