Spatial quantification of community resilience in contexts where quantitative data are scarce: The case of Muzarabani district in Zimbabwe

Abstract

There has been an upsurge in tools for measuring resilience of the past decade. Despite this progress, we argue, there are few studies focusing on the spatial quantification of resilience in the context of multiple hazards, particularly in developing countries. Placing a particular emphasis on the contribution of geography to resilience studies, this paper examines the spatial variation of community resilience to disasters in Muzarabani, Zimbabwe. Place‐specific resilience variables are selected from the 2012 national census report to develop a disaster resilience index for Muzarabani district. A principal component analysis technique was used to analyse the overall and subcomponents of resilience to identify wards that needed policy intervention. Using the Geographical Information Systems tool to model the spatial variation of community resilience and its subcomponents, we found a geographic variation in community resilience across Muzarabani district, with the majority of the wards scoring low to below low levels of overall resilience. Although we view this study as being complementary to qualitative studies, it would appear quantifying and visualising resilience provide possible explanations and actions required for decision‐makers to address the resilience gaps and disaster risk reduction broadly.

Benchmarking Community Disaster Resilience in Nepal

“…Despite more than five decades of collective conceptual and research and experience, resilience is still a contested term that has mainly arisen from different epistemological orientations and subsequent methodological practices [9,10,21]. Subsequently, resilience does not have an internationally agreed-upon definition.…”

“…Various metrics have been developed in recent decades in order to evaluate different types and numerous interpretations of resilience. Mavhura and Manyena [10] listed 43 tools that were developed by academia and disaster practitioners under various categories, such as toolkits, models, indexes, scorecards, and policy guides to quantify resilience. However, resilience measures have primarily been a developed world phenomenon.…”

“…Conversely, developing countries have primarily focused on assessments of coping capacity to uncertainty and shocks. In developing countries, vulnerable populations are regularly exposed to the severity of natural hazards and disasters requiring less focus on resilience and a heavier emphasis on more immediate response and coping capacities [10]. Current resilience indices, both US-based and international, have been systematically reviewed and summarized by multiple scholars, including Asadzadeh, Kötter [31], Cutter [9], and Patel, Rogers [32].…”

“…Table 2 presents these indices, methodological approaches, study areas, domains, and indicators. Among the most prominent indices is the Baseline Resilience Index for Communities (BRIC) [6,10,11], a county-level index derived through an in-depth literature review linking community-specific disaster resilience measures to available datasets in the United States context. We chose to replicate BRIC methods because of the geospatial context that is inherent in the model as well as the latitude in indicator selection linking theory to the best measures that are available in Nepal.…”

“…Baseline resilience measurements can serve as a focal tool for formulating effective programs and policies prior to the hazard event occurrence. However, indicator selection requires careful consideration, ensuring a reliable reflection of the study area characteristics [10,11]. While various methods and measures have been used to examine and estimate community disaster resilience in the developed countries, very few models have been applied toward understanding disaster resilience in developing nations.…”