A composite inherent resilience index for Zimbabwe: An adaptation of the disaster resilience of place model

Building resilience to disasters has become a strategic goal of many risk reduction programs across the globe. This is because resilience ensures that communities develop capacities which prevent or minimise loses to disasters. In view of this, there is need to develop a baseline that tracks changes in resilience through time. This study responded to this gap in Zimbabwe by developing composite resilience indices (CRI) using 26 variables that reflected 5 subdomains of resilience: community capital, economic, infrastructure, social and health. The CRI were then used to map the spatial variation of resilience across 91 districts. The results show that the majority of the districts with below moderate resilience are mainly rural and marginalised, while the most resilient districts emerged in urban areas where service provision and infrastructure are better developed. These findings were further subjected to factor analyses which deconstructed the overall CRI and identified six latent factors behind resilience: infrastructure, health, household head, and income, access to maize and fortified food. These factors were mapped in a GIS environment to show their geographic variation in the country. Furthermore, Moran?s Index and the Getis Ord Gi* statistical tests were applied to determine clusters of resilience across space. Results confirmed the spatial clustering of CRI. The results are therefore, useful in planning mitigation, response and preparedness measures across the country.

Automated summary

This study developed a composite resilience index (CRI) to assess the resilience levels of 91 districts in Zimbabwe and found that districts with lower resilience levels are mainly rural and marginalized, while the most resilient districts are in urban areas with better service provision and infrastructure. Further factor analyses identified six latent factors behind resilience, which were mapped in a GIS environment to show their geographic variation in the country. The results confirmed spatial clustering of CRI and can be useful in planning mitigation, response, and preparedness measures across Zimbabwe.