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Primary care physicians played an important role in the global response during the COVID-19 pandemic, but with the absence of laboratory and diagnostics services, the move to telehealth and the focus on respiratory assessment, they faced increased uncertainty when making clinical decisions. This paper aims to examine the impact of the pandemic on decisions made by primary care physicians, as measured by referrals to chest X-ray and laboratory tests and by prescriptions of antibiotics. We conducted a retrospective study of all visits recorded with fever or cough, presenting to 209 community clinics in Southern Israel during the years 2018–2022. We describe changes in outcome rates across time and use multivariate generalised linear mixed effects model to compare the odds of referrals and prescriptions between periods, while accounting for gender, age, clinic sector, visit type, diagnosis, and season. In total, 609,823 visits to primary care physicians complied with the cohort definitions. Social restrictions were associated with a decline in all measured outcomes for primary care physician decisions, most prominently among ages 20-59, for throat culture referral during the first lockdown (OR = 0.46) and for cephalosporine prescription during the second lockdown (OR = 0.55). This trend persisted following the cancellation of the restrictions. Despite higher uncertainty during the COVID-19 social restrictions, the overall course of clinical decision-making processes was maintained, and was associated with a reduction in the use of auxiliary resources, which can improve the quality of patient care by lowering costs and supporting prevention of future antibiotics resistance. [ABSTRACT FROM AUTHOR]

The aim of the article is to designate catalogues of typological disruption as an inherent element of supply chain management in the light of uncertainty conditions. By means of deduction, the typological characteristics of the disruption and the catalogue of management decisions were determined. In this way, the scope of theoretical knowledge based on the theory of risk and supply chain management was expanded by leading the discourse towards the location of the so-called required uncertainty in the canon of obligatory components of management strategies. The article presents an overview discourse leading to the conclusion that contemporary supply chain management requires at least an attempt to forecast the effects of uncertainty conditions, including the risk of disruption. [ABSTRACT FROM AUTHOR]

We consider the construction of an adaptive algorithm for solving a boundary value problem ensuring that a trajectory issuing from some point hits a finite-size target at a given time under partial uncertainty in the disturbance field. Although the disturbance field has a component that is unknown in explicit form but is still important for hitting a target of given size, we have constructed an iteration procedure for solving the problem in finitely many steps under a number of conditions. The algorithm is based on trial trajectories and uses the measurement of their deviations from the target center as a feedback; this proves sufficient to compensate for the incompleteness of information about the external disturbance field. [ABSTRACT FROM AUTHOR]

Interval analysis procedures are used to estimate the parameters of an experimental chemical process under conditions of noise and uncertainty in the probabilistic characteristics of the measurement errors for a small measurement sample. Interval analysis makes it possible to describe exactly the set of admissible values of the estimated parameters needed for correct organization of the technological process through a correct choice of its parameters. Approximate estimates of the parameters are obtained by formal application of a statistical approach and it is shown that in this case the standard statistical approach yields essentially meaningless estimates for the parameters of the process studied here. [ABSTRACT FROM AUTHOR]

In the present paper, the types of decisions being taken at the top management level of a company, aim at its development and its manifestation on the competitive market, in the long run. These strategic decisions are adopted more in the conditions of risk and uncertainty determined by the forecast of market evolution. [ABSTRACT FROM AUTHOR]

A numerical method to solve a general random linear parabolic equation where the diffusion coefficient, source term, boundary and initial conditions include uncertainty, is developed. Diffusion equations arise in many fields of science and engineering, and, in many cases, there are uncertainties due to data that cannot be known, or due to errors in measurements and intrinsic variability. In order to model these uncertainties the corresponding parameters, diffusion coefficient, source term, boundary and initial conditions, are assumed to be random variables with certain probability distributions functions. The proposed method includes finite difference schemes on the space variable and the differential transformation method for the time. In addition, the Monte Carlo method is used to deal with the random variables. The accuracy of the hybrid method is investigated numerically using the closed form solution of the deterministic associated equation. Based on the numerical results, confidence intervals and expected mean values for the solution are obtained. Furthermore, with the proposed hybrid method numerical-analytical solutions are obtained. [ABSTRACT FROM AUTHOR]

The article deals with the analysis of the researches conducted in the field of the air traffic flow and capacity management in terminal control areas under uncertainty conditions. Traffic flows indicators, uncertainty factors and air traffic flow management in terminal control areas have been reviewed. Principles of improvement of air traffic flow and capacity management in terminal control areas have been analysed and conclusions regarding Ukrainian aeronautical system have been proposed. [ABSTRACT FROM AUTHOR]