Maturity model for evaluating disaster and humanitarian operations

PurposeThis paper proposes a maturity model (MM) for assessing disaster operations and identifying strategies for organisations to evolve their maturity stages.Design/methodology/approachThis study applies a systematic literature review to identify state-of-the-art work related to maturity models for disaster operations. In addition, the study develops a case study to validate the proposed maturity model in a generic scenario and two real-life scenarios.FindingsThe analysis of 158 papers in the literature resulted in identifying 8 maturity models for disaster operations. Based on their structure, the authors proposed a new model with five maturity stages suitable for any of the four phases of the disaster life cycle (i.e. mitigation, preparedness, response and recovery). In addition, the research identified and presents 24 strategies for improving disaster operations according to each maturity stage transition. Finally, the research presents a case study that evaluates the disaster response operations from a Civil Defense organisation considering a response scenario disaster in general, a flood scenario, and the COVID-19 pandemic scenario.Originality/valueThis study provides the following three main contributions useful for academics and practitioners in the disaster operations area: a new maturity model for assessing disaster operations, a strategy guide for improving disaster operations based on a maturity evolution and an empirical study exploring the approximation between academia and professionals involved in real-life disaster operations management.

An AI/ML-Based Strategy for Disaster Response and Evacuation of Victims in Aged Care Facilities in the Hawkesbury-Nepean Valley: A Perspective

The Hawkesbury-Nepean Valley, Australia’s longest coastal catchment, is spanned by a river system of more than 470 km, that runs from Goulburn to Broken Bay, covering a total area of over 2.2 million hectares. This region has remained prone to flood events, with considerable mortalities, economic impacts and infrastructural losses occurring quite regularly. The topography, naturally variable climatic conditions and the ‘bathtub’ effect in the region are responsible for the frequent flood events. In response, the Government at the national/federal, state and local level has focused on the design of efficient flood risk management strategies with appropriate evacuation plans for vulnerable communities from hospitals, schools, childcare and aged care facilities during a flood event. Despite these overarching plans, specialized response and evacuation plans for aged care facilities are critical to reducing the loss incurred by flood events in the region. This is the focus of this present paper, which reviews the history of flood events and responses to them, before examining the utilization of artificial intelligence (AI) techniques during flood events to overcome the flood risks. An early flood warning system, based on AI/Machine Learning (ML) strategy is being suggested for a timely decision, enhanced disaster prediction, assessment and response necessary to overcome the flood risks associated with aged care facilities within the Hawkesbury-Nepean region. A framework entailing AI/ML methods for identifying the safest route to the destination using UAV and path planning has been proposed for timely disaster response and evacuation of the residents of aged care facilities.

Detecting Natural Hazard-Related Disaster Impacts with Social Media Analytics: The Case of Australian States and Territories

Natural hazard-related disasters are disruptive events with significant impact on people, communities, buildings, infrastructure, animals, agriculture, and environmental assets. The exponentially increasing anthropogenic activities on the planet have aggregated the climate change and consequently increased the frequency and severity of these natural hazard-related disasters, and consequential damages in cities. The digital technological advancements, such as monitoring systems based on fusion of sensors and machine learning, in early detection, warning and disaster response systems are being implemented as part of the disaster management practice in many countries and presented useful results. Along with these promising technologies, crowdsourced social media disaster big data analytics has also started to be utilized. This study aims to form an understanding of how social media analytics can be utilized to assist government authorities in estimating the damages linked to natural hazard-related disaster impacts on urban centers in the age of climate change. To this end, this study analyzes crowdsourced disaster big data from Twitter users in the testbed case study of Australian states and territories. The methodological approach of this study employs the social media analytics method and conducts sentiment and content analyses of location-based Twitter messages (n = 131,673) from Australia. The study informs authorities on an innovative way to analyze the geographic distribution, occurrence frequency of various disasters and their damages based on the geo-tweets analysis.

Falling Apart and Coming Together: How Public Perceptions of Leadership Change in Response to Natural Disasters vs. Health Crises

Responding to disruptions and crises are challenges public leaders face as they strive to lead responsibly for the good of the community. The last two years have been especially challenging for public leaders and institutions. In Australia, the federal government battled natural disasters (bushfires) and COVID-19 within the span of only a few months, beginning in late 2019. These events provided the opportunity for a natural experiment to explore public perceptions of leadership in times of crises, with both a natural disaster and health crisis in quick succession. In this study, we develop, validate, and test a scale of perceptions of leadership for the greater good, the Australian Leadership Index, throughout different crisis contexts. We hypothesize and find support for the drivers of perceptions of public leadership and shifts in these perceptions as a function of the bushfire disaster response, a negative shift, and the initial COVID-19 response, a positive shift. Comparisons of the crisis periods against a period of relative stability are made. We discuss the implications of differential media coverage, how the crises were managed, and the resulting public perceptions of leadership for the greater good.

The importance of social work roles in disaster risk management in Zimbabwe

This study was aimed at exploring the efficacy of social work roles in disaster risk management in Zimbabwe in the face of climatic changes. It was carried out in Binga district, Matebeleland-North province using the qualitative methodology and a case study design. The study sample was comprised of 8 practicing social workers. Snowballing and purposive sampling techniques were used to select these participants. Data were collected through in-depth interviews using an interview guide. Thematic content analysis was employed to analyze the collected data. It was found that social workers play essential roles before, during and after disasters. On disaster preparedness, it was established that social workers assume roles of educators, community workers and disaster planners. Moreover, it was found that they play the roles of case managers, administrators of social protection and counselors during the disaster response phase of disaster risk management. Subsequently they also act as advocates, development facilitators as well as monitoring and evaluation personnel in the disaster recovery phase. As per the findings, the study recommends that social workers be recognized as essential in disaster risk management at both policy and practice level. Further, there is need to enhance social work training education for flexibility and contextual application of social work knowledge in the field of disaster risk management for quality realization of green social work in Zimbabwe.

When It Strikes, Are We Ready? Lessons Identified at the 7th Planetary Defense Conference in Preparing for a Near-Earth Object Impact Scenario

Near-Earth object (NEO) impact is one of the examples of high impact and low probability (HILP) event, same as the Covid-19 pandemic the world faces since the beginning of 2020. The 7th Planetary Defense Conference held by the International Academy of Astronautics (IAA) in April 2021 included an exercise on a hypothetical NEO impact event, allowing the planetary defense community to discuss potential responses. Over the span of the 4-day conference this exercise connected disaster response and management professionals to participate in a series of panels, providing feedback and perspective on the unfolding crisis scenario. The hypothetical but realistic asteroid threat scenario illustrated how such a short-warning threat might evolve. The scenario utilized during the conference indicates a need to prepare now for what might come in the future, because even with advance notice, preparation time might be minimal. This scenario chose Europe for the impact, which may likely cope with such a disaster, through the Union Civil Protection Mechanism (UCPM) and other solidarity and support mechanisms within the European Union (EU), as well as with potential support from international partners. This short article raises concern about other areas in the world on how they may access NEO impact information and cope with such disasters. It also provides an idea on vast scale of such disaster vis-à-vis the current capacity of response systems to cope with a larger event in Europe or elsewhere. This scenario showed that planetary defense is a global endeavor. Constant engagement of the planetary defense and disaster response communities is essential in order to keep the world safe from potential disasters caused by NEO impacts.