Fuzzy analytic hierarchy process-based safety assessment and resilience repair strategy of old district buildings

The growing importance of urban seismic resilience highlights the need for effective strategies to minimize earthquake-induced losses of building groups. Urban seismic capacity assessment requires rapid and accurate prediction of buildings’ seismic responses. However, in large urban building groups, the design information of many buildings is often difficult to obtain completely. In addition, post-earthquake interruption of economic activities will cause significant indirect losses to the city. Based on this background, this paper developed a convolutional neural network (CNN) model using structural characteristic parameters and ground motion parameters, by which the seismic response of structures in a building group can be rapidly predicted. On this basis, the repair priority of buildings was determined according to the repair efficiency value, and an optimal repair strategy considering indirect losses was proposed to minimize the post-earthquake indirect losses of building groups. Taking 908 buildings in Shanghai as an example, the effectiveness of the model is verified, and a comparison is made with the existing conventional repair strategies. Results showed that the proposed neural network accurately predicted the damage states of buildings. Compared with other existing strategies, the proposed optimal repair strategy effectively reduced the indirect economic loss. Further, the increased repair resources can reduce the indirect economic loss and repair time, but the reduction ratio decreases with the further increase of resource allocation.

River floods are common natural disasters that cause serious economic damage worldwide. In addition to direct economic damage, such as the destruction of physical assets, floods with long‐lasting inundation cause direct and indirect economic losses within and outside the affected area. Direct economic losses include loss of opportunity, due to interruption of business activities, and the costs associated with emergency measures such as cleaning, while indirect economic losses affect sectors within the trade and supply network. Few studies have explicitly estimated direct and indirect economic losses in several sectors, due to the difficulty of modeling inundation depth and period at finer scales. Here we developed a global modeling framework to estimate the direct and indirect economic losses associated with floods using a computable general equilibrium model and a global river and inundation model, which can simulate the flood extent, depth, and period. Application of the method to the 2011 Thailand flood demonstrated that the estimated economic losses due to business interruption in the industry and service sectors totaled $14.7 billion, which was about two thirds of the estimated direct economic damage caused by the flood ($22.0 billion). The estimated indirect economic losses reduced the gross domestic product of Thailand by 4.81% in 2011, without considering transboundary effects, and will cause more than 0.5% reduction in gross domestic product even in 2030, resulting in $55.3 billion of total losses from 2011 to 2030. Comprehensive estimation of direct and indirect economic losses facilitates understanding of various types of flood‐related economic risks during and after a flood.

Drought is an economically important hazard for many countries, with the potential to cause large direct and indirect economic losses. Superimposed on this risk is the danger that future anthropogenic climate change poses. The study utilises projected estimates of direct drought losses, for a variety of different climate change scenarios, to assess how input–output analysis could be used to estimate indirect losses. Modifications were made to the adaptive regional input–output model to consider both the severity of individual drought events and the propagation of economic losses over time and applied to a case study of Spain. The study highlights the importance of the distribution of drought severity and direct losses over time when modelling indirect losses, emphasising a need to focus on time steps shorter than a year to model losses more comprehensively. The results suggest that annual drought losses in 2003–2050 could be up to 32 % higher for short-term droughts if indirect economic losses were considered and 57 % higher for longer-term droughts. Indirect losses were shown to increase nonlinearly over time and as emission scenarios became more severe. This suggests that the benefits of stringent mitigation policies in terms of avoided indirect losses may be more substantial than for direct losses in the second half of the twenty-first century. Whilst the estimates presented here are considered illustrative, the study highlights the importance of considering indirect economic losses for providing more comprehensive economic estimates of drought loss under future climate change and for assessing economic benefits of future mitigation and adaptation strategies.

Over the past decade, numerous studies have estimated the economic impacts of a variety of disruptions. Most of these studies are based on macroeconomic models that quantify the direct and indirect economic losses from a disruption. Direct economic losses occur due to damaged facilities or when consumers change their purchasing behavior because of the disruption. Indirect economic losses occur when directly impacted businesses consequently reduce their orders to their suppliers. Indirect economic losses are often larger than direct economic losses. This paper compiles the results from these economic models in order to compare the costs of different disruptions and help decision makers prioritize among disruptions. We compare the direct and indirect economic losses from a variety of disruptions, including earthquakes, hurricanes, terrorist attacks, pandemic diseases, and port closures. Some studies model hypothetical scenarios, but other studies quantify the economic losses from historical events such as the September 11 attacks and the 2011 Japanese tsunami. This paper provides a useful benchmark to understand the consequences from disruptions and highlight areas that public officials could address in planning for future disruptions.

Objective: To provide scientific basis for the prevention and control of pneumoconiosis and the formulation of relevant policies, this paper discusses the loss of health life and economic loss caused by coal worker's pneumoconiosis in a mining group. Methods: From March to October 2017, 1262 cases of coal worker's pneumoconiosis were diagnosed in a mining group from 1972 to 2013. The direct and indirect economic losses are calculated by the step-by-step model method. Direct economic losses include medical expenses, one-time disability allowance, disability allowance, funeral allowance, one-time work death allowance, living and nursing expenses, food allowance, pension for supporting relatives and transportation expenses, etc. Indirect economic losses includes loss of social productivity, additional training fee for new employees, transportation fee for accompanying family members, loss of social productivity of accompanying family members, loss of production suspension and production reduction, etc. Life table method was used to calculate the loss of social productivity caused by coal worker's pneumoconiosis. Results: All 1262 coal worker's pneumoconiosis patients were male. In the stage of pneumoconiosis, 95.40% (1204/1262) of the first stage of pneumoconiosis and 42.62% (538/1262) of the seventh stage of disability. The age of diagnosis (22.02-71.33) was 47.38 years on average. 1262 coal worker's pneumoconiosis patients caused a total of 9068.54 years of health life loss, of which YLD accounted for 93.56% (8484.69/9068.54) . The loss of YLD (0.06-33.30) years in 1262 coal worker's pneumoconiosis patients was 6.70 years per capita. The total economic loss of 1262 coal workers with pneumoconiosis was 2842185447.70 yuan, with a per capita of 2252127.93 yuan. The direct economic loss accounted for 81.59% (2318990168.46/2842185447.70) , which was 4.42 times of the indirect economic loss. Among the direct economic loss per capita, medical expenses accounted for a large proportion of 50.04% (919510.84/1837551.64) . The per capita indirect economic loss is 414576.29 yuan. The loss of social productivity accounted for 56.18% (232908.95/414576.29) . Conclusion: Coal worker's pneumoconiosis causes heavy economic burden and serious loss of social productivity.

This paper aims to model the indirect economic loss due to damaged highway transportation systems in earthquake-affected areas that tends to be overlooked by decision-makers compared to direct economic loss that can be measured by repair or replacement cost. A regional Computable General Equilibrium (CGE) model is applied for estimating indirect economic loss in the whole economic system of the affected area. Shifang is a county-level city located in northwest Chengdu city, which is the capital of Sichuan Province, China. In the “5.12” Wenchuan earthquake, Shifang was one of the ten hardest-hit counties or cities and its highway transportation system was seriously damaged. It was selected as a case study to evaluate the indirect economic loss by seismic highway transportation system disruption. Results show that indirect economic loss accounted for nearly 36.4% of direct economic loss, which is as significant as direct economic loss resulting from earthquakedamaged highway transportation systems, and thus should be paid enough attention by decision-makers in pre-earthquake prevention and postearthquake recovery and reconstruction.

Quantifying total economic impacts of flood disaster in a timely manner is essential for flood risk management and sustainable economic growth. This study takes the flood disaster in China's Jiangxi province during the flood season in 2020 as an example, and exploits the input-output method to analyze indirect economic impacts caused by the agricultural direct economic loss. Based on regional IO data and MRIO data, a multi-dimensional econometric analysis was undertaken in terms of inter-regional, multi-regional, and structural decomposition of indirect economic losses. Our study reveals that the indirect economic losses caused by the agricultural sector in other sectors in Jiangxi province were 2.08 times the direct economic losses, of which the manufacturing sector suffered the worst, accounting for 70.11% of the total indirect economic losses. In addition, in terms of demand side and supply side indirect losses, the manufacturing and construction industries were found to be more vulnerable than other industries, and the flood disaster caused the largest indirect economic loss in eastern China. Besides, the supply side losses were significantly higher than the demand side losses, highlighting that the agricultural sector has strong spillover effects on the supply side. Moreover, based on the MRIO data of the years 2012 and 2015, dynamic structural decomposition analysis was undertaken, which showed that changes in the distributional structure appear to be influential in the evaluation of indirect economic losses. The findings highlight the spatial and sectoral heterogeneity of indirect economic losses caused by floods, and have significant implications for disaster mitigation and recovery strategies.

Quantitative assessment of economic losses from disasters can benefit government decision-making as well as mitigation and adaptation strategies. Here, we identified significant rainstorm events in China in 2021 using an objective identification method and investigated the direct economic losses (DELs) from each event. Then, a loss assessment model was developed to estimate the indirect economic losses (IDELs) from rainstorm events. We found that, in 2021, China experienced 36 major rainstorm events, causing approximately 179.8 billion yuan in DELs. The north of China was severely affected by rainstorms and floods, with Henan, Hebei and Shaanxi being the main loss centers. The assessment of IDELs based on rainstorm events showed a non-linear relationship between direct and indirect losses. The socio-economic impact of the 2021 Henan flood (Event No. 15) was the most serious, with direct and indirect losses of 125.8 billion yuan and 269.1 billion yuan, respectively. The primary industry in Henan was seriously affected, and the impact also spread to Inner Mongolia and Guangdong, causing indirect losses of 23.9 billion and 13.1 billion yuan, respectively. We recommend that the indirect losses resulting from such interregional trade linkages should be considered in catastrophe risk management. Finally, the sensitivity analysis showed that moderate overproduction can reduce the indirect impacts caused by disasters. A more detailed study is required to explore how to determine the appropriate levels of disaster relief, as well as a rational funding allocation mechanism.

An empirical method to estimate earthquake direct economic losses using building damages in high intensity area as a proxy

Abstract. The total losses caused by natural disasters have spatial heterogeneity due to the different economic development levels inside the disaster-hit areas. This paper uses scenarios of direct economic loss to introduce the sectors' losses caused by the 2008 Wenchuan earthquake (2008 WCE) in Beijing, utilizing the Adaptive Regional Input–Output (ARIO) model and the Inter-regional ripple effect (IRRE) model. The purpose is to assess the ripple effects of indirect economic loss and spatial heterogeneity of both direct and indirect economic loss at the scale of the smallest administrative divisions of China (streets, villages, and towns). The results indicate that the district of Beijing with the most severe indirect economic loss is the Chaoyang District; the finance and insurance industry (15, see Table 1) of Chaowai Street suffers the most in the Chaoyang District, which is 1.46 times that of its direct economic loss. During 2008–2014, the average annual GDP (gross domestic product) growth rate of Beijing was decreased 3.63 % by the catastrophe. Compared with the 8 % of GDP growth rate target, the decreasing GDP growth rate is a significant and noticeable economic impact, and it can be efficiently mitigated by increasing rescue effort and by supporting the industries which are located in the seriously damaged regions.

Abstract. Indirect seismic economic loss not only impacts regional economic recovery policies but is also related to economic assistance at the national level. Due to cross-regional economic activities and the difficulty of obtaining data, it is difficult for the indirect economic loss survey to cover all economic activities. However, nighttime light in an area can reflect the economic activity of the region. This article focuses on the indirect economic losses caused by the 2008 Wenchuan earthquake and evaluation of the progress of restoration and reconstruction based on nighttime light images. First, the functional relationship between GDP and nighttime light parameters is established based on pre-earthquake data. Next, the indirect loss of the earthquake is evaluated by the nighttime light attenuation in the disaster area after the earthquake. Then, the capacity recovery, which is characterized by the brightness recovery process of the light area, is evaluated. Lastly, the process of light expansion in the disaster area is analyzed to evaluate the speed and efficiency of economic expansion.

Optimizing the allocation schemes of post-disaster recovery resources can promote the sustainable development of a regional economy. However, previous studies determined the inputs and allocation schemes of recovery resources based on direct economic (DE) loss while neglecting indirect economic (IDE) loss, which restricted economic recovery. This study considered DE and IDE loss, and used a dynamic disastrous computable general equilibrium (CGE) model to simulate multiple scenarios with different inputs and allocation schemes to identify a better economic recovery strategy. Taking Super Typhoon Mangkhut’s landing in Guangdong Province in 2018 as an example, the results showed that the IDE loss had a long-term impact and dynamic accumulation without post-disaster recovery, reaching 15.25 times the DE loss by 2022. In the baseline scenario, the recovery resource inputs, including relief funds, reconstruction funds, and natural disaster commercial insurance, were limited, leading to a cumulative loss recovery rate of less than 2% in 2018–2022. According to our findings, recovery resources needed a 15-fold increase to recover to pre-disaster levels. Considering the impacts of sector connections on IDE loss, six allocation schemes were established based on DE loss, IDE loss, and industrial structure. Compared with the typical allocation scheme based on DE loss, allocating recovery resources according to the diffusion coefficient substantially improved the loss recovery rate and recovery resource utilization efficiency. The dynamic disastrous CGE model conducted multi-scenario simulations to identify the optimal recovery resource allocation scheme that supported rapid and efficient post-disaster economic recovery.

Investigating the role of refining urban flood direct loss in enhancing the accuracy of indirect economic loss assessment

Objective: To investigate the current status of disease burden and its influencing factors among welder's pneumoconiosis patients, and provide scientific basis for taking targeted intervention measures. Methods: From June 2022 to June 2023, the patients with welder's pneumoconiosis in Jiangsu Province were selected from 1956 to 2020 as the research objects, and disability adjusted life years (DALY) were used as the comprehensive index to study the disease burden. The direct and indirect economic losses caused by the diseases were calculated, and the factors affecting the disease burden were discussed by multiple linear regression method. Results: A total of 974 cases of welder's pneumoconiosis were reported in Jiangsu Province, the cumulative loss of DALY was 6300.73 person-years, and the per capita loss was 6.47 person-years. Among them, the healthy life years lost due to disability (YLD) was 6156.50 person-years (97.71%) , and the healthy life years lost due to premature death (YLL) was 144.23 person-years (2.29%) . Multiple linear regression analysis showed that the main factors affecting DALY were disability grade, diagnostic age, pneumoconiosis grade and length of dust exposure (P<0.05) . The total economic loss caused by 974 welder's pneumoconiosis patients was 1831838160.18 yuan, and the per capita loss was 1880737.33 yuan. Among them, the direct economic loss was 970917563.75 yuan (53.00%) , and the indirect economic loss was 860920596.43 yuan (47.00%) . Conclusion: Welder's pneumoconiosis causes serious disease burden to patients, and at the same time causes huge economic losses to individuals and society, which seriously hinders the development of society. Taking effective control measures to prevent the incidence of welder's pneumoconiosis is the key to reduce the disease burden.

The United States Army Corps of Engineers’ Hydrologic Engineering Center developed the HEC-FIA (Flood Impact Analysis) software to assist in the estimation of consequences with uncertainty. By estimating the consequences, the benefits of existing and future flood risk management measures can be evaluated and compared.HEC-FIA utilizes geospatial datasets to help users build structure inventories and assign values and population per structure. Using this information and geospatially derived flood depth grids (provided by most hydraulic models), HEC-FIA estimates direct economic, indirect economic, agricultural, and life loss consequences for flood hazards. HEC-FIA can compute results for a single event in either deterministic mode or in uncertainty mode which utilizes a Monte Carlo approach. The user can define the uncertainties about any structure in the floodplain in many ways, and each has various impacts on the different consequence calculations. For example, foundation heights, structure values, and depth-damage relationships impact economic consequences, while foundation heights, warning issuance times, and fatality rates impact the life loss calculations. All of these parameters can be defined with uncertainty. HEC-FIA can also be linked into HEC-WAT (Watershed Analysis Tool) with the FRA (Flood Risk Analysis) compute option to randomize the hydraulic events being evaluated in HEC-FIA so that hydrologic, hydraulic, geotechnical, and economic uncertainties can all be represented and evaluated by alternative within the floodplain.This paper will describe how HEC-FIA can be utilized to help evaluate the indirect economic consequences for various alternatives within a floodplain. The computational methods for indirect economic losses utilize a Computable General Equilibrium model to describe the secondary and tertiary impacts of loss of service, loss of laborers, and reductions in demand for intermediary goods.