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Saini Yang
State Key Laboratory of Earth Surface Processes and Resources Ecology, Beijing Normal University, Beijing, China

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Original paper
Published: 21 August 2021 in Natural Hazards
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With worsening global climate change, we still do not fully understand how to cope with possible extreme precipitation events or secondary disasters on highway networks. Correctly estimating the impact on the highway network from extreme precipitation plays a vital role in decision making regarding future highway investment. This study uses datasets from 21 NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) under the RCP (Representative Concentration Pathway) 4.5 and RCP8.5 scenarios. We use the percentile method to select the extreme precipitation threshold. A set of system performance measures for an impact analysis of Chinese highways under different scenarios is developed from the perspectives of physical exposure, network function and sensitivity analyses for high-impact areas in China. The results show that the intensity of extreme precipitation will increase in the future. More than 10,000 km and at least 4,000 intersections will be affected by extreme precipitation in 2030 and 2050. Based on a functional analysis of the highway network in Guangdong and Guangxi, more than 80% of the mileage of highways in Guangdong and Guangxi will be exposed to extreme precipitation. The network function of Chinese highways will dramatically decrease when precipitation reaches a critical value, which will shed light on highway fortification standards and planning.

ACS Style

Liang Jia; Saini Yang; Weiping Wang; Xinlong Zhang. Impact analysis of highways in China under future extreme precipitation. Natural Hazards 2021, 1 -17.

AMA Style

Liang Jia, Saini Yang, Weiping Wang, Xinlong Zhang. Impact analysis of highways in China under future extreme precipitation. Natural Hazards. 2021; ():1-17.

Chicago/Turabian Style

Liang Jia; Saini Yang; Weiping Wang; Xinlong Zhang. 2021. "Impact analysis of highways in China under future extreme precipitation." Natural Hazards , no. : 1-17.

Journal article
Published: 15 April 2021 in Environmental Research
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This study investigated the impact of humidity and temperature on the spread of COVID-19 (SARS-CoV-2) by statistically comparing modelled pandemic dynamics (daily infection and recovery cases) with daily temperature and humidity of three climate zones (Mainland China, South America and Africa) from January to August 2020. We modelled the pandemic growth using a simple logistic function to derive information of the viral infection and describe the growth of infected and recovered cases. The results indicate that the infected and recovered cases of the first wave were controlled in China and managed in both South America and Africa. There is a negative correlation between both humidity (r = − 0.21; p = 0.27) and temperature (r = −0.22; p = 0.24) with spread of the virus. Though this study did not fully encompass socio-cultural factors, we recognise that local government responses, general health policies, population density and transportation could also affect the spread of the virus. The pandemic can be managed better in the second wave if stricter safety protocols are implemented. We urge various units to collaborate strongly and call on countries to adhere to stronger safety protocols in the second wave.

ACS Style

Pius Babuna; Chuanliang Han; Meijia Li; Amatus Gyilbag; Bian Dehui; Doris Abra Awudi; Roberto Xavier Supe Tulcan; Saini Yang; Xiaohua Yang. The effect of human settlement temperature and humidity on the growth rules of infected and recovered cases of COVID-19. Environmental Research 2021, 197, 111106 -111106.

AMA Style

Pius Babuna, Chuanliang Han, Meijia Li, Amatus Gyilbag, Bian Dehui, Doris Abra Awudi, Roberto Xavier Supe Tulcan, Saini Yang, Xiaohua Yang. The effect of human settlement temperature and humidity on the growth rules of infected and recovered cases of COVID-19. Environmental Research. 2021; 197 ():111106-111106.

Chicago/Turabian Style

Pius Babuna; Chuanliang Han; Meijia Li; Amatus Gyilbag; Bian Dehui; Doris Abra Awudi; Roberto Xavier Supe Tulcan; Saini Yang; Xiaohua Yang. 2021. "The effect of human settlement temperature and humidity on the growth rules of infected and recovered cases of COVID-19." Environmental Research 197, no. : 111106-111106.

Journal article
Published: 31 March 2021 in International Journal of Disaster Risk Reduction
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Disaster information acquisition and assessment in China primarily depends on disaster-related governmental departments at all levels. As new challenges faced by disaster emergency management arise, a gap still exists in the timeliness and completeness of rapid disaster assessment. The development and popularity of social media has opened up new channels. Social media data, containing massive amounts of disaster information, has the advantages of timeliness, efficiency, and multiple spatiotemporal scales and can supplement existing methods. Based on the dominant social media platform in China, Sina Weibo, this paper proposes a method of extracting intensity information from Weibo texts, including social perceptions such as shaking, emergency reaction, mood and visible damage, which can support the rapid assessment of seismic intensity. By taking the Changning earthquake in Sichuan Province, China, as a case study, we verify the feasibility of hazard information extraction from Weibo. The results show that the intensity information derived from Weibo in the short-term can respond to a sudden earthquake promptly, then effectively identify the main earthquake affected area, locate the possible orientation close to the meizoseismal area and depict the situation in 10 minutes. We also propose a grid-based correction method, which synthesizes the hotness-intensity matrix and a seismic attenuation-based model. Compared with taking the seismic attenuation model directly, the proposed correction method improves the accuracy of correct recognition rate of seismic intensity assessment to 82% on average and reduces the false recognition rate significantly. The proposed framework of rapid assessment and correction reveals that the combination of social perception and hazard intensity plays a valuable and promising role as a supplement of traditional disaster assessment approach.

ACS Style

Kezhen Yao; Saini Yang; Jiting Tang. Rapid assessment of seismic intensity based on Sina Weibo — A case study of the changning earthquake in Sichuan Province, China. International Journal of Disaster Risk Reduction 2021, 58, 102217 .

AMA Style

Kezhen Yao, Saini Yang, Jiting Tang. Rapid assessment of seismic intensity based on Sina Weibo — A case study of the changning earthquake in Sichuan Province, China. International Journal of Disaster Risk Reduction. 2021; 58 ():102217.

Chicago/Turabian Style

Kezhen Yao; Saini Yang; Jiting Tang. 2021. "Rapid assessment of seismic intensity based on Sina Weibo — A case study of the changning earthquake in Sichuan Province, China." International Journal of Disaster Risk Reduction 58, no. : 102217.

Original paper
Published: 18 March 2021 in Nonlinear Dynamics
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Recurrent outbreaks of the coronavirus disease 2019 (COVID-19) have occurred in many countries around the world. We developed a twofold framework in this study, which is composed by one novel descriptive model to depict the recurrent global outbreaks of COVID-19 and one dynamic model to understand the intrinsic mechanisms of recurrent outbreaks. We used publicly available data of cumulative infected cases from 1 January 2020 to 2 January 2021 in 30 provinces in China and 43 other countries around the world for model validation and further analyses. These time series data could be well fitted by the new descriptive model. Through this quantitative approach, we discovered two main mechanisms that strongly correlate with the extent of the recurrent outbreak: the sudden increase in cases imported from overseas and the relaxation of local government epidemic prevention policies. The compartmental dynamical model (Susceptible, Exposed, Infectious, Dead and Recovered (SEIDR) Model) could reproduce the obvious recurrent outbreak of the epidemics and showed that both imported infected cases and the relaxation of government policies have a causal effect on the emergence of a new wave of outbreak, along with variations in the temperature index. Meanwhile, recurrent outbreaks affect consumer confidence and have a significant influence on GDP. These results support the necessity of policies such as travel bans, testing of people upon entry, and consistency of government prevention and control policies in avoiding future waves of epidemics and protecting economy.

ACS Style

Chuanliang Han; Meijia Li; Naem Haihambo; Pius Babuna; Qingfang Liu; Xixi Zhao; Carlo Jaeger; Ying Li; Saini Yang. Mechanisms of recurrent outbreak of COVID-19: a model-based study. Nonlinear Dynamics 2021, 1 -17.

AMA Style

Chuanliang Han, Meijia Li, Naem Haihambo, Pius Babuna, Qingfang Liu, Xixi Zhao, Carlo Jaeger, Ying Li, Saini Yang. Mechanisms of recurrent outbreak of COVID-19: a model-based study. Nonlinear Dynamics. 2021; ():1-17.

Chicago/Turabian Style

Chuanliang Han; Meijia Li; Naem Haihambo; Pius Babuna; Qingfang Liu; Xixi Zhao; Carlo Jaeger; Ying Li; Saini Yang. 2021. "Mechanisms of recurrent outbreak of COVID-19: a model-based study." Nonlinear Dynamics , no. : 1-17.

Journal article
Published: 06 February 2021 in International Journal of Disaster Risk Reduction
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Social media, as a new data source, is a promising field in disaster research. Despite doubts about its validity, a growing number of research institutes and commercial companies are exploring the potential of social media in disaster risk management. To understand the development and trends in this domain, a bibliometric analysis was performed using 1573 related published articles in Web of Science between 1991 and 2019. We found that (1) the number of annual publications and new research institutes in this field grew rapidly but seems to have become saturated in recent years. (2) The main research force is independent universities with limited cooperation, and a knowledge network has not yet been formed in this arena. (3) Research hotspots evolve in the path of “conceptualization - refinement - application”. Due to the three features of social media data, namely, timeliness, subjectivity, and disequilibrium, obstacles still exist in applicable disaster types and population representativeness. We anticipate new scientific advances emerging to overcome some technical difficulties. Knowledge sharing, advanced computer science, and multiorganizational cooperation will benefit this arena. These findings indicate potential directions for the development of and innovation in social media-based disaster research.

ACS Style

Jiting Tang; Saini Yang; Weiping Wang. Social media-based disaster research: Development, trends, and obstacles. International Journal of Disaster Risk Reduction 2021, 55, 102095 .

AMA Style

Jiting Tang, Saini Yang, Weiping Wang. Social media-based disaster research: Development, trends, and obstacles. International Journal of Disaster Risk Reduction. 2021; 55 ():102095.

Chicago/Turabian Style

Jiting Tang; Saini Yang; Weiping Wang. 2021. "Social media-based disaster research: Development, trends, and obstacles." International Journal of Disaster Risk Reduction 55, no. : 102095.

Article
Published: 28 September 2020 in International Journal of Disaster Risk Science
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This article focuses on decision making for retrofit investment of road networks in order to alleviate severe consequences of roadside tree blowdown during tropical cyclones. The consequences include both the physical damage associated with roadside trees and the functional degradation associated with road networks. A trilevel, two-stage, and multiobjective stochastic mathematical model was developed to dispatch limited resources to retrofit the roadside trees of a road network. In the model, a new metric was designed to evaluate the performance of a road network; resilience was considered from robustness and recovery efficiency of a road network. The proposed model is at least a nondeterministic polynomial-time hardness (NP-hard) problem, which is unlikely to be solved by a polynomial time algorithm. Pareto-optimal solutions for this problem can be obtained by a proposed trilevel algorithm. The random forest method was employed to transform the trilevel algorithm into a single-level algorithm in order to decrease the computation burden. Roadside tree retrofit of a provincial highway network on Hainan Island, China was selected as a case area because it suffers severely from tropical cyclones every year, where there is an urgency to upgrade roadside trees against tropical cyclones. We found that roadside tree retrofit investment significantly alleviates the expected economic losses of roadside tree blowdown, at the same time that it promotes robustness and expected recovery efficiency of the road network.

ACS Style

Fuyu Hu; Saini Yang; Russell G. Thompson. Resilience-Driven Road Network Retrofit Optimization Subject to Tropical Cyclones Induced Roadside Tree Blowdown. International Journal of Disaster Risk Science 2020, 12, 72 -89.

AMA Style

Fuyu Hu, Saini Yang, Russell G. Thompson. Resilience-Driven Road Network Retrofit Optimization Subject to Tropical Cyclones Induced Roadside Tree Blowdown. International Journal of Disaster Risk Science. 2020; 12 (1):72-89.

Chicago/Turabian Style

Fuyu Hu; Saini Yang; Russell G. Thompson. 2020. "Resilience-Driven Road Network Retrofit Optimization Subject to Tropical Cyclones Induced Roadside Tree Blowdown." International Journal of Disaster Risk Science 12, no. 1: 72-89.

Article
Published: 03 September 2020 in International Journal of Disaster Risk Science
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Rapid urbanization and natural hazards are posing threats to local ecological processes and ecosystem services worldwide. Using land use, socioeconomic, and natural hazards data, we conducted an assessment of the ecological vulnerability of prefectures in Sichuan Province for the years 2005, 2010, and 2015 to capture variations in its capacity to modulate in response to disturbances and to explore potential factors driving these variations. We selected five landscape metrics and two topological indicators for the proposed ecological vulnerability index (EVI), and constructed the EVI using a principal component analysis-based entropy method. A series of correlation analyses were subsequently performed to identify the factors driving variations in ecological vulnerability. The results show that: (1) for each of the study years, prefectures with high ecological vulnerability were located mainly in southern and eastern Sichuan, whereas prefectures in central and western Sichuan were of relatively low ecological vulnerability; (2) Sichuan’s ecological vulnerability increased significantly (p = 0.011) during 2005–2010; (3) anthropogenic activities were the main factors driving variations in ecological vulnerability. These findings provide a scientific basis for implementing ecological protection and restoration in Sichuan as well as guidelines for achieving integrated disaster risk reduction.

ACS Style

Yimeng Liu; Saini Yang; Chuanliang Han; Wei Ni; Yuyao Zhu. Variability in Regional Ecological Vulnerability: A Case Study of Sichuan Province, China. International Journal of Disaster Risk Science 2020, 11, 696 -708.

AMA Style

Yimeng Liu, Saini Yang, Chuanliang Han, Wei Ni, Yuyao Zhu. Variability in Regional Ecological Vulnerability: A Case Study of Sichuan Province, China. International Journal of Disaster Risk Science. 2020; 11 (6):696-708.

Chicago/Turabian Style

Yimeng Liu; Saini Yang; Chuanliang Han; Wei Ni; Yuyao Zhu. 2020. "Variability in Regional Ecological Vulnerability: A Case Study of Sichuan Province, China." International Journal of Disaster Risk Science 11, no. 6: 696-708.

Journal article
Published: 27 August 2020 in Advances in Climate Change Research
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A model-by-model analysis for historical simulations was necessary for identifying reasonably performing models in the updated Coupled Model Intercomparison Project (CMIP6) over the Tibetan Plateau. To determine whether the capacity of the CMIP6 models in simulating temperature and precipitation over the Plateau has been enhanced, we compared the outputs of 23 CMIP6 models with an observational dataset (CN05.1) for the period 1961–2014. The results suggest the systematic model biases (cold bias and wet bias) in the Tibetan Plateau still exist in CMIP6. Most models in CMIP6 realistically simulated the surface temperature and spatial distribution of precipitation, with a pattern correlation exceeding 0.75. The bias in the mean surface temperature of the multi-model ensemble (MME) simulation was 1.08 °C lower than the observational data, which had been decreased compared with the cold bias of CMIP5 (1.52 °C). At the seasonal scale, most models exhibited a warm temperature bias in summer and a cold bias in winter. The CMIP6 MME displayed a higher reproducibility of the precipitation amplitude over dry regions compared with CMIP5 and a lower ability over wet regions.

ACS Style

Yu-Yao Zhu; Saini Yang. Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5. Advances in Climate Change Research 2020, 11, 239 -251.

AMA Style

Yu-Yao Zhu, Saini Yang. Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5. Advances in Climate Change Research. 2020; 11 (3):239-251.

Chicago/Turabian Style

Yu-Yao Zhu; Saini Yang. 2020. "Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5." Advances in Climate Change Research 11, no. 3: 239-251.

Journal article
Published: 18 August 2020
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The first phase of the novel coronavirus disease (COVID-19) that emerged at the end of 2019 has been brought under control in the mainland of China in March, while it is still spreading globally. When the pandemic will end is a question of great concern. A logistic model that depicts the growth rules of infected and recovered cases in China’s mainland may shed some light on this question. This model well explained the data by 13 April from 31 countries that have been experiencing serious COVID-2019 outbreaks (R2 ≥ 0.95). Based on this model, the semi-saturation period (SSP) of infected cases in those countries ranges from 3 March to 18 June. According to the linear relationship between the growth rules for infected and for recovered cases identified from the Chinese data, we predicted that the SSP of the recovered cases outside China ranges from 22 March to 8 July. More importantly, we found a strong positive correlation between the SSP of infected cases and the timing of a government’s response. Finally, this model was also applied to four regions that went through other coronavirus or Ebola virus epidemics (R2 ≥ 0.95). There is a negative correlation between the death rate and the logistic growth rate. These findings provide strong evidence for the effectiveness of rapid epidemic control measures in various countries.

ACS Style

Chuanliang Han; Yimeng Liu; Jiting Tang; Yuyao Zhu; Carlo Jaeger; Saini Yang. Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide. 2020, 1 -11.

AMA Style

Chuanliang Han, Yimeng Liu, Jiting Tang, Yuyao Zhu, Carlo Jaeger, Saini Yang. Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide. . 2020; ():1-11.

Chicago/Turabian Style

Chuanliang Han; Yimeng Liu; Jiting Tang; Yuyao Zhu; Carlo Jaeger; Saini Yang. 2020. "Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide." , no. : 1-11.

Article
Published: 18 August 2020 in International Journal of Disaster Risk Science
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The first phase of the novel coronavirus disease (COVID-19) that emerged at the end of 2019 has been brought under control in the mainland of China in March, while it is still spreading globally. When the pandemic will end is a question of great concern. A logistic model that depicts the growth rules of infected and recovered cases in China’s mainland may shed some light on this question. This model well explained the data by 13 April from 31 countries that have been experiencing serious COVID-2019 outbreaks (R 2 ≥ 0.95). Based on this model, the semi-saturation period (SSP) of infected cases in those countries ranges from 3 March to 18 June. According to the linear relationship between the growth rules for infected and for recovered cases identified from the Chinese data, we predicted that the SSP of the recovered cases outside China ranges from 22 March to 8 July. More importantly, we found a strong positive correlation between the SSP of infected cases and the timing of a government’s response. Finally, this model was also applied to four regions that went through other coronavirus or Ebola virus epidemics (R 2 ≥ 0.95). There is a negative correlation between the death rate and the logistic growth rate. These findings provide strong evidence for the effectiveness of rapid epidemic control measures in various countries.

ACS Style

Chuanliang Han; Yimeng Liu; Jiting Tang; Yuyao Zhu; Carlo Jaeger; Saini Yang. Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide. International Journal of Disaster Risk Science 2020, 11, 1 -11.

AMA Style

Chuanliang Han, Yimeng Liu, Jiting Tang, Yuyao Zhu, Carlo Jaeger, Saini Yang. Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide. International Journal of Disaster Risk Science. 2020; 11 (4):1-11.

Chicago/Turabian Style

Chuanliang Han; Yimeng Liu; Jiting Tang; Yuyao Zhu; Carlo Jaeger; Saini Yang. 2020. "Lessons from the Mainland of China’s Epidemic Experience in the First Phase about the Growth Rules of Infected and Recovered Cases of COVID-19 Worldwide." International Journal of Disaster Risk Science 11, no. 4: 1-11.

Research article
Published: 19 July 2020 in International Journal of Climatology
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Coupled Model Intercomparison Project Phase 5 (CMIP5) models have limited capacity for depicting the variability of precipitation at interannual and interdecadal timescales. This study analyses the relative magnitude of interannual to multidecadal variability in annual precipitation across the world in the recently released CMIP6 dataset by quantifying the discrepancy between observed and modelled CMIP5 and CMIP6 data, considering both the absolute and relative magnitude of precipitation variability. We found that: 1) similar to CMIP5, CMIP6 models were short of capacity to simulate the non‐homogeneity in the relative magnitude of interdecadal variability, which is linked to prolonged drought and pluvials in terms of the strength value. The relative value of the interdecadal variability ranged from 15% to more than 30% in observation. Compared with observational data, the relative magnitude, having spatial uniformity, mostly ranged from 10–20% in CMIP5 and CMIP6. This result suggests that future projections lack a sufficient decadal variability in CMIP6, indicating a limited capacity for the prediction of floods and droughts in regions like central Africa, North America, and Amazonia. 2) Most individual models in CMIP6 had a better performance in terms of the spatial distribution of the interdecadal precipitation as compared to CMIP5. However, the absolute variations of the overall, interannual, and interdecadal precipitation of multi‐model ensemble simulations (MME) in CMIP6 were larger than those in CMIP5; 3) the underestimation of the interdecadal component in different areas was markedly decreased in East Asia, South Asia but increased in North and South Africa in CMIP6, when compared with CMIP5; 4) For future scenarios, the higher the range of future forcing pathway is, the larger interdecadal and interannual variabilities are in all regions in CMIP6. For future persistent droughts and floods predicting in a specific region, it is necessary to consider the discrepancy between historical simulations and observational data, and select the performance‐plus models.

ACS Style

Yuyao Zhu; Saini Yang. Interdecadal and interannual evolution characteristics of the global surface precipitation anomaly shown by CMIP5 and CMIP6 models. International Journal of Climatology 2020, 41, 1 .

AMA Style

Yuyao Zhu, Saini Yang. Interdecadal and interannual evolution characteristics of the global surface precipitation anomaly shown by CMIP5 and CMIP6 models. International Journal of Climatology. 2020; 41 (S1):1.

Chicago/Turabian Style

Yuyao Zhu; Saini Yang. 2020. "Interdecadal and interannual evolution characteristics of the global surface precipitation anomaly shown by CMIP5 and CMIP6 models." International Journal of Climatology 41, no. S1: 1.

Original research article
Published: 07 June 2020 in Risk Analysis
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The negative impact of climate change continues to escalate flood risk. Floods directly and indirectly damage highway systems and disturb the socioeconomic order. In this study, we propose an integrated approach to quantitatively assess how floods impact the functioning of a highway system. The approach has three parts: (1) a multi-agent simulation model to represent traffic, heterogeneous user demand, and route choice in a highway network; (2) a flood simulator using future runoff scenarios generated from five global climate models, three representative concentration pathways (RCPs), and the CaMa-Flood model; and (3) an impact analyzer, which superimposes the simulated floods on the highway traffic simulation system, and quantifies the flood impact on a highway system based on car following model. This approach is illustrated with a case study of the Chinese highway network. The results show that (i) for different global climate models, the associated flood damage to a highway system is not linearly correlated with the forcing levels of RCPs, or with future years; (ii) floods in different years have variable impacts on regional connectivity; and (iii) extreme flood impacts can cause huge damages in highway networks; that is, in 2030, the estimated 84.5% of routes between provinces cannot be completed when the highway system is disturbed by a future major flood. These results have critical implications for transport sector policies and can be used to guide highway design and infrastructure protection. The approach can be extended to analyze other networks with spatial vulnerability, and it is an effective quantitative tool for reducing systemic disaster risk.

ACS Style

Weiping Wang; Saini Yang; Jianxi Gao; Fuyu Hu; Wanyi Zhao; H. Eugene Stanley. An Integrated Approach for Assessing the Impact of Large‐Scale Future Floods on a Highway Transport System. Risk Analysis 2020, 40, 1780 -1794.

AMA Style

Weiping Wang, Saini Yang, Jianxi Gao, Fuyu Hu, Wanyi Zhao, H. Eugene Stanley. An Integrated Approach for Assessing the Impact of Large‐Scale Future Floods on a Highway Transport System. Risk Analysis. 2020; 40 (9):1780-1794.

Chicago/Turabian Style

Weiping Wang; Saini Yang; Jianxi Gao; Fuyu Hu; Wanyi Zhao; H. Eugene Stanley. 2020. "An Integrated Approach for Assessing the Impact of Large‐Scale Future Floods on a Highway Transport System." Risk Analysis 40, no. 9: 1780-1794.

Other
Published: 22 April 2020
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The novel coronavirus disease (COVID-19) that emerged at the end of 2019 has been controlled in mainland China so far, while it is still spreading globally. When the pandemic will end is a question of great concern. A logistic model depicting the growth rules of infected and recovered cases in mainland China may shed some light on this question. We extended this model to 31 countries outside China experiencing serious COVID-2019 outbreaks. The model well explained the data in our study (R2 >0.95). For infected cases, the semi-saturation period (SSP) ranges from 63 to 170 days (March 3 to June 18). The logistic growth rate of infected cases is positively correlated with that of recovered cases, and the same holds for the SSP. According to the linear connection between the growth rules for infected and recovered cases identified from the Chinese data, we predicted that the SSP of the recovered cases outside China ranges from 82 to 196 days (March 22 to July 8). More importantly, we found a strong positive correlation between the SSP of infected cases and the timing of the government's response, providing strong evidence for the effectiveness of rapid epidemic control measures in various countries.

ACS Style

Chuanliang Han; Yimeng Liu; Jiting Tang; Yuyao Zhu; Carlo Jaeger; Saini Yang. Lessons from mainland China's epidemic experience about the growth rules of infected and recovered cases of COVID-19 worldwide. 2020, 1 .

AMA Style

Chuanliang Han, Yimeng Liu, Jiting Tang, Yuyao Zhu, Carlo Jaeger, Saini Yang. Lessons from mainland China's epidemic experience about the growth rules of infected and recovered cases of COVID-19 worldwide. . 2020; ():1.

Chicago/Turabian Style

Chuanliang Han; Yimeng Liu; Jiting Tang; Yuyao Zhu; Carlo Jaeger; Saini Yang. 2020. "Lessons from mainland China's epidemic experience about the growth rules of infected and recovered cases of COVID-19 worldwide." , no. : 1.

Other
Published: 25 February 2020
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An outbreak of a novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) was first diagnosed in Wuhan, China, in December 2019 and then spread rapidly to other regions. We collected the time series data of the cumulative number of confirmed infected, dead, and cured cases from the health commissions in 31 provinces in mainland China. A descriptive model in a logistic form was formulated to infer the intrinsic epidemic rules of COVID-19, which illustrates robustness spatially and temporally. Our model is robust (R2>0.95) to depict the intrinsic growth rule for the cumulative number of confirmed infected, dead, and cured cases in 31 provinces in mainland China. Furthermore, we compared the intrinsic epidemic rules of COVID-19 in Hubei with that of severe acute respiratory syndrome (SARS) in Beijing, which was obtained from the Ministry of Public Health of China in 2003. We found that the infected case is the earliest to be saturated and has the lowest semi-saturation period compared with deaths and cured cases for both COVID-19 and SARS. All the three types of SARS cases are later to saturate and have longer semi-saturation period than that of COVID-19. Despite the virus caused SARS (SARS-CoV) and the virus caused COVID-19 (SARS-CoV-2) are homologous, the duration of the outbreak would be shorter for COVID-19.

ACS Style

Chuanliang Han; Yimeng Liu; Saini Yang. Intrinsic growth rules of patients infected, dead and recovered with 2019 novel coronavirus in mainland China. 2020, 1 .

AMA Style

Chuanliang Han, Yimeng Liu, Saini Yang. Intrinsic growth rules of patients infected, dead and recovered with 2019 novel coronavirus in mainland China. . 2020; ():1.

Chicago/Turabian Style

Chuanliang Han; Yimeng Liu; Saini Yang. 2020. "Intrinsic growth rules of patients infected, dead and recovered with 2019 novel coronavirus in mainland China." , no. : 1.

Journal article
Published: 23 January 2020 in Science of The Total Environment
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In response to more frequent heatwaves, various regional or national heat-health warning systems (HHWSs) have been developed recently as adaptation measures. A wide range of methodologies have been utilized to issue warnings, as there is no universal definition of “heat event” or “heatwave”, nor are there quantified thresholds of human-health tolerance to extreme weather. The performance of these warning systems has rarely been evaluated with actual heat-health data, especially the morbidity data, in regions with severe impact. In this study, we assessed the performance of the Shanghai HHWS based on heat-related illness data collected by the Chinese Center for Disease Control and Prevention (China CDC) and then conducted a comparative analysis among the Shanghai HHWS, the China Meteorological Administration HHWS, the Chinese national standard for heatwave indexes, the heat index adopted by the USA's National Weather Service and the definition suggested by the World Meteorological Organization to understand their potential performance for application in Shanghai and to evaluate the temperature thresholds and different meteorological indices employed. The results show that: 1) during the research period, 50% of heat-related illnesses and 58.2% of heat-related deaths in Shanghai occurred on dates that had no heat warnings; 2) for the current threshold (35 °C), the single metric of temperature outperformed the temperature-duration two-parameter method; 3) different from existing studies, while infants and seniors are deemed as vulnerable population groups to heat, young and middle-aged males were found to suffer more heat-related illnesses in hot weather. More detailed analyses reveal that the performance of heat-health warning systems needs to be evaluated and revised periodically, and warning thresholds utilized must be localized to reflect public tolerance to heat and to address the vulnerability of target population groups. Temperature is the dominant threshold in heat-related morbidity and mortality analysis. While a decrease in the temperature threshold would definitely increase the warning frequency and socioeconomic costs, it might also cause warning fatigue. The trade-off between these two aspects is essential for decision-makers and other stakeholders in HHWS design and improvement.

ACS Style

Yaqiao Wu; Xiaoye Wang; Jingyan Wu; Rui Wang; Saini Yang. Performance of heat-health warning systems in Shanghai evaluated by using local heat-related illness data. Science of The Total Environment 2020, 715, 136883 .

AMA Style

Yaqiao Wu, Xiaoye Wang, Jingyan Wu, Rui Wang, Saini Yang. Performance of heat-health warning systems in Shanghai evaluated by using local heat-related illness data. Science of The Total Environment. 2020; 715 ():136883.

Chicago/Turabian Style

Yaqiao Wu; Xiaoye Wang; Jingyan Wu; Rui Wang; Saini Yang. 2020. "Performance of heat-health warning systems in Shanghai evaluated by using local heat-related illness data." Science of The Total Environment 715, no. : 136883.

Journal article
Published: 15 May 2019 in Nature Communications
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The adverse effect of climate change continues to expand, and the risks of flooding are increasing. Despite advances in network science and risk analysis, we lack a systematic mathematical framework for road network percolation under the disturbance of flooding. The difficulty is rooted in the unique three-dimensional nature of a flood, where altitude plays a critical role as the third dimension, and the current network-based framework is unsuitable for it. Here we develop a failure model to study the effect of floods on road networks; the result covers 90.6% of road closures and 94.1% of flooded streets resulting from Hurricane Harvey. We study the effects of floods on road networks in China and the United States, showing a discontinuous phase transition, indicating that a small local disturbance may lead to a large-scale systematic malfunction of the entire road network at a critical point. Our integrated approach opens avenues for understanding the resilience of critical infrastructure networks against floods.

ACS Style

Weiping Wang; Saini Yang; H. Eugene Stanley; Jianxi Gao. Local floods induce large-scale abrupt failures of road networks. Nature Communications 2019, 10, 2114 .

AMA Style

Weiping Wang, Saini Yang, H. Eugene Stanley, Jianxi Gao. Local floods induce large-scale abrupt failures of road networks. Nature Communications. 2019; 10 (1):2114.

Chicago/Turabian Style

Weiping Wang; Saini Yang; H. Eugene Stanley; Jianxi Gao. 2019. "Local floods induce large-scale abrupt failures of road networks." Nature Communications 10, no. 1: 2114.

Conference paper
Published: 01 November 2018 in Journal of Physics: Conference Series
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This study proposes an agent-based model to investigate major stakeholders' behaviors in the housing market. The proposed model mimics the heterogeneous behaviors of individual buyers and sellers in a housing market considering bounded rationality. The simulation results of case study in Shanghai are robust and reproduce stylized facts including as volatility clustering, absence of autocorrelations, heavy tail, loss asymmetry, and aggregational gaussianity on the absolute return.

ACS Style

Weiping Wang; Saini Yang; Fuyu Hu; Zhangang Han; Carlo Jaeger. An agent-based modeling for housing prices with bounded rationality. Journal of Physics: Conference Series 2018, 1113, 012014 .

AMA Style

Weiping Wang, Saini Yang, Fuyu Hu, Zhangang Han, Carlo Jaeger. An agent-based modeling for housing prices with bounded rationality. Journal of Physics: Conference Series. 2018; 1113 (1):012014.

Chicago/Turabian Style

Weiping Wang; Saini Yang; Fuyu Hu; Zhangang Han; Carlo Jaeger. 2018. "An agent-based modeling for housing prices with bounded rationality." Journal of Physics: Conference Series 1113, no. 1: 012014.

Journal article
Published: 01 November 2018 in Physica A: Statistical Mechanics and its Applications
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As socioeconomic systems continue to develop, their critical infrastructure systems become more intricate and the interdependencies among systems more intensive. This cascading effect on critical infrastructure systems significantly impacts system performance. We develop an approach to quantitatively assess the complex cascading effect on critical infrastructure systems under four different types of attack: (i) random, (ii) malicious, (iii) shell-based and local, and (iv) orientated and local. In the context of these four we study three types of cascading effect—non-cascading, inner-system cascading, and inter-system cascading—in both independent systems and interdependent systems. We model both logical and geographical interdependency. We apply this approach to the Chinese road and railway system and find that (i) the damage done by different types of attack on critical infrastructures systems varies significantly, (ii) under the same type of attack the damage caused by cascading effects on different critical infrastructure systems varies significantly, and (iii) different cascading effects contribute to damage in critical infrastructure systems. These findings indicate that more theoretical and practical research on cascading effects in infrastructure systems under different attacks is needed, especially when the attacks are local and oriented.

ACS Style

Weiping Wang; Saini Yang; Fuyu Hu; H. Eugene Stanley; Shuai He; Mimi Shi. An approach for cascading effects within critical infrastructure systems. Physica A: Statistical Mechanics and its Applications 2018, 510, 164 -177.

AMA Style

Weiping Wang, Saini Yang, Fuyu Hu, H. Eugene Stanley, Shuai He, Mimi Shi. An approach for cascading effects within critical infrastructure systems. Physica A: Statistical Mechanics and its Applications. 2018; 510 ():164-177.

Chicago/Turabian Style

Weiping Wang; Saini Yang; Fuyu Hu; H. Eugene Stanley; Shuai He; Mimi Shi. 2018. "An approach for cascading effects within critical infrastructure systems." Physica A: Statistical Mechanics and its Applications 510, no. : 164-177.

Article
Published: 20 September 2018 in International Journal of Disaster Risk Science
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Although the notion of systemic risk gained prominence with respect to financial systems, it is a generic term that refers to risks of increasing importance in many domains—risks that cannot be tackled by conventional techniques of risk management and governance. We build on a domain-overarching definition of systemic risks by highlighting crucial properties that distinguish them from conventional risks and plain disasters. References to typical examples from various domains are included. Common features of systemic risks in different domains—such as the role of agents and emergence phenomena, tipping and cascading, parameters indicating instability, and historicity—turn out to be more than noncommittal empirical observations. Rather these features can be related to fundamental theory for relatively simple and well-understood systems in physics and chemistry. A crucial mechanism is the breakdown of macroscopic patterns of whole systems due to feedback reinforcing actions of agents on the microlevel, where the reinforcement is triggered by boundary conditions moving beyond critical tipping points. Throughout the whole article, emphasis is placed on the role of complexity science as a basis for unifying the phenomena of systemic risks in widely different domains.

ACS Style

Klaus Lucas; Ortwin Renn; Carlo Jaeger; Saini Yang. Systemic Risks: A Homomorphic Approach on the Basis of Complexity Science. International Journal of Disaster Risk Science 2018, 9, 292 -305.

AMA Style

Klaus Lucas, Ortwin Renn, Carlo Jaeger, Saini Yang. Systemic Risks: A Homomorphic Approach on the Basis of Complexity Science. International Journal of Disaster Risk Science. 2018; 9 (3):292-305.

Chicago/Turabian Style

Klaus Lucas; Ortwin Renn; Carlo Jaeger; Saini Yang. 2018. "Systemic Risks: A Homomorphic Approach on the Basis of Complexity Science." International Journal of Disaster Risk Science 9, no. 3: 292-305.

Short article
Published: 06 June 2018 in International Journal of Disaster Risk Science
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ACS Style

Peijun Shi; Rajib Shaw; Ali Ardalan; Emily Ying Yang Chan; Jamilur Reza Choudhury; Peng Cui; Bojie Fu; GuoYi Han; Qunli Han; Takako Izumi; Fumiko Kasuga; Antonia Yulo Loyzaga; Joy Jacqueline Pereira; Shirish Kumar Ravan; David Sanderson; Vinod Kumar Sharma; Frank Thomalla; Sugeng Triutomo; Siquan Yang; Qian Ye; Ming Wang; Yaqiao Wu; Renhe Zhang; Wenjian Zhang; Ying Li; Saini Yang. Fourteen Actions and Six Proposals for Science and Technology-Based Disaster Risk Reduction in Asia. International Journal of Disaster Risk Science 2018, 9, 275 -279.

AMA Style

Peijun Shi, Rajib Shaw, Ali Ardalan, Emily Ying Yang Chan, Jamilur Reza Choudhury, Peng Cui, Bojie Fu, GuoYi Han, Qunli Han, Takako Izumi, Fumiko Kasuga, Antonia Yulo Loyzaga, Joy Jacqueline Pereira, Shirish Kumar Ravan, David Sanderson, Vinod Kumar Sharma, Frank Thomalla, Sugeng Triutomo, Siquan Yang, Qian Ye, Ming Wang, Yaqiao Wu, Renhe Zhang, Wenjian Zhang, Ying Li, Saini Yang. Fourteen Actions and Six Proposals for Science and Technology-Based Disaster Risk Reduction in Asia. International Journal of Disaster Risk Science. 2018; 9 (2):275-279.

Chicago/Turabian Style

Peijun Shi; Rajib Shaw; Ali Ardalan; Emily Ying Yang Chan; Jamilur Reza Choudhury; Peng Cui; Bojie Fu; GuoYi Han; Qunli Han; Takako Izumi; Fumiko Kasuga; Antonia Yulo Loyzaga; Joy Jacqueline Pereira; Shirish Kumar Ravan; David Sanderson; Vinod Kumar Sharma; Frank Thomalla; Sugeng Triutomo; Siquan Yang; Qian Ye; Ming Wang; Yaqiao Wu; Renhe Zhang; Wenjian Zhang; Ying Li; Saini Yang. 2018. "Fourteen Actions and Six Proposals for Science and Technology-Based Disaster Risk Reduction in Asia." International Journal of Disaster Risk Science 9, no. 2: 275-279.