Modeling a flexible staff scheduling problem in the Era of Covid-19.

In this paper, we propose optimization models to address flexible staff scheduling problems and some main issues arising from efficient workforce management during the Covid-19 pandemic. The adoption of precautionary measures to prevent the pandemic from spreading has raised the need to rethink quickly and effectively the way in which the workforce is scheduled, to ensure that all the activities are conducted in a safe and responsible manner. The emphasis is on novel optimization models that take into account demand requirements, employees' personal and family responsibilities, and anti-Covid-19 measures at the same time. It is precisely considering the anti-Covid-19 measures that the models allow to define the working mode to be assigned to the employees: working remotely or on-site. The last optimization model, which can be viewed as the most general and the most flexible formulation, has been developed to capture the specificity of a real case study of an Italian University. In order to improve employees' satisfaction and ensure the best work/life balance possible, an alternative partition of a workday into shifts to the usual two shifts, morning and afternoon, is proposed. The model has been tested on real data provided by the Department of Mechanical, Energy and Management Engineering, University of Calabria, Italy. The computational experiments show good performance and underline the potentiality of the model to handle worker safety requirements and practicalities and to ensure work activities continuity. In addition, the non-cyclic workforce policy, based on the proposed workday organization, is preferred by employees, since it allows them to better meet their needs.

The Relevance of Topology in Parallel Simulation of Biological Networks.

Important achievements in traditional biology has deepened the knowledge about living systems leading to an extensive identification of parts-list of the cell as well as of the interactions among biochemical species responsible for cell's regulation. Such an expanding knowledge also introduces new issues. For example the increasing comprehension of the inter- dependencies between pathways (pathways cross-talk) has resulted, on one hand, in the growth of informational complexity, on the other, in a strong lack of information coherence. The overall grand challenge remains unchanged: to be able to assemble the knowledge of every 'piece' of a system in order to figure out the behavior of the whole (integrative approach). In light of these considerations high performance computing plays a fundamental role in the context of in-silico biology. Stochastic simulation is a renowned analysis tool, which, although widely used, is subject to stringent computational requirements, in particular when dealing with heterogeneous and high dimensional systems. Here we introduce and discuss a methodology aimed at alleviating the burden of simulating complex biological networks. Such a method, which springs from graph theory, is based on the principle of fragmenting the computational space of a simulation trace and delegating the computation of fragments to a number of parallel processes.

Operational research in the management of the operating theatre: a survey.

Operating theatre represents one of the most critical and expensive hospital resources since a high percentage of the hospital admissions is due to surgical interventions. The main objectives are to guarantee the optimal utilization of medical resources, the delivery of surgery at the right time, the maximisation of profitability (i.e., patient flow) without incurring additional costs or excessive patient waiting time. The operating theatre management is a process very complex: the use of mathematical and simulation models, and quantitative techniques plays, thus a crucial role. The main aim of this paper is to provide a structured literature review on how Operational Research can be applied to the surgical planning and scheduling processes. A particular attention is on the published papers that present the most interesting mathematical (optimization and simulation) models and solution approaches developed to address the problems arising in operating theatres. Directions for future researches are also highlighted.

An optimal decision making model for supporting week hospital management.

Week Hospital is an innovative inpatient health care organization and management, by which hospital stay services are planned in advance and delivered on week-time basis to elective patients. In this context, a strategic decision is the optimal clinical management of patients, and, in particular, devising efficient and effective admission and scheduling procedures, by tackling different requirements such as beds' availability, diagnostic resources, and treatment capabilities. The main aim is to maximize the patient flow, by ensuring the delivery of all clinical services during the week. In this paper, the optimal management of Week Hospital patients is considered. We have developed and validated an innovative integer programming model, based on clinical resources allocation and beds utilization. In particular, the model aims at scheduling Week Hospital patients' admission/discharge, possibly reducing the length of stay on the basis of an available timetable of clinical services. The performance of the model has been evaluated, in terms of efficiency and robustness, by considering real data coming from a Week Hospital Rheumatology Division. The experimental results have been satisfactory and demonstrate the effectiveness of the proposed approach.

Taming the complexity of biological pathways through parallel computing.

Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system of ordinary differential equations (ODEs) or the simulation of a stochastic model, is commonly computed in a centralised fashion. In recent times, research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this article, we present a survey on the progresses of such parallelisation efforts describing the most promising results so far obtained.

Beneficial effects of iodized salt prophylaxis on thyroid volume in an iodine deficient area of southern Italy.

OBJECTIVE AND SUBJECTS: Goitre prevalence in school-age children is an indicator of the severity of iodine deficiency disorders (IDD) in an endemic area. The aims of the present study were (i) to provide ultrasound thyroid volume (TV) reference values in a healthy population of school-children aged 11-14 year living in iodine-sufficient areas of Calabria region (ii) to assess both goitre prevalence and urinary iodine (UI) concentration in all children aged 11-14 year from four mildly iodine-deficient areas in which we have carried out a program of salt iodization and (iii) to evaluate the efficacy of the iodoprophylaxis in an adult population living in a small village of the same endemic area. DESIGN: Cross-sectional and prospective studies. METHODS: TV was assessed by ultrasonography and iodine intake was estimated by measuring iodine excretion in spot urine samples. Results We provided the ultrasound normal reference values as a function of age and body surface area, which displayed significant differences from those recommended by the World Health Organization. By adopting local criteria, the prevalence of goitre in children ranged from 23.4% to 27.7% normalized for age and body surface area, respectively, while the UI excretion was < 100 microg/l in 38% of subjects studied. In an adult population living in the same endemic area, goitre prevalence was lowest in the 18-27-year-old age group, and increased progressively with age. CONCLUSION: We propose for the first time local reference ultrasound values for TV in a population of 11-14-year-old school-children that should be used for monitoring IDDs and have demonstrated the beneficial effects of iodoprophylaxis in consistent with reduced goitre prevalence in children and in the young adult population studied.