资源环境科技发展态势分析平台

Knowing how resilience changes in the aftermath of a shock is crucial to the targeting of effective humanitarian responses. Yet, heavy reliance on face-to-face household surveys often means that post-disaster evaluations of resilience are costly, time-consuming and difficult to coordinate. As a result, most quantitative assessments are either carried out via one-off snapshots or by combining surveys conducted years apart. Doing so severely restricts our understanding of the temporal dynamics of resilience, particularly as it relates to inter- and infra- annual fluctuations.

In this paper we examine how household's resilience to multi-hazard risk changes over time. To do so we combine two novel approaches. Firstly, we use a high-frequency mobile-phone panel survey to conduct remote interviews in Eastern Myanmar. Surveys took place every six weeks over a one-year period. Secondly, we adapt a self-evaluated subjective measure of resilience to allow it to be administered via mobile phone. Shortly after the first survey was conducted, monsoonal flooding affected the site, allowing for the effects of flood exposure on resilience to be compared over time.

Our findings reveal how self-evaluated levels of resilience fluctuate considerably over the course of a year. To probe the effects of the monsoon floods, we compare resilience scores between households directly and indirectly affected by flooding. Scores drop sharply for the first three months amongst directly affected households, before slowly converging up to a year later. We also compare the effects of flood exposure on different socio-economic groups, revealing how female-headed households are particularly affected in the aftermath of flooding. Insights from the study highlight the dangers of using one-off resilience surveys to measure resilience, and underscore the need for development actors to account for shorter-term changes in the design of resilience-building interventions. Lastly, our findings showcase the potential of methodological innovations in addressing many of the resource, time and logistical constraints of traditional resilience measurement practices.