{"id":1161,"date":"2019-06-16T21:39:29","date_gmt":"2019-06-16T21:39:29","guid":{"rendered":"http:\/\/wordpress.test\/measuring-household-resilience-using-high-frequency-data\/"},"modified":"2019-06-16T21:39:29","modified_gmt":"2019-06-16T21:39:29","slug":"measuring-household-resilience-using-high-frequency-data","status":"publish","type":"post","link":"https:\/\/globaldev.blog\/measuring-household-resilience-using-high-frequency-data\/","title":{"rendered":"Measuring household resilience using high-frequency data"},"content":{"rendered":"

High-frequency data collection at the level of households in developing countries offers the potential to measure their resilience and to act quickly in response to food shortages, disease outbreaks, and other adverse events. This column explains how such timeliness is crucial during a humanitarian emergency like the March 2019 floods in Malawi. By being proactive rather than reactive, these data can buffer vulnerable households against the effects of natural disasters.<\/strong><\/em><\/p>\n

In March 2019, Cyclone Idai slammed into southeastern Africa, killing over 1,000 people and affecting three million more. In Malawi, an estimated 81,000 people<\/a> were displaced by the cyclone-related flooding that affected the region.<\/p>\n

As humanitarian aid rushed in to assist those who were displaced, directing it required up-to-date data concerning these households. Where have they moved to? What is their health status? Do they have access to sufficient food?<\/p>\n

As it happens, timely updates were available via an established network of sentinel sites, providing timely updates on the impact of the flood on households\u2019 resilience and food security. Compiled in a widely disseminated one-pager<\/a>, the data highlighted how households affected by the floods were facing severe food shortages and reported an alarmingly high level of malaria incidence (see Figure 1).<\/p>\n

The data were drawn from the Measuring Indicators for Resilience Analysis (MIRA) protocol, a system of locally embedded enumerators collecting monthly data from representative households in order to measure resilience.<\/p>\n

<\/p>\n

Figure 1. Excerpt from a one-pager highlighting household food-insecurity after the 2019 Floods<\/p>\n

Conceptually, resilience sees a system as dynamic, shifting in response to external stimuli. Because the shocks and their effects on outcomes under study are uncertain, they are quantified in terms of uncertainty. Shocks are also interlocking: if a breadwinner loses his or her job and cannot afford care, household members may be more likely to get sick.<\/p>\n

Recent studies have sought to quantify resilience empirically<\/a>, building on the rich body of research on poverty measurement. This has prompted a call to develop a series of sentinel sites<\/a> in vulnerable communities to inform resilience-programming efforts.<\/p>\n

MIRA was jointly designed by the Monitoring, Evaluation, Accountability, and Learning (MEAL) unit within the Southern African Regional Office (SARO) of Catholic Relief Services (CRS) and the Charles H. Dyson School of Applied Economics and Management at Cornell University.<\/p>\n

MIRA was piloted as part of the USAID funded United in Building and Advancing Life Expectations (UBALE) project in southern Malawi. It was developed in response to multiple needs at the donor, project, and community levels, including:<\/p>\n