Esmeralda Paupério

A framework to assess quality and uncertainty in disaster loss data

There is a growing interest in the systematic and consistent collection of disaster loss data for different applications. Therefore, the collected data must follow a set of technical requirements to guarantee its usefulness. One of those requirements is the availability of a measure of the uncertainty in the collected data to express its quality for a given purpose. Many of the existing disaster loss databases do not provide such uncertainty/quality measures due to the lack of a simple and consistent approach to express uncertainty. After reviewing existing literature on the subject, a framework to express the uncertainty in disaster loss data is proposed. This framework builds on an existing uncertainty classification that was updated and combined with an existing method for data characterization. The proposed approach is able to establish a global score that reflects the overall uncertainty in a certain loss indicator and provides a measure of its quality.