Pub Date : 2020-07-01DOI: 10.2991/jracr.k.200709.002
Chongfu Huang
The COVID-19 outbreak was first reported in the city of Wuhan, central China’s Hubei Province, in December 2019. Experts have attributed the outbreak to a novel coronavirus that has since spread across China and abroad with confirmed cases exceeding 234,000 globally, death toll of coronavirus tops 11,000 [1], on March 21, 2020. The disease has been named “coronavirus disease 2019” (abbreviated “COVID-19”). When the disease started to spread in China, authorities reacted with historically unprecedented quarantines of cities. On February 27, 2020, the World Health Organization (WHO) raised the risk assessment of COVID-19 from “high” to “very high” at global level. However, the concept of the risk of COVID-19 is still unclear today, and risk communication is not smooth. Before the outbreak, information about the disease was incomplete and traditional risk analysis tools were unable to provide any support. Holding the hope that the virus does not pass from human to human, meanwhile some political considerations, people lost the opportunity to control the source of infection early, causing serious losses. If a more reliable risk analysis was carried out before and at the beginning of the outbreak, and if a strengthen crisis response was took immediately, the situation will certainly be much better. It is the same for almost all disasters, the story after the events is easy to tell, but the risk analysis before the events is not easy. One reason is that the information available for risk analysis before and at the beginning of the outbreak is incomplete.
{"title":"Analysis of Death Risk of COVID-19 under Incomplete Information1","authors":"Chongfu Huang","doi":"10.2991/jracr.k.200709.002","DOIUrl":"https://doi.org/10.2991/jracr.k.200709.002","url":null,"abstract":"The COVID-19 outbreak was first reported in the city of Wuhan, central China’s Hubei Province, in December 2019. Experts have attributed the outbreak to a novel coronavirus that has since spread across China and abroad with confirmed cases exceeding 234,000 globally, death toll of coronavirus tops 11,000 [1], on March 21, 2020. The disease has been named “coronavirus disease 2019” (abbreviated “COVID-19”). When the disease started to spread in China, authorities reacted with historically unprecedented quarantines of cities. On February 27, 2020, the World Health Organization (WHO) raised the risk assessment of COVID-19 from “high” to “very high” at global level. However, the concept of the risk of COVID-19 is still unclear today, and risk communication is not smooth. Before the outbreak, information about the disease was incomplete and traditional risk analysis tools were unable to provide any support. Holding the hope that the virus does not pass from human to human, meanwhile some political considerations, people lost the opportunity to control the source of infection early, causing serious losses. If a more reliable risk analysis was carried out before and at the beginning of the outbreak, and if a strengthen crisis response was took immediately, the situation will certainly be much better. It is the same for almost all disasters, the story after the events is easy to tell, but the risk analysis before the events is not easy. One reason is that the information available for risk analysis before and at the beginning of the outbreak is incomplete.","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"48 7","pages":"43-53"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72417664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.2991/jracr.k.200522.001
S. B. Malla, S. Hasegawa, R. Dahal
In the original article, there were mistakes in introduction section paragraph 11, paragraph 13, paragraph 14 and paragraph 15. These paragraphs contain wrong abbreviation ‘SKK’. The abbreviation should be ‘SSK’. The wrong abbreviation was also written in paragraph 1 of method section, table 1 and paragraph 2 of effect of rank and training in competition section, and paragraph 1 and 3 of discussion section. Similarly paragraph 11 and paragraph 15 of introduction section, and paragraph 1 of method of analysis section also contain wrong word ‘Nepali’. They should be replaced by word ‘Nepalese’. The corrected paragraphs and table are given below.
在原文中，引言部分第11段、第13段、第14段和第15段都有错误。这些段落包含错误的缩写“SKK”。缩写应该是“SSK”。在method section的第1段、table 1和second section的rank and training in competition section的effect，以及discussion section的第1段和第3段也写错了缩写。同样，引言部分的第11段和第15段以及分析方法部分的第1段也包含错误的“尼泊尔人”一词。应该用“尼泊尔人”这个词来代替。更正后的段落和表格如下。
{"title":"Corrigendum to “Competency of the Infantry Troops of the Nepalese Army in Disaster Response” [Journal of Risk Analysis and Crisis Response 9(2), (2019), 62–73]","authors":"S. B. Malla, S. Hasegawa, R. Dahal","doi":"10.2991/jracr.k.200522.001","DOIUrl":"https://doi.org/10.2991/jracr.k.200522.001","url":null,"abstract":"In the original article, there were mistakes in introduction section paragraph 11, paragraph 13, paragraph 14 and paragraph 15. These paragraphs contain wrong abbreviation ‘SKK’. The abbreviation should be ‘SSK’. The wrong abbreviation was also written in paragraph 1 of method section, table 1 and paragraph 2 of effect of rank and training in competition section, and paragraph 1 and 3 of discussion section. Similarly paragraph 11 and paragraph 15 of introduction section, and paragraph 1 of method of analysis section also contain wrong word ‘Nepali’. They should be replaced by word ‘Nepalese’. The corrected paragraphs and table are given below.","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"1 1","pages":"119-120"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76506742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.2991/jracr.k.200507.002
Panagiotis Ntzeremes, K. Kirytopoulos, V. Leopoulos
Although studies indicate the significant growth of maritime and the rise of intermodal transportation during the last decade, they also pinpoint that road transportation continues to hold the largest share in the transportation sector worldwide, having a considerable margin from the rest [1]. In that view, modern roads face the challenge to provide an adequate, intelligent as well as safe road network. Therefore, road infrastructure must be formed in order to cope with the arisen challenges. Although each part of the infrastructure should fulfill these challenges, special emphasis should be primarily given on its critical elements, such as tunnels [2].
{"title":"Discussing the Need to Manage Uncertainty Relating to Users in Road Tunnel Fire Risk Assessment","authors":"Panagiotis Ntzeremes, K. Kirytopoulos, V. Leopoulos","doi":"10.2991/jracr.k.200507.002","DOIUrl":"https://doi.org/10.2991/jracr.k.200507.002","url":null,"abstract":"Although studies indicate the significant growth of maritime and the rise of intermodal transportation during the last decade, they also pinpoint that road transportation continues to hold the largest share in the transportation sector worldwide, having a considerable margin from the rest [1]. In that view, modern roads face the challenge to provide an adequate, intelligent as well as safe road network. Therefore, road infrastructure must be formed in order to cope with the arisen challenges. Although each part of the infrastructure should fulfill these challenges, special emphasis should be primarily given on its critical elements, such as tunnels [2].","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"51 1","pages":"12-18"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90577121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-05-01DOI: 10.2991/jracr.k.200507.001
Xiaofeng Xie, Yang Yang, Jing Gu, Zongfang Zhou
{"title":"Research on the Contagion Mechanism of Associated Credit Risk in the Supply Chain","authors":"Xiaofeng Xie, Yang Yang, Jing Gu, Zongfang Zhou","doi":"10.2991/jracr.k.200507.001","DOIUrl":"https://doi.org/10.2991/jracr.k.200507.001","url":null,"abstract":"","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"25 1","pages":"19-22"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82288730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.2991/jracr.k.200421.002
清 Wu吴Qing
{"title":"Review the Parameters of Historical Strong Earthquakes in Tianshui and Its Surrounding Areas","authors":"清 Wu吴Qing","doi":"10.2991/jracr.k.200421.002","DOIUrl":"https://doi.org/10.2991/jracr.k.200421.002","url":null,"abstract":"","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"70 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74670943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.2991/jracr.k.200415.001
Xuan-hua Xu, Yushi Liu, Z. Zhang
With the increasingly prominent problem of global climate change, the frequency of all kinds of natural disasters is increasing, and the scope of impact is becoming wider and wider. According to the statistics of the civil affairs bureau, all kinds of natural disasters in China have caused 243,533 million disasters, 1583 deaths, 6017 million emergency relocation in 2014, and the direct economic losses have reached 337,38 billion yuan [1]. Natural disasters not only cause a large number of casualties and economic losses, but also cause varying degrees of psychological trauma to the affected people, which may affect individual behavior in the short-term or even in the long-term [2]. Many cases have shown that anxiety in disaster scenarios can urge the affected children to make some aggressive behaviors [3], these experiences of negative psychological behaviors will increase the difficulty of rescue and resettlement. If it is not alleviated in time and effectively, it will accumulate gradually, and easily turn into illegal behavior, or even evolve into group events [4] and reduce the stability and safety of society [5,6]. Behavior analysis of the disaster victims plays an important role in crisis management, disaster emergency response and implementation of evacuation plan [7], and is also one of the core scientific issues in emergency management of public emergencies [8]. Therefore, in order to rescue effectively and block the evolution and upgrading of individual events, and scientifically formulate rescue strategies after the disaster, it is necessary to deeply analyze the mutation mechanism of individual psychological behavior state of the affected people after natural disasters. Many researchers have studied the psychology and behavior of the people affected by climate change and natural disasters. Doherty and Clayton [9] analyzed three effects of climate change on people’s psychology: direct psychological impact (ASD or PTSD); indirect psychological impact (decreased wellbeing); social psychological impact (social conflict). Norris et al. [10] analyzed more than 160 empirical studies on disasters from 1981 to 2001 and found that the occurrence of nature disasters would bring people some shortor long-term psychological problems, such as specific psychological injury, mental and physical disorders. Aiming at whether there is a correlation between natural disasters and suicide behavior, Kõlves et al. [11] has analyzed the existing empirical studies and found that different types of natural disasters have different effects on suicide rate, and suicide rate is mainly affected by economic conditions. Hu et al. [12] believed that people had panic behavior in evacuation and temporary resettlement after the disaster, and panic behavior was infectious, which made more affected groups panic. Helbing et al. [13] also simulated the irrational panic escape behavior of groups under the emergency. Panic psychology and irrational behavior are easy to lead to s
随着全球气候变化问题的日益突出，各类自然灾害发生的频率越来越高，影响范围越来越广。据民政局统计，2014年全国各类自然灾害共造成灾害2435.33亿人次，死亡1583人，紧急搬迁6.017亿人次，直接经济损失337.38亿元。自然灾害不仅造成大量的人员伤亡和经济损失，还会给受灾群众造成不同程度的心理创伤，这些创伤可能在短期甚至长期内影响个人行为。许多案例表明，灾难场景中的焦虑会促使受灾儿童做出一些攻击行为，这些负面心理行为的经历会增加救援和安置的难度。如果得不到及时有效的缓解，就会逐渐积累，很容易演变为违法行为，甚至演变为群体性事件[4]，降低社会的稳定与安全[5,6]。灾害受害者行为分析在危机管理、灾害应急响应和疏散计划实施等方面发挥着重要作用，也是突发公共事件应急管理的核心科学问题之一。因此，为了有效地进行救援，阻断个体事件的演化升级，科学地制定灾后救援策略，有必要深入分析自然灾害后受灾人群个体心理行为状态的突变机制。许多研究人员研究了受气候变化和自然灾害影响的人们的心理和行为。Doherty和Clayton分析了气候变化对人们心理的三种影响:直接心理影响(ASD或PTSD);间接心理影响(幸福感下降);社会心理影响(社会冲突)。Norris et al. b[10]对1981 - 2001年的160多项灾害实证研究进行了分析，发现自然灾害的发生会给人们带来一些短期、长期的心理问题，如特定的心理伤害、身心障碍等。针对自然灾害与自杀行为之间是否存在相关性，Kõlves等人b[11]对已有的实证研究进行了分析，发现不同类型的自然灾害对自杀率的影响是不同的，而自杀率主要受经济条件的影响。Hu等人[12]认为灾后人们在疏散和临时安置中存在恐慌行为，并且恐慌行为具有传染性，使更多的受影响群体产生恐慌。Helbing等[13]也模拟了突发事件下群体的非理性恐慌逃离行为。在突发事件中，恐慌心理和非理性行为容易导致踩踏事件的发生，是增加生命财产损失的重要因素。此外，一些研究已经证明，人们有亲社会行为，并在灾难后表现出适应力。Bonanno et al.[15]通过问卷调查和多变量分析发现，心理弹性主要与受影响人群的收入、社会支持等因素有关。van der Linden [16]， Akerlof et al.[17]等研究者也采用实证方法探讨了自然灾害后风险感知与社会结构、经济等控制因素的相关性。这些研究为探讨受害者心理和行为状态的突变机制奠定了理论和实证基础。我想我可以把它放进去
{"title":"Study on Mutation Mechanism of Victim’s Psychological Behavior State after Major Natural Disasters","authors":"Xuan-hua Xu, Yushi Liu, Z. Zhang","doi":"10.2991/jracr.k.200415.001","DOIUrl":"https://doi.org/10.2991/jracr.k.200415.001","url":null,"abstract":"With the increasingly prominent problem of global climate change, the frequency of all kinds of natural disasters is increasing, and the scope of impact is becoming wider and wider. According to the statistics of the civil affairs bureau, all kinds of natural disasters in China have caused 243,533 million disasters, 1583 deaths, 6017 million emergency relocation in 2014, and the direct economic losses have reached 337,38 billion yuan [1]. Natural disasters not only cause a large number of casualties and economic losses, but also cause varying degrees of psychological trauma to the affected people, which may affect individual behavior in the short-term or even in the long-term [2]. Many cases have shown that anxiety in disaster scenarios can urge the affected children to make some aggressive behaviors [3], these experiences of negative psychological behaviors will increase the difficulty of rescue and resettlement. If it is not alleviated in time and effectively, it will accumulate gradually, and easily turn into illegal behavior, or even evolve into group events [4] and reduce the stability and safety of society [5,6]. Behavior analysis of the disaster victims plays an important role in crisis management, disaster emergency response and implementation of evacuation plan [7], and is also one of the core scientific issues in emergency management of public emergencies [8]. Therefore, in order to rescue effectively and block the evolution and upgrading of individual events, and scientifically formulate rescue strategies after the disaster, it is necessary to deeply analyze the mutation mechanism of individual psychological behavior state of the affected people after natural disasters. Many researchers have studied the psychology and behavior of the people affected by climate change and natural disasters. Doherty and Clayton [9] analyzed three effects of climate change on people’s psychology: direct psychological impact (ASD or PTSD); indirect psychological impact (decreased wellbeing); social psychological impact (social conflict). Norris et al. [10] analyzed more than 160 empirical studies on disasters from 1981 to 2001 and found that the occurrence of nature disasters would bring people some shortor long-term psychological problems, such as specific psychological injury, mental and physical disorders. Aiming at whether there is a correlation between natural disasters and suicide behavior, Kõlves et al. [11] has analyzed the existing empirical studies and found that different types of natural disasters have different effects on suicide rate, and suicide rate is mainly affected by economic conditions. Hu et al. [12] believed that people had panic behavior in evacuation and temporary resettlement after the disaster, and panic behavior was infectious, which made more affected groups panic. Helbing et al. [13] also simulated the irrational panic escape behavior of groups under the emergency. Panic psychology and irrational behavior are easy to lead to s","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"50 1","pages":"27-36"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79799095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.2991/jracr.k.200421.003
E. A. Shileche, P. Weke, T. Achia
Many businesses make profit yearly and tend to invest some of the profit so that they can cushion their organizations against any future unknown events that can affect their current profit making. Since future happenings in businesses cannot be predicted accurately, estimates are made using experience or past data which are not exact. The probability element (which is normally determined by experience or past data) is important in investment decision making process since it helps address the problem of uncertainty. Many of the investment decision making methods have incorporated the expectation and risk of an event in making investment decisions. Most of those that use risk account for diversifiable risk (non-systematic risk) only thus limiting the predictability element of these investment methods since total risk are not properly accounted for. A few of these methods include the certainty (probability) element. These include value at risk method which uses covariance matrices as total risk and the binning system which always assumes normal distribution and thus does not take care of discrete cases. Moreover comparison among various entities lacks since the probabilities derived are for individual entities and are just quantile values. Finite investment decision making using real market risk (non-diversifiable risk) was undertaken in this study. Non-diversifiable risk (systematic risk) estimates of a portfolio of stocks determined by a real risk weighted pricing model are used as initial data. The variance of non-diversifiable risk is estimated as a random variable referred to as random error (white noise). The estimator is used to calculate estimates of white noise (wn). A curve estimation of the wn is made using Kernel Density Estimation (KDE). KDE is a non-parametric way to estimate the probability density function of a random variable. KDE is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. This is used to derive probability estimates of the non-diversifiable risks of the various stocks. This enables determination of total risk with given probabilities of its occurrence thus facilitating decision making under risky and uncertain situations as well as accentuating comparison among the portfolio of stocks.
{"title":"Kernel Density Estimation of White Noise for Non-diversifiable Risk in Decision Making","authors":"E. A. Shileche, P. Weke, T. Achia","doi":"10.2991/jracr.k.200421.003","DOIUrl":"https://doi.org/10.2991/jracr.k.200421.003","url":null,"abstract":"Many businesses make profit yearly and tend to invest some of the profit so that they can cushion their organizations against any future unknown events that can affect their current profit making. Since future happenings in businesses cannot be predicted accurately, estimates are made using experience or past data which are not exact. The probability element (which is normally determined by experience or past data) is important in investment decision making process since it helps address the problem of uncertainty. Many of the investment decision making methods have incorporated the expectation and risk of an event in making investment decisions. Most of those that use risk account for diversifiable risk (non-systematic risk) only thus limiting the predictability element of these investment methods since total risk are not properly accounted for. A few of these methods include the certainty (probability) element. These include value at risk method which uses covariance matrices as total risk and the binning system which always assumes normal distribution and thus does not take care of discrete cases. Moreover comparison among various entities lacks since the probabilities derived are for individual entities and are just quantile values. Finite investment decision making using real market risk (non-diversifiable risk) was undertaken in this study. Non-diversifiable risk (systematic risk) estimates of a portfolio of stocks determined by a real risk weighted pricing model are used as initial data. The variance of non-diversifiable risk is estimated as a random variable referred to as random error (white noise). The estimator is used to calculate estimates of white noise (wn). A curve estimation of the wn is made using Kernel Density Estimation (KDE). KDE is a non-parametric way to estimate the probability density function of a random variable. KDE is a fundamental data smoothing problem where inferences about the population are made, based on a finite data sample. This is used to derive probability estimates of the non-diversifiable risks of the various stocks. This enables determination of total risk with given probabilities of its occurrence thus facilitating decision making under risky and uncertain situations as well as accentuating comparison among the portfolio of stocks.","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"128 1","pages":"6-11"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74505954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.2991/jracr.k.200421.001
未希 Weixi徐Xu, 选华 Xuanhua徐Xu
After the outbreak of new coronavirus pneumonia, all regions have responded to take measures. Emergency decision-making plays an important role, directly related to the safety of the people, and more deeply will affect the future of the country. In this paper, we try to use the wisdom of large groups which are distributed in the social network to deal with the relevant indicators of the group big data decision-making model under the maximum likelihood estimation of the complementary judgment matrix, to establish the epidemic risk assessment system of infectious diseases, and to realize the group decision-making and risk analysis based on the big data.
{"title":"Risk Analysis and Crisis Management of Novel Coronavirus COVID-19✩","authors":"未希 Weixi徐Xu, 选华 Xuanhua徐Xu","doi":"10.2991/jracr.k.200421.001","DOIUrl":"https://doi.org/10.2991/jracr.k.200421.001","url":null,"abstract":"After the outbreak of new coronavirus pneumonia, all regions have responded to take measures. Emergency decision-making plays an important role, directly related to the safety of the people, and more deeply will affect the future of the country. In this paper, we try to use the wisdom of large groups which are distributed in the social network to deal with the relevant indicators of the group big data decision-making model under the maximum likelihood estimation of the complementary judgment matrix, to establish the epidemic risk assessment system of infectious diseases, and to realize the group decision-making and risk analysis based on the big data.","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84465239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.2991/jracr.k.200415.002
L. Liu 刘
On February 2020, the Diamond Princess Cruise, which left Japan, was obliged to stay at sea for 14 days-quarantine after it was found that a Hong Kong passenger had been diagnosed SARS-COV2 pneumonia after disembarking. As a result shocked the world, an outbreak of infection occurred on board; the number of infected people increased rapidly; and about 20% of the population infected. Finally, the quarantine is completely failed and has to be ended officially. The crowd was evacuated back to their own country. The incident can be seen as an experimental model of virus infection in an independently enclosed building, showing powerful air-borne transmission of the virus to pass through public ventilation ducts and crevices in doors and windows. There have trend that no is immune; there have no racial differences and all world people are generally susceptible. The populations of asymptomatic recessive infection are large and are a dangerous infection source. The failure of closed quarantine indicates that evacuation is the best quarantine and protection. To sum up, mistake quarantine = forced infection; ineffective quarantine = condoning spreading; excessive quarantine = wasting resources. The only right way is to evacuate the infected immediately and disperse the uninfected quickly.
{"title":"The Diamond Princess Cruise: An Accidentally Experimental Model of COVID-19","authors":"L. Liu 刘","doi":"10.2991/jracr.k.200415.002","DOIUrl":"https://doi.org/10.2991/jracr.k.200415.002","url":null,"abstract":"On February 2020, the Diamond Princess Cruise, which left Japan, was obliged to stay at sea for 14 days-quarantine after it was found that a Hong Kong passenger had been diagnosed SARS-COV2 pneumonia after disembarking. As a result shocked the world, an outbreak of infection occurred on board; the number of infected people increased rapidly; and about 20% of the population infected. Finally, the quarantine is completely failed and has to be ended officially. The crowd was evacuated back to their own country. The incident can be seen as an experimental model of virus infection in an independently enclosed building, showing powerful air-borne transmission of the virus to pass through public ventilation ducts and crevices in doors and windows. There have trend that no is immune; there have no racial differences and all world people are generally susceptible. The populations of asymptomatic recessive infection are large and are a dangerous infection source. The failure of closed quarantine indicates that evacuation is the best quarantine and protection. To sum up, mistake quarantine = forced infection; ineffective quarantine = condoning spreading; excessive quarantine = wasting resources. The only right way is to evacuate the infected immediately and disperse the uninfected quickly.","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90969973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the continuous development of the social economy and the deepening of urbanization, large buildings are increasing, and disaster risks associated with large buildings, such as fire risks, are also increasing. Because of large buildings, such as shopping malls, business offices, transportation hubs buildings, high-rise commercial buildings are often crowded, it is essential in reducing fire casualties to guide people effectively in the buildings through the escape corridors, and to evacuate in a timely, rapid and efficient manner in the event of a fire. Therefore, in order to fully protect the safety of life and property, it is necessary to establish a fire protection intelligent guidance system. The research of intelligent guidance system for fire emergency evacuation in large buildings at home and abroad was reviewed in this paper. Three key problems of the fire detection, the evacuation path planning and the evacuation guidance design are presented. The development trend of the intelligent guidance system for fire emergency evacuation is discussed from two aspects, namely, the evacuation path planning methods and the guidance system hardware research.
{"title":"Summary of Intelligent Guidance System for Fire Emergency Evacuation in Large Buildings","authors":"孟. Xiangzhi相至Meng, 郭. Rongmei荣梅Guo, 胡. Xiaobing小兵Hu","doi":"10.2991/jracr.k.200117.003","DOIUrl":"https://doi.org/10.2991/jracr.k.200117.003","url":null,"abstract":"With the continuous development of the social economy and the deepening of urbanization, large buildings are increasing, and disaster risks associated with large buildings, such as fire risks, are also increasing. Because of large buildings, such as shopping malls, business offices, transportation hubs buildings, high-rise commercial buildings are often crowded, it is essential in reducing fire casualties to guide people effectively in the buildings through the escape corridors, and to evacuate in a timely, rapid and efficient manner in the event of a fire. Therefore, in order to fully protect the safety of life and property, it is necessary to establish a fire protection intelligent guidance system. The research of intelligent guidance system for fire emergency evacuation in large buildings at home and abroad was reviewed in this paper. Three key problems of the fire detection, the evacuation path planning and the evacuation guidance design are presented. The development trend of the intelligent guidance system for fire emergency evacuation is discussed from two aspects, namely, the evacuation path planning methods and the guidance system hardware research.","PeriodicalId":31887,"journal":{"name":"Journal of Risk Analysis and Crisis Response JRACR","volume":"52 1","pages":"194-202"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87984907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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