Policies and interventions seeking to build resilience among the poor and vulnerable need to be underpinned by an understanding of the communities they target. An adequate understanding of who the vulnerable are and the ways in which they are vulnerable is imperative for actors both within and outside the social protection systems and allows for intervening more effectively before, during and after a natural disaster. Yet, information to guide decision-makers is scarce in many developing countries, which partly stems from the costs and complexities of collecting socioeconomic data. In the United Beneficiary Registry (UBR), Malawi is endowed with a comprehensive social registry, both in population coverage and in the range of variables stored, which reflects an understanding of poverty as multidimensional. This rich database, however, has been sparsely used for analytical purposes and its potential to inform decision-making remains largely untapped, not least in the areas of disaster preparedness and response. Against this background, this contribution seeks to explore how the UBR can be leveraged as an instrument to forward the climate change agenda in Malawi, both within and beyond the social protection sector.
Sharing of data between policy fields with similar goals
In disaster-prone contexts, the data and information required by social protection actors tend to be very similar to that needed by disaster risk management (DRM actors), including humanitarian agencies. In these contexts, exemplified by Malawi, there is considerable scope for actors to jointly collect and administer data, which can both bring economies of scale for user programs and reduce the effort for citizens to register and report grievances (Leite et al., 2017). The notion of centralized data collection for actors with similar goals has already gained broad acceptance in the social protection field, with many countries having established integrated social registries: databases catering to the information needs of multiple programs. Expanding social registry stakeholders beyond the social protection field may be particularly feasible in these countries, as certain coordination mechanisms are already in place.
To exchange data and information across policy fields with similar goals may not only result in substantial cost-savings but could also pave the way for improved coordination and collaboration, which is much needed as no set of actors is likely to independently reduce vulnerability in the long term (Bowen et al., 2020). To this end, a better understanding of who receives what can facilitate operational linkages, such as coordinated resilience-building efforts prior to a hazard and a seamless transition between humanitarian support and social protection in its aftermath. Targeting systems operating in isolation, by contrast, risk leading to duplication of efforts and inequitable distribution of resources among people in need (Tebaldi, 2019).
Poverty and vulnerability
At the center of both the adaptive social protection and DRM agendas is an understanding of households’ vulnerability to natural hazards, which requires gathering data beyond poverty indicators as poverty is only one determinant of vulnerability, albeit a central one. Vulnerability has both a biophysical and a social component, where the former is concerned with the natural hazards a community is exposed to (floods, droughts, etc.) and the latter, the social factors that determine people’s susceptibility to harm and ability to respond (Cutter et al., 2003). Social vulnerability explains why some households fare worse than others when faced with an identical hazard event and can be assessed by looking at socioeconomic factors, such as social inequality, quality of housing and dependency on natural resources.
Whether targeting is based on a measure of poverty or vulnerability can have implications for identification and selection of beneficiaries, as the vulnerable are not necessarily the poorest. In the absence of preparedness support, vulnerable groups risk falling into poverty when exposed to a hazard, hence thwarting the poverty-reduction agenda. In Malawi, the social protection programs principally target the chronic poor with little attention given to the transient poor. Transient poverty, which is a manifestation of vulnerability, is in Malawi mainly addressed by humanitarian actors, for example, through the annual lean season response. Following an unusually poor harvest the previous year, the 2016/2017 lean season response reached as much as 40% of the population (Holmes et al., 2017). To adequately respond to the emergency, substantial resources from development programs were diverted to the humanitarian response, providing an example of how the two sectors are interlinked in Malawi.
Leveraging the UBR for vulnerability assessments
The UBR data is in many respects already suitable for informing decision-making before, during and after a disaster. The data is georeferenced and, in the most disaster-prone districts, the registry has full population coverage. These features mean that the UBR possesses crucial information about the people affected, or at risk of being affected, by natural hazards, such as where they live and ways in which they are vulnerable. The UBR data, in combination with exposure data, can play an important role in informing preparedness measures and which geographical areas to prioritize for interventions. Figure 1 provides an example of a vulnerability map in which historical flood frequency (serving as an indicator of flood exposure) is overlaid with a Household Social Vulnerability Index (HSVI) created from the UBR data, achieved by using Geographical Information Systems (GIS). The HSVI is mapped at a fine spatial resolution (with every square representing a surface of approximately 1.2 km2), which is useful when assessing vulnerability to spatially heterogeneous hazards, such as floods.
The georeferenced individual-level data can also be aggregated to administrative levels relevant to decision-makers. Figure 2 displays the average Household Social Vulnerability by Traditional Authority, which is also the level at which the Department of Disaster Management Affairs (DODMA) determines the allocation of emergency support following disasters. This allocation, however, is informed by a separate assessment with its own data collection.
The UBR’s path ahead
As compelling the idea of collaborating on data and information may be, its realization may face certain challenges, compounded by a tradition of social protection and DRM actors working in isolation from one another (Costella et al., 2023). While the UBR data already contains relevant information for DRM actors, a new round of dialogues on the registration questionnaire design is likely needed for the uptake of new stakeholders. Incorporating the preferences of these stakeholders may require compromises given questionnaire length limitations.
An important obstacle to using the UBR data in an emergency context is the relatively long interval between data collection rounds. The goal is for the UBR data to be updated every four years (followed by a new intake of social protection beneficiaries), which makes it of limited use for capturing the dynamics of poverty and vulnerability. Maintaining a 100% registration target while increasing the frequency of data collection would require a substantial increase in funding. However, not all parts of Malawi are equally affected by natural disasters and, faced with financial constraints, an alternative could be to increase the frequency of data collection only in certain areas. The most disaster-prone area in Malawi is the Lower Shire Valley, spanning Nsanje (Figures 1 and 2) and Chikwawa districts, which earlier this year saw Cyclone Freddy cause devastation and mass displacement. Pooling resources for acquiring data and information in this area could result in better informed disaster mitigation efforts while potentially also achieving overall net cost-savings through rationalization of the multiple sources of truth.
While this blog post mainly has discussed opportunities to use Malawi’s social registry beyond the social protection sector, the data exchange should ideally go in both directions. DRM actors, for example, can contribute with relevant information on natural hazards, such as early warnings, which are crucial for planning and carrying out horizontal expansions of social protection programs. This information, however, critically needs to be related to socioeconomic data that helps understand the capacities of households to withstand and recover from natural hazards. A unified socioeconomic database should allow for measuring different concepts relevant to the policy objectives of its stakeholders, which can have complementary roles and help minimize exclusion due to targeting errors. These concepts may not only include poverty and vulnerability but also related ones, such as livelihood vulnerability and food insecurity.
Bowen, T., Del Ninno, C., Andrews, C., Coll-Black, S., Johnson, K., Kawasoe, Y., & Williams, A. (2020). Adaptive social protection: building resilience to shocks. World Bank Publications.
Costella, C., van Aalst, M., Georgiadou, Y., Slater, R., Reilly, R., McCord, A. & Barca, V. (2023). Can social protection tackle emerging risks from climate change, and how? A framework and a critical review. Climate Risk Management, 100501.
Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). Social Vulnerability to Environmental Hazards. Social Science Quarterly, 84(2).
Holmes, R., Costella, C., Bailey, M., Kruczkiewicz, A., Poulter, R., Sharp, K., & Scott, L. (2017). Towards a shock sensitive social protection system for Malawi. London: Overseas Development Institute.
Leite, P., George, T., Sun, C., Jones, T., & Lindert, K. (2017). Social registries for social assistance and beyond: a guidance note and assessment tool. World Bank.
Tebaldi, R. (2019). Building shock-responsive national social protection systems in the Middle East and North Africa (MENA) region (No. 30). Research Report.
Sundqvist, P. (2023). Using a social registry to assess household social vulnerability to natural hazards in Malawi.
 Registration is conducted through a census-sweep approach with a 100% registration target
 In Malawi, the Malawi Vulnerability Assessment Committee (MVAC) is charged with conducting bi-annual vulnerability assessments that constitute the basis for humanitarian response (also known as the MVAC response).