Evolution of seismic risk management for insurance over the past 30 years

During the past 30 years, there has been spectacular growth in the use of risk analysis and risk management tools developed by engineers in the financial and insurance sectors. The insurance, the reinsurance, and the investment banking sectors have enthusiastically adopted loss estimation tools developed by engineers in developing their business strategies and for managing their financial risks. As a result, insurance/reinsurance strategy has evolved as a major risk mitigation tool in managing catastrophe risk at the individual, corporate, and government level. This is particularly true in developed countries such as US, Western Europe, and Japan. Unfortunately, it has not received the needed attention in developing countries, where such a strategy for risk management is most needed. Fortunately, in the last five years, there has been excellent focus in developing ＂Insur Tech＂ tools to address the much needed ＂Insurance for the Masses＂, especially for the Asian Markets. In the earlier years of catastrophe model development, risk analysts were mainly concerned with risk reduction options through engineering strategies, and relatively little attention was given to financial and economic strategies. Such state-of-affairs still exists in many developing countries. The new developments in the science and technologies of loss estimation due to natural catastrophes have made it possible for financial sectors to model their business strategies such as peril and geographic diversification, premium calculations, reserve strategies, reinsurance contracts, and other underwriting tools. These developments have not only changed the way in which financial sectors assess and manage their risks, but have also changed the domain of opportunities for engineers and scientists.This paper will address the issues related to developing insurance/reinsurance strategies to mitigate catastrophe risks and describe the role catastrophe risk insurance and reinsurance has played in managing financial risk due to natural catastrophes. Historical losses and the share of those losses covered by insurance will be presented. How such risk sharing can help the nation share the burden of losses between tax paying public, the ＂at risk＂ property owners, the insurers and the reinsurers will be discussed. The paper will summarize the tools that are used by the insurance and reinsurance companies for estimating their future losses due to catastrophic natural events. The paper will also show how the results of loss estimation technologies developed by engineers are communicated to the business flow of insurance/reinsurance companies. Finally, to make it possible to grow ＂Insurance for the Masses - IFM＂, the role played by parametric insurance products and Insur Tech tools will be discussed.

Cardiovascular risk management in cancer survivors:Are we doing it right?

Although under-recognized,cancer survivors continue to be at an increased risk of death from cardiovascular complications post-remission or cure.This increased burden of cardiovascular disease results from the interplay of various factors.Adequate cardiovascular risk assessment and timely intervention through a multi-disciplinary approach in these patients plays a pivotal role in the prevention of cardiovascular morbidity and mortality.We discuss the shortcomings of using current risk prediction scores in cancer survivors and provide some insights into cardiovascular risk management relevant for primary care physicians,oncologists,and cardiologists alike.

An immunity based network security risk estimation

According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunitybased model for the network security risk estimation （Insre）. In Insre, the concepts and formal definitions of self, nonself, antibody, antigen and lymphocyte in the network security domain are given. Then the mathematical models of the selftolerance, the clonal selection, the lifecycle of mature lymphocyte, immune memory and immune surveillance are established. Building upon the above models, a quantitative computation model for network security risk estimation, which is based on the calculation of antibody concentration, is thus presented. By using Insre, the types and intensity of network attacks, as well as the risk level of network security, can be calculated quantitatively and in real-time. Our theoretical analysis and experimental results show that Insre is a good solution to real-time risk evaluation for the network security.

Risk estimation and prediction of the transmission of coronavirus disease-2019(COVID-19)in the mainland of China excluding Hubei province

Background In December 2019,an outbreak of coronavirus disease(later named as COVID-19)was identified in Wuhan,China and,later on,detected in other parts of China.Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures,estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in the mainland of China excluding Hubei province based on the published data and a novel mathematical model.Methods A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed.COVID-19 daily data of the mainland of China excluding Hubei province,including the cumulative confirmed cases,the cumulative deaths,newly confirmed cases and the cumulative recovered cases between 20 January and 3 March 2020,were archived from the National Health Commission of China(NHCC).We parameterize the model by using the Markov Chain Monte Carlo(MCMC)method and estimate the control reproduction number(Rc),as well as the effective daily reproduction ratio-Re(t),of the disease transmission in the mainland of China excluding Hubei province.Results The estimation outcomes indicate that Rc is 3.36(95%CI:3.20–3.64)and Re(t)has dropped below 1 since 31 January 2020,which implies that the containment strategies implemented by the Chinese government in the mainland of China are indeed effective and magnificently suppressed COVID-19 transmission.Moreover,our results show that relieving personal protection too early may lead to a prolonged disease transmission period and more people would be infected,and may even cause a second wave of epidemic or outbreaks.By calculating the effective reproduction ratio,we prove that the contact rate should be kept at least less than 30%of the normal level by April,2020.Conclusions To ensure the pandemic ending rapidly,it is necessary to maintain the current integrated restrict interventions and self-protection measures,including travel restriction,quarantine of entry,contact tracing followed by quarantine and isolation and reduction of contact,like wearing masks,keeping social distance,etc.People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April.If all the above conditions are met,the outbreak is expected to be ended by April in the mainland of China apart from Hubei province.

Estimator of Scale Parameter in a Subclass of the Exponential Family under Symmetric Entropy Loss

In this paper we investigate the estimator for the rth power of the scale parameter in a class of exponential family under symmetric entropy loss L（θ, δ） = v（θ/δ ＋ δ/θ - 2）. An exact form of the minimum risk equivariant estimator under symmetric entropy loss is given, and the minimaxity of the minimum risk equivariant estimator is proved. The results with regard to admissibility and inadmissibility of a class of linear estimators of the form cT（X） ＋ d are given, where T（X） Gamma（v, θ）.

The Clinical Value of Syntax Scores in Predicting Coronary Artery Disease Outcomes

The Synergy Between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery(SYNTAX)score(SS)has significantly improved angiographic risk stratification.By analyzing angiographic variables,this score characterizes coronary artery disease qualitatively and quantitatively.To date,combining this score with other non-angiographic clini-cal scores has broadened perspectives regarding risk estimation,and future research on this topic appears promising.

Analysis of Length of Stay (LOS) Data from the Medical Records of Tertiary Care Hospital in Saudi Arabia for Five Diagnosis Related Groups: Application of Cox Prediction Model

Background: One of the main objectives of hospital managements is to control the length of stay (LOS). Successful control of LOS of inpatients will result in reduction in the cost of care, decrease in nosocomial infections, medication side effects, and better management of the limited number of available patients’ beds. The length of stay (LOS) is an important indicator of the efficiency of hospital management by improving the quality of treatment, and increased hospital profit with more efficient bed management. The purpose of this study was to model the distribution of LOS as a function of patient’s age, and the Diagnosis Related Groups (DRG), based on electronic medical records of a large tertiary care hospital. Materials and Methods: Information related to the research subjects were retrieved from a database of patients admitted to King Faisal Specialist Hospital and Research Center hospital in Riyadh, Saudi Arabia between January 2014 and December 2016. Subjects’ confidential information was masked from the investigators. The data analyses were reported visually, descriptively, and analytically using Cox proportional hazard regression model to predict the risk of long-stay when patients’ age and the DRG are considered as antecedent risk factors. Results: Predicting the risk of long stay depends significantly on the age at admission, and the DRG to which a patient belongs to. We demonstrated the validity of the Cox regression model for the available data as the proportionality assumption is shown to be satisfied. Two examples were presented to demonstrate the utility of the Cox model in this regard.

Existence of the Uniformly Minimum Risk Unbiased Estimator in Seemingly Unrelated Regression System

For a seemingly Unrelated regression system with the assumption of normality,a necessary and sufficient condition for the existence of the Uniformly Minimum Risk Unbiased (UMRU)estimator of regression coefficients under strictly convex loss is obtained;it is proved that any unbiased estimator can not improve the least squares estimator;it is also shown that no UMRU estimator exists under missing observations.

Opinion on reconsideration of lung cancer risk from domestic radon exposure

Two extensive collaborative meta studies including 13 residential case-control studies from Europe and 7 from North America have demonstrated that domestic radon clearly poses a risk for lung cancer at exposure levels approaching those for underground miners.An excess risk for lung cancer of 0.08–0.16 per 100 Bq/m3 increase in radon concentration was obtained,with a positive trend of increased relative risk at above 200 Bq/m3.However,estimation of the cancer risk associated with domestic radon obtained by the pooling of multiple casecontrol studies has led to inaccuracies of the derived risk estimates in the low dose range,mainly due to smoking misclassification bias,uncertainties with respect to radon dosimetry,the histopathological characterization of lung cancers,as well as confounding by co-exposures with tobacco smoke and other indoor air pollutants.Together with a lack of biological plausibility,these deficiencies have a negative impact on the reliability of reported statistical relations between radon exposure and lung cancer at concentrations below 200 Bq/m3.It is vital that costly remedial actions to reduce domestic radon exposure are based on a scientifically robust risk assessment,and in view of aforementioned flaws,the hitherto proposed risk estimates need to be reconsidered.

De-Noising Stochastic Noise in FOG Based on Second-Generation DB4 Wavelet and SURE-Threshold

An effective de-noising method for fiber optic gyroscopes （FOGs） is proposed. This method is based on second-generation Daubechies D4 （DB4） wavelet transform （WT） and level-dependent threshold estimator called Stein＇s unbiased risk estimator （SURE）. The whole approach consists of three critical parts： wavelet decomposition module, parameters estimation module and SURE de-noising module. First, DB4 wavelet is selected as lifting base of the second-generation wavelet in the decomposition module. Second, in the parameters estimation module, maximum likelihood estimation （MLE） is used for stochastic noise parameters estimation. Third, combined with soft threshold de-noising technique, the SURE de-noising module is designed. For comparison, both the traditional universal threshold wavelet and the second-generation Harr wavelet method are also investigated. The experiment results show that the computation cost is 40% less than that of the traditional wavelet method. The standard deviation of de-noised FOG signal is 0.012 and the three noise terms such as angle random walk, bias instability and quantization noise are reduced to 0.007 2°/√h, 0.004 1° / h, and 0.008 1°, respectively.

Effects of decline in renal function with age on the outcome of asymptomatic carotid plaque in healthy adults： a 5-year follow-up study

Background It has been long suggested that abnormal clinical factors in the body, such as dyslipidemia and diabetes, can affect the presence of atherosclerosis. However, few studies on the effect of factors within the normal range, such as the loss of renal function with age, on the prevalence of atherosclerosis are few know in healthy individuals. The aim of this study was to investigate risk factors affecting the presence of asymptomatic carotid plaques in a middle-aged and elderly healthy population. Methods In this regard, we prospectively evaluated 245 healthy individuals （98 males and 147 females） at baseline and after 5 years. Changes in the presence of carotid plaque between 2003 and 2008 were categorized into four groups, i.e. subjects without plaque at entry （n=165）： Group 1 （without plaque on two occasions, n=129） and Group 2 （with nascent plaque at follow-up, n=36）; subjects with plaque at entry （n=80）; Group 3 （with plaque regression at follow-up, n=29） and Group 4 （with plaque on two occasions, n=51）. Results Univariate analysis showed that the positive rate of carotid plaques in males was higher than that in females at the baseline, and that a significantly inverse correlation existed between the prevalence rate of plaque and aging. Logistic regression analysis of cross-sectional research showed that independent risk factors for the prevalence of atherosclerosis were male gender, lower estimated glomerular filtration rate （eGFR） and higher low-density lipoprotein cholesterol （LDL-C） at the baseline, and older age and lower eGFR were involved in the presence of carotid plaques at follow-up point. However, logistic regression analysis of the longitudinal data showed that older age, decreased eGFR and increased systolic blood pressure （SBP） independently predicted the presence of carotid plaques after 5 years in subjects without plaque at entry. In addition, in subjects with plaque at entry, age, changes in eGFR and the baseline levels of serum albumin （ALB） and serum total bilirubin （BIL） dependently influenced the outcome of carotid plaque. Conclusion Physiological decline of renal function, together with advancing age, was an independent risk factor which consistently affected the presence of carotid atherosclerosis in two categories of healthy individuals.