scholarly journals A Data-Driven Approach Based on Multivariate Copulas for Quantitative Risk Assessment of Concrete Dam

2019 ◽  
Vol 7 (10) ◽  
pp. 353 ◽  
Author(s):  
Chenfei Shao ◽  
Chongshi Gu ◽  
Zhenzhu Meng ◽  
Yating Hu
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Risk Ratio ◽  
Copula Function ◽  
Quantitative Risk Assessment ◽  
Data Driven ◽  
Data Series ◽  
Monitoring Point ◽  
Risk Probability ◽  
Multivariate Copula

Risk assessment of dam’s running status is an important part of dam management. A data-driven method based on monitored displacement data has been applied in risk assessment, owing to its easy operation and real-time analysis. However, previous data-driven methods considered displacement data series at each monitoring point as an independent variable and assessed the running status of each monitoring point separately, without considering the correlation between displacement of different monitoring points. In addition, previous studies assessed the dam’s running status qualitatively, without quantifying the risk probability. To solve the above two issues, a displacement-data driven method based on a multivariate copula function is proposed in this paper. Multivariate copula functions can construct a joint distribution which reveals the relevance structure of random variables. We assumed that the risk probability of each dam section is independent and took monitoring points at one dam section as examples. Starting from the risk assessment of single monitoring points, we calculated the residual between the monitored displacement data and the modelled data estimated by the statistical model, and built a risk ratio function based on the residual. Then, using the multivariate copula function, we obtained a combined risk ratio of multi-monitoring points which took the correlation between each monitoring point into account. Finally, a case study was provided. The proposed method not only quantitatively assessed the probability of the real-time dam risk but also considered the correlation between the displacement data of different monitoring points.

scholarly journals Implications of Limits of Detection of Various Methods for Bacillus anthracis in Computing Risks to Human Health

2009 ◽  
Vol 75 (19) ◽  
pp. 6331-6339 ◽  
Author(s):  
Amanda B. Herzog ◽  
S. Devin McLennan ◽  
Alok K. Pandey ◽  
Charles P. Gerba ◽  
Charles N. Haas ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Bacillus Anthracis ◽  
Real Time ◽  
Real Time Pcr ◽  
Limit Of Detection ◽  
Quantitative Risk Assessment ◽  
Detection Methods ◽  
Enzyme Linked Immunosorbent Assay ◽  
Environmental Matrices ◽  
Limits Of Detection

ABSTRACT Used for decades for biological warfare, Bacillus anthracis (category A agent) has proven to be highly stable and lethal. Quantitative risk assessment modeling requires descriptive statistics of the limit of detection to assist in defining the exposure. Furthermore, the sensitivities of various detection methods in environmental matrices are vital information for first responders. A literature review of peer-reviewed journal articles related to methods for detection of B. anthracis was undertaken. Articles focused on the development or evaluation of various detection approaches, such as PCR, real-time PCR, immunoassay, etc. Real-time PCR and PCR were the most sensitive methods for the detection of B. anthracis, with median instrument limits of detection of 430 and 440 cells/ml, respectively. There were very few peer-reviewed articles on the detection methods for B. anthracis in the environment. The most sensitive limits of detection for the environmental samples were 0.1 CFU/g for soil using PCR-enzyme-linked immunosorbent assay (ELISA), 17 CFU/liter for air using an ELISA-biochip system, 1 CFU/liter for water using cultivation, and 1 CFU/cm2 for stainless steel fomites using cultivation. An exponential dose-response model for the inhalation of B. anthracis estimates of risk at concentrations equal to the environmental limit of detection determined the probability of death if untreated to be as high as 0.520. Though more data on the environmental limit of detection would improve the assumptions made for the risk assessment, this study's quantification of the risk posed by current limitations in the knowledge of detection methods should be considered when employing those methods in environmental monitoring and cleanup strategies.

scholarly journals Rapid Quantification of Viable Campylobacter Bacteria on Chicken Carcasses, Using Real-Time PCR and Propidium Monoazide Treatment, as a Tool for Quantitative Risk Assessment

2010 ◽  
Vol 76 (15) ◽  
pp. 5097-5104 ◽  
Author(s):  
M. H. Josefsen ◽  
C. L�fstr�m ◽  
T. B. Hansen ◽  
L. S. Christensen ◽  
J. E. Olsen ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Control Strategies ◽  
Quantitative Risk Assessment ◽  
Quantitative Detection ◽  
Amplification Efficiency ◽  
Sample Treatment ◽  
Propidium Monoazide ◽  
Real Time Quantitative Pcr ◽  
Chicken Carcass

ABSTRACT A number of intervention strategies against Campylobacter-contaminated poultry focus on postslaughter reduction of the number of cells, emphasizing the need for rapid and reliable quantitative detection of only viable Campylobacter bacteria. We present a new and rapid quantitative approach to the enumeration of food-borne Campylobacter bacteria that combines real-time quantitative PCR (Q-PCR) with simple propidium monoazide (PMA) sample treatment. In less than 3 h, this method generates a signal from only viable and viable but nonculturable (VBNC) Campylobacter bacteria with an intact membrane. The method's performance was evaluated by assessing the contributions to variability by individual chicken carcass rinse matrices, species of Campylobacter, and differences in efficiency of DNA extraction with differing cell inputs. The method was compared with culture-based enumeration on 50 naturally infected chickens. The cell contents correlated with cycle threshold (CT ) values (R 2 = 0.993), with a quantification range of 1 � 102 to 1 � 107 CFU/ml. The correlation between the Campylobacter counts obtained by PMA-PCR and culture on naturally contaminated chickens was high (R 2 = 0.844). The amplification efficiency of the Q-PCR method was not affected by the chicken rinse matrix or by the species of Campylobacter. No Q-PCR signals were obtained from artificially inoculated chicken rinse when PMA sample treatment was applied. In conclusion, this study presents a rapid tool for producing reliable quantitative data on viable Campylobacter bacteria in chicken carcass rinse. The proposed method does not detect DNA from dead Campylobacter bacteria but recognizes the infectious potential of the VBNC state and is thereby able to assess the effect of control strategies and provide trustworthy data for risk assessment.

Quantitative Pipeline Risk Assessment and Maintenance Optimization

2004 ◽  
Author(s):  
Patrick L. Wickenhauser ◽  
David K. Playdon
Keyword(s):  
Risk Assessment ◽  
Risk Ratio ◽  
Financial Risk ◽  
Minimum Cost ◽  
Quantitative Risk Assessment ◽  
Individual Risk ◽  
Optimal Time ◽  
Time Interval ◽  
Safety Risk ◽  
The Individual

The quantitative risk assessment tool was used to calculate the failure rates, failure consequences and risk levels along the pipeline. Safety risk was characterized by the individual risk ratio, which was defined as the maximum individual risk associated with a given segment divided by the tolerable individual risk. Tolerable individual risk values were defined as a function of population density following the approach developed by MIACC and the UK HSE. Financial risk was expressed in dollars per km-year and included a dollar equivalent for public perception. The recommended maintenance plan was defined as the minimum cost option that achieved a tolerable safety risk. The first step in developing the plan was to identify all segments that do not meet tolerable risk criteria (i.e., segments with an individual risk ratio greater than 1). For each of these segments a number of potential maintenance scenarios that address the dominant failure threats were selected. A cost optimization analysis was then carried out in which the total expected cost associated with each maintenance option was calculated as the sum of implementing the option plus the corresponding financial risk component, amortized over the inspection interval. This analysis was used to identify the minimum cost alternative that meets the individual risk constraint. Outcomes of the analysis included the best maintenance option (e.g., inline inspection, hydrostatic test) and the optimal time interval for segment re-evaluation.

scholarly journals Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis

2020 ◽  
Author(s):  
Tanujit Chakraborty ◽  
Indrajit Ghosh
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Moving Average ◽  
Hybrid Approach ◽  
Regression Tree ◽  
Case Fatality ◽  
Warning System ◽  
Data Driven ◽  
Short Term ◽  
The Future

AbstractThe coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020, it has caused a pandemic outbreak with more than 11,16,643 confirmed infections and more than 59,170 reported deaths worldwide. The main focus of this paper is two-fold: (a) generating short term (real-time) forecasts of the future COVID-19 cases for multiple countries; (b) risk assessment (in terms of case fatality rate) of the novel COVID-19 for some profoundly affected countries by finding various important demographic characteristics of the countries along with some disease characteristics. To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as an early-warning system for government policymakers. In the second problem, we applied an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries. This data-driven analysis will necessarily provide deep insights into the study of early risk assessments for 50 immensely affected countries.

A semi-quantitative risk assessment model for the outbreak of grass carp hemorrhage

2013 ◽  
Vol 19 (3) ◽  
pp. 521-527 ◽  
Author(s):  
Song YANG ◽  
Shuqin WU ◽  
Ningqiu LI ◽  
Cunbin SHI ◽  
Guocheng DENG ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Grass Carp ◽  
Assessment Model ◽  
Quantitative Risk Assessment ◽  
Risk Assessment Model

Risk assessment of Campylobacter species in shellfish: identifying the unknown

1997 ◽  
Vol 35 (11-12) ◽  
pp. 29-34 ◽  
Author(s):  
P. Teunis ◽  
A. Havelaar ◽  
J. Vliegenthart ◽  
G. Roessink
Keyword(s):  
Risk Assessment ◽  
Quantitative Risk Assessment ◽  
Contamination Level ◽  
Risk Of Infection ◽  
Worst Case ◽  
Considerable Uncertainty ◽  
Risk Estimates ◽  
Consumption Data ◽  
Campylobacter Infection ◽  
Campylobacter Spp

Shellfish are frequently contaminated by Campylobacter spp, presumably originating from faeces from gulls feeding in the growing or relaying waters. The possible health effects of eating contaminated shellfish were estimated by quantitative risk assessment. A paucity of data was encountered necessitating many assumptions to complete the risk estimate. The level of Campylobacter spp in shellfish meat was calculated on the basis of a five-tube, single dilution MPN and was strongly season-dependent. The contamination level of mussels (<1/g) appeared to be higher than in oysters. The usual steaming process of mussels was found to completely inactivate Campylobacter spp so that risks are restricted to raw/undercooked shellfish. Consumption data were estimated on the basis of the usual size of a portion of raw shellfish and the weight of meat/individual animal. Using these data, season-dependent dose-distributions could be estimated. The dominant species in Dutch shellfish is C. lari but little is known on its infectivity for man. As a worst case assumption, it was assumed that the infectivity was similar to C. jejuni. A published dose-response model for Campylobacter-infection of volunteers is available but with considerable uncertainty in the low dose region. Using Monte Carlo simulation, risk estimates were constructed. The consumption of a single portion of raw shellfish resulted in a risk of infection of 5–20% for mussels (depending on season; 95% CI 0.01–60%). Repeated (e.g. monthly) exposures throughout a year resulted in an infection risk of 60% (95% CI 7–99%). Risks for oysters were slightly lower than for mussels. It can be concluded that, under the assumptions made, the risk of infection with Campylobacter spp by eating of raw shellfish is substantial. Quantitative risk estimates are highly demanding for the availability and quality of experimental data, and many research needs were identified.

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