Analyzing the Disaster Preparedness Capability of Local Government Using AHP: Zhengzhou 7.20 Rainstorm Disaster

Abstract

This study aimed to identify factors influencing disaster preparedness capability, measure and compare the relative importance of evaluation indicators of preparedness capability in a rainstorm disaster, and analyze the impact of these factors on disaster preparedness so as to improve disaster preparedness capability. The evaluation model was proposed by constructing the target level (the first level) as an indicator system; this was divided into four indicators (the second level): planning, organization, equipment, and education and exercise, and 14 tertiary evaluation indicators (the third level). The validity of the evaluation index system was demonstrated, and the weight of each level was calculated using the Analytic Hierarchical Process and expert survey methods, taking the example of the Zhengzhou “7.20” rainstorm to conduct an empirical analysis of the proposed model. The weak points of disaster preparedness capability were identified. The empirical analysis revealed that organization scored the highest, followed by planning, equipment, and education and exercise, indicating the lack of disaster management equipment and resources, disaster management training, and exercise and public emergency safety education. These results will help in future decision-making, as they provide a clear understanding of what needs to be done to improve disaster preparedness capability.

Exploring and Enhancing Community Disaster Resilience: Perspectives from Different Types of Communities

“…Due to its geographical location, it is subject to monsoons and rainfall all year round and often suffers from heavy rainfall and flooding [46]. In July 2021, Henan Province in China endured an exceptionally powerful rainstorm that lasted from 17 July to 23 July, triggering severe flooding [47]. As documented in the "Investigation Report of the '7.20' Extraordinary Rainstorm Disaster in Zhengzhou, Henan Province", this rainstorm was a natural disaster responsible for extensive property damage, casualties, and widespread flooding in both urban areas and rivers.…”

Spatial Modelling for Enhanced Disaster Preparedness by Mapping Evacuation Routes in Al-Hillah City

“…Evacuation will be different according to the density of people, road directions, type of danger and its causes, and also the degree of control on hazards caused by authorities that should be held according to an evacuation plan. (Relationships between evacuation population size, emergency shelter capacity, and the time to evacuation [26][27][28]. )…”

“…Network analysis in GIS to build a model that can be used for time-and length-based spatial analysis with network analysis, in addition to other information that can be added such as barriers, on lines and nods and collect more information as elevation, allowing us to retrieve information for spatial analysis, live flow, bridges, tunnels, overpasses and highways to support decision maker. In addition to the infrastructure network or service network, such as the water, gas, electricity, and other pipeline networks [27,29].…”

Assessment of disaster preparedness and related impact factors among emergency nurses in tertiary hospitals: descriptive cross-sectional study from Henan Province of China

“…For instance, in July 2021, Henan Province was struck by an extraordinarily heavy rainstorm that caused severe flooding, resulting in 352 deaths, 14.5 million population affected, and a cost of $16.5 billion ( 13 ). This sudden mega-disaster not only posed unprecedented challenges to disaster emergency management system but also exposed the poor disaster preparedness among municipal government, healthcare facilities and medical personnel ( 14 ). Considering the vital role of emergency nurses on the frontline of disasters response, the disaster preparedness of emergency nurses in Henan Province is of great concern.…”