scholarly journals Evaluation of Economic Loss of 2018/2019 African Swine Fever outbreaks in China

2021 ◽  
Author(s):  
Shibing You ◽  
Tingyi Liu ◽  
Miao Zhang ◽  
Xue Zhao ◽  
Bi Wu ◽  
...  
Keyword(s):  
Evaluation System ◽  
African Swine Fever ◽  
Economic Loss ◽  
Economic Losses ◽  
Swine Industry ◽  
Indicator Method ◽  
Economic Shock ◽  
Direct Economic Loss ◽  
Indirect Economic Loss ◽  
The Cost

Abstract This study evaluates the total economic loss due to the outbreaks of African Swine Fever (ASF) in China between August 2018 and July 2019. We propose a systematic framework to assess both the direct economic loss on the Chinses breeding industry and indirect economic loss on other sectors. Our evaluation system integrates various statistical analysis methods by applying the cost-loss model and substitution indicator method to calculate direct economic losses and using input-output (IO) model to estimate indirect economic losses. The proposed method provides an innovative and commonly applicable way to deal with the missing data that needs to be adjusted and repaired to be used for economic shock evaluation. We find that total economic loss caused by ASF is 224.768 billion yuan consisting of 99.042 billion yuan direct economic loss of the breeding industry and 125.726 billion yuan indirect economic loss of other industries. Our findings suggest that the overall impact of ASF on China's national economy is relatively small, mainly local and short-term impacts on the swine industry.

Research on Evaluation Models and Empirical Analysis of Earthquake Disaster Losses in China

2012 ◽  
Vol 67 (10-11) ◽  
pp. 534-544 ◽  
Author(s):  
Kepei Men ◽  
Lei Cui
Keyword(s):  
Economic Effect ◽  
Principal Component ◽  
Economic Loss ◽  
Economic Losses ◽  
Research On Evaluation ◽  
Earthquake Losses ◽  
Grey Clustering ◽  
Kolmogorov Smirnov ◽  
Direct Economic Loss ◽  
Indirect Economic Loss

Earthquake disasters occurred very frequently in China. As a result, to evaluate the losses has important social value and economic effect. This paper focuses on the assessment of economic losses of earthquake disasters which is divided into two parts: direct economic loss and indirect economic loss. First, the Kolmogorov-Smirnov (KS) test is used to determine the distribution of the earthquake losses per year in China, fitting the frequency of earthquake that happened per month in China. Second, the grey clustering method and principal component analysis (PCA) are applied, respectively, for direct economic loss rating and indirect economic loss rating. Finally, the economic loss generated by the earthquakes which happened from 2006 to 2009 in China is evaluated, and eight earthquakes are rated based on the comprehensive economic loss.

scholarly journals Assessment of the ripple effects and spatial heterogeneity of total losses in the capital of China after a great catastrophic shock

2017 ◽  
Vol 17 (3) ◽  
pp. 367-379 ◽  
Author(s):  
Zhengtao Zhang ◽  
Ning Li ◽  
Wei Xie ◽  
Yu Liu ◽  
Jieling Feng ◽  
...  
Keyword(s):  
Growth Rate ◽  
Spatial Heterogeneity ◽  
Economic Loss ◽  
Gdp Growth ◽  
Ripple Effect ◽  
Ripple Effects ◽  
Gdp Growth Rate ◽  
Direct Economic Loss ◽  
Indirect Economic Loss ◽  
Development Levels

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.

scholarly journals Risk of African swine fever virus introduction into the United States through smuggling of pork in air passenger luggage

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Cristina Jurado ◽  
Lina Mur ◽  
María Sol Pérez Aguirreburualde ◽  
Estefanía Cadenas-Fernández ◽  
Beatriz Martínez-López ◽  
...  
Keyword(s):  
Western Europe ◽  
African Swine Fever Virus ◽  
African Swine Fever ◽  
The United States ◽  
Economic Losses ◽  
Swine Industry ◽  
Virus Surveillance ◽  
Global Epidemiology ◽  
The Us ◽  
Mean Risk

Abstract African swine fever causes substantial economic losses in the swine industry in affected countries. Traditionally confined to Africa with only occasional incursions into other regions, ASF began spreading into Caucasian countries and Eastern Europe in 2007, followed by Western Europe and Asia in 2018. Such a dramatic change in the global epidemiology of ASF has resulted in concerns that the disease may continue to spread into disease-free regions such as the US. In this study, we estimated the risk of introduction of ASF virus into the US through smuggling of pork in air passenger luggage. Results suggest that the mean risk of ASFV introduction into the US via this route has increased by 183.33% from the risk estimated before the disease had spread into Western Europe or Asia. Most of the risk (67.68%) was associated with flights originating from China and Hong Kong, followed by the Russian Federation (26.92%). Five US airports accounted for >90% of the risk. Results here will help to inform decisions related to the design of ASF virus surveillance strategies in the US.

scholarly journals Genetic characterisation of African swine fever virus from 2017 outbreaks in Zambia: Identification of p72 genotype II variants in domestic pigs

2018 ◽  
Vol 85 (1) ◽  
Author(s):  
Edgar Simulundu ◽  
Yona Sinkala ◽  
Herman M. Chambaro ◽  
Andrew Chinyemba ◽  
Frank Banda ◽  
...  
Keyword(s):  
African Swine Fever Virus ◽  
African Swine Fever ◽  
Variable Region ◽  
Economic Losses ◽  
African Region ◽  
Swine Industry ◽  
African Countries ◽  
Central Variable Region ◽  
Close Relationship ◽  
Haemorrhagic Disease

African swine fever (ASF) is a contagious haemorrhagic disease associated with causing heavy economic losses to the swine industry in many African countries. In 2017, Zambia experienced ASF outbreaks in Mbala District (Northern province) and for the first time in Isoka and Chinsali districts (Muchinga province). Meanwhile, another outbreak was observed in Chipata District (Eastern province). Genetic analysis of part of the B646L gene, E183L gene, CP204L gene and the central variable region of the B602L gene of ASF virus (ASFV) associated with the outbreaks in Mbala and Chipata districts was conducted. The results revealed that the ASFV detected in Mbala District was highly similar to that of the Georgia 2007/1 isolate across all the genome regions analysed. In contrast, while showing close relationship with the Georgia 2007/1 virus in the B646L gene, the ASFV detected in Chipata District showed remarkable genetic variation in the rest of the genes analysed. These results suggest that the Georgia 2007/1-like virus could be more diverse than what was previously thought, underscoring the need of continued surveillance and monitoring of ASFVs within the south-eastern African region to better understand their epidemiology and the relationships between outbreaks and their possible origin.

scholarly journals Indirect Economic Loss Estimation due to Seismic Highway Transportation System Disruption in “5.12” Wenchuan Earthquake

2013 ◽  
Vol 8 (5) ◽  
pp. 1018-1024 ◽  
Author(s):  
Yan Shi ◽  
◽  
Shaoyu Wang
Keyword(s):  
Wenchuan Earthquake ◽  
Computable General Equilibrium ◽  
Economic Loss ◽  
Transportation System ◽  
Transportation Systems ◽  
Decision Makers ◽  
Highway Transportation ◽  
5.12 Wenchuan Earthquake ◽  
Direct Economic Loss ◽  
Indirect Economic Loss

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.

scholarly journals Assessment of ripple effect and spatial heterogeneity of total losses in the capital of China after a great catastrophe shocks

2016 ◽  
Author(s):  
Zhengtao Zhang ◽  
Ning Li ◽  
Wei Xie ◽  
Yu Liu ◽  
Jieling Feng ◽  
...  
Keyword(s):  
Growth Rate ◽  
Spatial Heterogeneity ◽  
Insurance Industry ◽  
Economic Loss ◽  
Gdp Growth ◽  
Ripple Effect ◽  
2008 Wenchuan Earthquake ◽  
Gdp Growth Rate ◽  
Direct Economic Loss ◽  
Indirect Economic Loss

Abstract. The total losses caused by natural disaster have spatial heterogeneity due to different economic development level inside the disaster-hit areas. This paper set the scenarios of direct economic loss to introduce the sectors' loss caused by 2008 Wenchuan earthquake into Beijing, utilized Adaptive Regional Input–Output (ARIO) model and 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 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 Chaoyang district; Finance & Insurance industry (#15) of Chaowai Street suffers the most in Chaoyang district, which is 1.46 times of its direct economic loss. During 2008–2014, the average annual GDP growth rate of Beijing could be decreased 3.63 % affected 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 reduced by increasing rescue effort and priority supporting the industries which are located in the seriously damaged regions.

Study on Urban Emergency Event Forecast - Taking Urban Traffic Accident in China as Example

2013 ◽  
Vol 734-737 ◽  
pp. 1629-1636
Author(s):  
Di Lu ◽  
Yao Wu Wang ◽  
Xiang Fei Niu
Keyword(s):  
Traffic Accident ◽  
Economic Loss ◽  
Urban Traffic ◽  
Economic Losses ◽  
Catastrophe Model ◽  
Emergency Event ◽  
Population Potential ◽  
Emergency Events ◽  
Direct Economic Loss ◽  
Urban Emergency Events

In China, with the accelerated urbanization and the rapid growth of urban population, potential urban emergency risk factors gradually increased. Therefore, how to forecast the urban emergency events seems to be important. This study elaborated the mechanism of catastrophe theory and grey forecast method, established the grey cusp catastrophe model according to further research. An empirical analysis on Chinese urban traffic accident forecast was made by this model through four indicators: the number of occurrences, the number of deaths, the number of people injured and direct economic losses. By operating the model with data from 2002 to 2006, the accuracy is verified. Based on data from 2002 to 2011, the model result shows that the next traffic accident occurrence catastrophe will occur in 2015-2016, the next death number catastrophe will occur in 2012-2013, the next injured number catastrophe will occur in 2018-2019, the next direct economic loss catastrophe will occur in 2014-2015.

Study on the Evaluation Models of Direct Economic Losses in Urban Flood Disasters

2012 ◽  
Vol 433-440 ◽  
pp. 4878-4882
Author(s):  
De Cai Kong ◽  
Feng Ping Wu
Keyword(s):  
Loss Rate ◽  
Economic Loss ◽  
Economic Losses ◽  
Urban Flood ◽  
General Process ◽  
Evaluation Models ◽  
Direct Economic Loss ◽  
Direct Economic Losses ◽  
Disaster System

Based on disaster system theory, flood risk assessment was conducted in regard to natural properties of hazard and environment as well as socioeconomics of hazard-affected bodies. The general process of economic loss evaluation in flood was consisted of two parts, namely the evaluation of pre-disaster value of hazard-affected bodies and the determination of direct economic loss rate in the flood disaster. At last, the evaluation models of direct economic losses in urban flood were established.

scholarly journals Evaluation on the Meteorological Service for Mitigating the Severe Impacts of Typhoon Rammasun

2021 ◽  
Vol 14 ◽  
pp. 194008292199266
Author(s):  
Yingjie Liu ◽  
Bingwei Cui ◽  
William D. Batchelor ◽  
Chenyi Zhang
Keyword(s):  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Economic Loss ◽  
Assessment Method ◽  
Economic Benefits ◽  
Disaster Prevention ◽  
Total Investment ◽  
Output Ratio ◽  
Direct Economic Loss ◽  
The Cost

This study takes the meteorological service of super typhoon Rammasun as an example, and proposes a multi-dimensional quantitative assessment method for meteorological service. Rammasun was the strongest typhoon that landed in China from 1949 to 2019. It hit the coastal areas of China three times, with a rare landing intensity in history. Guangdong, Guangxi, Hainan, Yunnan and other provinces have suffered disasters of varying degrees, with a total affected population of 12.084 million and a direct economic loss of 44.89 billion CNY. During this period, the total investment in meteorological services was approximately 1.213 billion CNY, and the economic benefits of disaster prevention and mitigation in the four disaster-stricken provinces were worth 16.1 billion CNY. According to the cost-benefit analysis of economics, the input-output ratio for disaster prevention and mitigation in Typhoon Rammasun was 1:13.

scholarly journals Wind and Rain Losses for Metal-clad Contemporary Houses Subjected to Non-cyclonic Windstorms

2020 ◽  
Author(s):  
Hao Qin
Keyword(s):  
Risk Assessment ◽  
Damage Assessment ◽  
Economic Loss ◽  
Wind Damage ◽  
Mitigation Measures ◽  
Economic Losses ◽  
Extreme Wind ◽  
Loss Modelling ◽  
The Cost ◽  
Extreme Winds

Severe windstorms cause millions in losses annually for housing in Southeast Australia that has more than half of Australia’s population. The risk assessment for housing in these non-cyclonic regions is the key to assessing the cost-effectiveness of relevant wind mitigation measures to reduce the economic losses. This study develops a probabilistic risk assessment framework to evaluate the wind and rain losses for Australian contemporary houses subjected to non-cyclonic windstorms, which integrates the hazard modelling for extreme wind and associated rainfall, reliability-based wind damage assessment, rainwater intrusion evaluation and economic loss modelling. The risk analysis was conducted for metal-clad contemporary houses in Brisbane and Melbourne. It was found that damage to building interior and contents 18 caused by rainwater intrusion associated with extreme winds is the major contributor to the annual expected economic losses, and houses in Brisbane are generally subjected to higher losses than houses in Melbourne.

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