By World Bank

The world is facing an era of compounded crises, from pandemics to conflicts to intensifying extreme weather events. For low-income and vulnerable households, particularly in fragile and conflict-affected states, these crises are devastating, erasing development gains, and increasing poverty and food insecurity.

A critical question looms as the polycrisis and the resulting development challenges, including historic levels of migration, surging food prices, and environmental degradation, continue to unfold.

How can we generate the granular, real-time data needed to design and target effective policies to strengthen resilience of vulnerable populations in the face of health, economic and climatic shocks? Part of the answer lies in transforming the way we collect and use socioeconomic survey data – through longitudinal, multi-topic, high-frequency, and interoperable survey systems.

The imperative for agile and inclusive data systems

Resilience, defined as the ability to anticipate, absorb, and recover from shocks, is a multidimensional concept that can be defined for individuals, households, communities and societies.

Besides income, resilience frameworks often include capabilities related to health; food security and nutrition; safely managed water, sanitation, and hygiene (WASH) practices; education; improved energy and cooking solutions; digital technologies and services; financial inclusion; social protection, and climate adaptation, among others. However, existing data systems in many low-income countries fall short of measuring and monitoring resilience and its different dimensions.

On the one hand, nationally representative household surveys conducted by national statistical offices (NSOs), while providing invaluable socioeconomic information, are often infrequent and lack the longitudinal designs needed to track changes over time. Their questionnaires often fall short of capturing resilience in its multiple dimensions and their sampling designs are not temporally adaptive as to oversample communities and households in disaster-affected geographies. These shortcomings create blind spots in our understanding of vulnerability and resilience, hindering the design and targeting of interventions that can improve the lives of populations vulnerable to climate extremes.

On the other hand, advances in satellite imagery, remote sensing, and artificial intelligence (AI) have dramatically improved our spatial understanding of vulnerability to climatic shocks and conflicts, and yet they alone are not enough to inform policies to strengthen resilience of vulnerable populations. These tools still cannot provide an inside look into the lives and struggles of vulnerable individuals and households and their effectiveness is constrained by a lack of georeferenced ground truth data that can technically be sourced from surveys to train and validate predictive models.

Supporting national statistical offices to institute longitudinal, multi-topic, high-frequency, and interoperable survey systems can help bridge these gaps. This would create long-lasting country capacity to produce policy-relevant and responsive surveys data, while enabling the seamless integration of surveys with geospatial data to derive highly localised insights on resilience and vulnerability, including in locations where it may not be possible to commission surveys due to conflicts and other calamities.

Introducing Resilient Futures 

The Resilient Futures Initiative, spearheaded by the Living Standards Measurement Study (LSMS) – the World Bank’s flagship household survey programme – in partnership with the World Bank departments and national statistical offices (NSOs), aims to fill these critical data gaps.

Building on the success of a past longitudinal survey initiative known as the LSMS-Integrated Surveys on Agriculture (LSMS-ISA), Resilient Futures will institute an improved, forward-looking longitudinal survey system that can speak to the data and knowledge needs of the polycrisis era, starting in 15 climate-vulnerable low- and middle-income countries.

Key features of Resilient Futures
Mixed-mode survey design: Resilient Futures will implement nationally representative face-to-face longitudinal surveys of 3,000 to 5,000 households per country, every three years, using computer-assisted personal interviewing (CAPI). In between face-to-face interviews, the same households will be interviewed over the phone, at a minimum quarterly basis (or more frequently, based on the data needs). This approach will allow for timely and high-frequency tracking of resilience indicators and changes in health, dietary and broader economic needs.
Harmonised multi-topic questionnaires: Rigorously tested, harmonised and multi-topic questionnaires will be rolled out across all the countries supported by the Initiative. This will facilitate cross-national comparisons and capture high-quality data on key resilience capacities of individuals, households, and communities – in relation to health, education, WASH, energy access, work and employment, consumption and income, food security and nutrition, social protection, digital technologies, financial inclusion, and climate adaptation, among others.
Georeferenced data collection and climate-sensitive sampling: Nationally representative longitudinal surveys will, for the first time, oversample households in climate-vulnerable areas and create opportunities to bring in new communities and households following disasters. And by georeferencing sampled household locations, we will provide previously unavailable, representative insights on the socioeconomic conditions and changes in vulnerable populations.

Open-access data to enable AI-powered insights: All unit-record survey data will be anonymised and will be made publicly available within a maximum of six months of completion of face-to-face surveys and within one month of completion of phone surveys. These georeferenced datasets will in turn calibrate and validate remote sensing and AI models, enhancing the accuracy of climate risk and impact analyses in localities and countries beyond where the interviews are conducted.

Capacity strengthening and innovation: The Initiative will strengthen statistical capacity of partner NSOs and will be inclusive of a programme of methodological innovation to further improve the quality, relevance and timeliness of data generated by Resilient Futures and all relevant NSO-owned surveys.
Driving impact across sectors
Resilient Futures is not just about data collection – it’s about transformation.

The Initiative will enable policymakers to:

Better anticipate and respond to shocks: High-frequency monitoring will provide early warnings and inform rapid responses to emerging crises.
Design more effective resilience-strengthening interventions: Resulting data, analytics and AI applications will help prioritise and design locally relevant policies/interventions in several sectors to bolster the most effective resilience capacities. This will in part be permitted by more rigorous ex-post impact evaluations that reveal which interventions yield the desired effects and lend themselves to replication elsewhere.

As a result, beneficiary individuals, households and communities will be better positioned to anticipate, absorb, and recover from future crises.
Call to action: Invest in resilience data
The urgency to act cannot be overstated. We cannot afford to wait for the next pandemic or natural disaster to expose the vulnerabilities of our current data systems. Resilient Futures represents a proactive approach, creating the infrastructure needed to address crises before they occur while also producing global public goods that will be used.

Resilient Futures requires a multi-donor partnership that we are in the process of forging, complementing resources from governments with those from international organisations, and private philanthropy. We are calling on all interested resource partners to join us!

As we pave the path to a more livable planet, we must recognise the foundational role of data in resilience-building. Resilient Futures offers a blueprint for integrating climate action with socioeconomic development, ensuring that no one is left behind in the fight against climate change.

The time to invest in resilient data systems is now – because a resilient future depends on it.

About the authors

STEPHANE HALLEGATTE (Senior Climate Change Advisor, Sustainable Development Practice Group, World Bank)

Stéphane Hallegatte is the Senior Climate Change Advisor of the World Bank Climate Change Group. He joined the World Bank in 2012 after 10 years of academic research. His research interests include the economics of natural disasters and risk management, climate change adaptation, urban policy and economics, climate change mitigation, and green growth.

Talip Kilic (Senior Program Manager, Development Data Group, World Bank)

Talip Kilic is the Senior Program Manager for the World Bank Development Data Group’s Living Standards Measurement Unit, which houses the Living Standards Measurement Study (LSMS); the World Bank’s flagship household survey program, and Survey Solutions; the World Bank’s open-source CAPI/CATI/CAWI software platform for design, implementation and management of large-scale surveys and censuses.