Universal risk phenotype of US counties for flu-like transmission to improve county-specific COVID-19 incidence forecasts

The spread of a communicable disease is a complex spatio-temporal process shaped by the specific transmission mechanism, and diverse factors including the behavior, socio-economic and demographic properties of the host population. While the key factors shaping transmission of influenza and COVID-19 are beginning to be broadly understood, making precise forecasts on case count and mortality is still difficult. In this study we introduce the concept of a universal geospatial risk phenotype of individual US counties facilitating flu-like transmission mechanisms. We call this the Universal Influenza-like Transmission (UnIT) score, which is computed as an information-theoretic divergence of the local incidence time series from an high-risk process of epidemic initiation, inferred from almost a decade of flu season incidence data gleaned from the diagnostic history of nearly a third of the US population. Despite being computed from the past seasonal flu incidence records, the UnIT score emerges as the dominant factor explaining incidence trends for the COVID-19 pandemic over putative demographic and socio-economic factors. The predictive ability of the UnIT score is further demonstrated via county-specific weekly case count forecasts which consistently outperform the state of the art models throughout the time-line of the COVID-19 pandemic. This study demonstrates that knowledge of past epidemics may be used to chart the course of future ones, if transmission mechanisms are broadly similar, despite distinct disease processes and causative pathogens.

Succession as a Risk Process in the Survival of a Family Business—Case of Slovakia

Generational transfer is a risky point in the life cycle of any family business, and thus the succession process should not be underestimated. Family businesses in Slovakia began to appear after 1989, and therefore many of them await the process of generational exchange in the coming years. For this reason, research on generational exchange has been limited. The aim of this paper was to evaluate the attitude of the owners of Slovak family businesses to the succession process and to reveal the key factors that positively or negatively affect this process. A semi-structured interview was selected as a tool for data collection, in which 74 family business owners took part. The findings were evaluated by the text mining method and afterwards transferred to a scatter diagram in concepts. Based on the clusters in the scatter plot, we revealed the key factors that the current owners consider to be a risk in successfully managing generational exchange. We found that only 48.64% of owners started the succession process, which proves the importance of solving the problem in Slovakia.

Application of Dynamic Risk Approach to Mitigate Major Accidents

Major industrial accidents with catastrophic consequences routinely occur around the world and as the industry continue to grow, so will the system complexities and uncertainties. Hence, the need for a more dynamic approach to hazards identification and risk management, to proactively mitigate potential exposures in a real-time manner. Evidences suggests that, dynamic approach to risk management is capable to identifying and assessing developing and increasing industry risks and processes. The Piper Alpha investigation and derivation and adoption of safety case framework in the UK, was a proven approach to mitigate Major Accident Hazards on the front-end design of high-risk process facilities and through their lifespan. With increasing process systems complexities however, dynamic risk management an enhanced conventional method would be the next generation approach to ensure safer operations. This paper aims to stimulate discussions on the novel Dynamic Risk Management (DRM) approach, leveraging on advanced technologies such as Artificial Intelligence (AI) and the 4th Industrial Revolution (4IR) as a new risk management pathway to industrial accident prevention.

Using Failure Mode, Effect and Criticality Analysis to Improve Safety in the COVID Mass Vaccination Campaign

Vaccination against SARS-CoV-2 will likely be the most promising way to combat the pandemic. Even if mass vaccination is urgent, it should still always be supported by appropriate patient safety management. The aim of this study, based on failure mode, effects and criticality analysis (FMECA), was to identify possible failures and highlight measures that can be adopted to prevent their occurrence. A team of resident doctors in public health from the University of Padua and specialists in risk analysis in public health examined the mass vaccination process. A diagram was drafted to illustrate the various phases of mass vaccination, analyze the process, and identify all failure modes. Criticalities were ascertained by rating the severity, frequency and likelihood of failure detection on a scale of 1 to 10. We identified a total of 71 possible faults distributed over the various phases of the process, and 34 of them were classified as carrying a high risk. For the potentially high-risk failure modes, we identified 63 recommended actions to contain the cause of their occurrence or improve their detection. For the purpose of detecting potential failures, FMECA can be successfully applied to mass vaccination, which should be considered a high-risk process.

Risk Analysis of the Copula Dependent Aggregate Discounted Claims with Weibull Inter-Arrival Time

We model the recursive moments of aggregate discounted claims, assuming the inter-claim arrival time follows a Weibull distribution to accommodate overdispersed and underdispersed data set. We use a copula to represent the dependence structure between the inter-claim arrival time and its subsequent claim amount. We then use the Laplace inversion via the Gaver-Stehfest algorithm to solve numerically the first and second moments, which takes the form of a Volterra integral equation (VIE). We compute the average and variance of the aggregate discounted claims under the Farlie-Gumbel-Morgenstern (FGM) copula and conduct a sensitivity analysis under various Weibull inter-claim parameters and claim-size parameters. The comparison between the equidispersed, overdispersed and underdispersed counting processes shows that when claims arrive at times that vary more than is expected, insured lives can expect to pay higher premium, and vice versa for the case of claims arriving at times that vary less than expected. Upon comparing the Weibull risk process with an equivalent Poisson process, we also found that copulas with a wider range of dependency parameter such as the Frank and Heavy Right Tail (HRT), have a greater impact on the value of moments as opposed to modeling under FGM copula with weak dependence structure.

Monte Carlo Simulation of the Moments of a Copula-Dependent Risk Process with Weibull Interwaiting Time

The widely used Poisson count process in insurance claims modeling is no longer valid if the claims occurrences exhibit dispersion. In this paper, we consider the aggregate discounted claims of an insurance risk portfolio under Weibull counting process to allow for dispersed datasets. A copula is used to define the dependence structure between the interwaiting time and its subsequent claims amount. We use a Monte Carlo simulation to compute the higher-order moments of the risk portfolio, the premiums and the value-at-risk based on the New Zealand catastrophe historical data. The simulation outcomes under the negative dependence parameter θ, shows the highest value of moments when claims experience exhibit overdispersion. Conversely, the underdispersed scenario yields the highest value of moments when θ is positive. These results lead to higher premiums being charged and more capital requirements to be set aside to cope with unfavorable events borne by the insurers.

Merton Investment Problems in Finance and Insurance for the Hawkes-Based Models

We show how to solve Merton optimal investment stochastic control problem for Hawkes-based models in finance and insurance (Propositions 1 and 2), i.e., for a wealth portfolio X(t) consisting of a bond and a stock price described by general compound Hawkes process (GCHP), and for a capital R(t) (risk process) of an insurance company with the amount of claims described by the risk model based on GCHP. The main approach in both cases is to use functional central limit theorem for the GCHP to approximate it with a diffusion process. Then we construct and solve Hamilton–Jacobi–Bellman (HJB) equation for the expected utility function. The novelty of the results consists of the new Hawkes-based models and in the new optimal investment results in finance and insurance for those models.

ECONOMIC EFFICIENCY ASSESSMENT OF GEOLOGICAL EXPLORATION WORKS IN THE PROCESS OF GEOLOGICAL EXPLORATION OF SUBSURFACE RESOURCES

The relevance of the economic assessment of the effectiveness of geological exploration works in the process of geological exploration of the subsurface resources consists not only in the need to ensure the stages of the geological exploration process, but also in the need to increase the reliability of the economic assessment of the effectiveness of geological exploration works in the process of geological exploration of the subsurface resources. As practice shows, it is the geological study of the subsurface that is the most expensive and high-risk process, the effectiveness of which largely depends on the ability to estimate the costs of increasing reserves with the greatest accuracy, especially in terms of industrial categories. Therefore, it is necessary to develop a methodology for evaluating the effectiveness of geological exploration, the use of which would allow estimating costs and results at the planning stage. The quality of geological exploration works at the object is determined by the increment of the initial geological and economic information. The greatest risks when performing geological exploration works arise when interacting between the state customer of geological exploration works at the early stages of geological exploration and geological organizations performing works under state contracts. As a result, a method of economic evaluation of the efficiency of geological exploration works in the process of geological exploration of the subsurface was proposed, which was tested on solid minerals, using the example of the Central Federal District.