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In this paper, the structural vibration control of short-period systems by a sliding model of a tuned liquid column damper (herein referred to as STLCD) is investigated from both theoretical and experimental points of view. The proposed STLCD is essentially composed of a U-tube container with liquid inside, which can slide on a linear guide rail and is connected to the structure by a spring-dashpot system. Unlike traditional fixed TLCDs, this type of arrangement allows the proposed STLCD to be tuned to short-period structural systems since the spring can be used for tuning while the dashpot provides additional damping. Details on the selection of the optimal design parameters of the STLCD are provided, and the validity of the introduced mathematical model is verified both in time and frequency domains through experimental tests conducted at the Laboratory of Experimental Dynamics at the University of Palermo, Italy. For the experimental tests, a scale model of an STLCD-controlled structure is considered, focusing on the reduction of the roof accelerations. Finally, for comparison purposes, the control performance of the proposed control strategy for the vibration suppression of stiff structures is evaluated by analyzing its structural responses in contrast with the corresponding uncontrolled structure under harmonic excitations. [ABSTRACT FROM AUTHOR]

Smooth power injection is one of the possible services that modern wind farms could provide in the not-so-far future, for which energy storage is required. Indeed, this is one among the three possible operations identified by the International Energy Agency (IEA)-Hydrogen Implementing Agreement (HIA) within the Task 24 final report, that may promote their integration into the main grid, in particular when paired to hydrogen-based energy storages. In general, energy storage can mitigate the inherent unpredictability of wind generation, providing that they are deployed with appropriate control algorithms. On the contrary, in the case of no storage, wind farm operations would be strongly affected, as well as their economic performances since the penalty fees wind farm owners/operators incur in case of mismatches between the contracted power and that actually delivered. This paper proposes a Model Predictive Control (MPC) algorithm that operates a Hydrogen-based Energy Storage System (HESS), consisting of one electrolyzer, one fuel cell and one tank, paired to a wind farm committed to smooth power injection into the grid. The MPC relies on Mixed-Logic Dynamic (MLD) models of the electrolyzer and the fuel cell in order to leverage their advanced features and handles appropriate cost functions in order to account for the operating costs, the potential value of hydrogen as a fuel and the penalty fee mechanism that may negatively affect the expected profits generated by the injection of smooth power. Numerical simulations are conducted by considering wind generation profiles from a real wind farm in the center-south of Italy and spot prices according to the corresponding market zone. The results show the impact of each cost term on the performances of the controller and how they can be effectively combined in order to achieve some reasonable trade-off. In particular, it is highlighted that a static choice of the corresponding weights can lead to not very effective handling of the effects given by the combination of the system conditions with the various exogenous', while a dynamic choice may suit the purpose instead. Moreover, the simulations show that the developed models and the set-up mathematical program can be fruitfully leveraged for inferring indications on the devices' sizing. [ABSTRACT FROM AUTHOR]

Abstract: Wind energy evaluation is an important goal in the conversion of energy systems to more environmentally friendly solutions. In this paper, we present a novel approach to wind speed spatial estimation on the isle of Sicily (Italy): an incremental self-organizing neural network (Generalized Mapping Regressor – GMR) is coupled with exploratory data analysis techniques in order to obtain a map of the spatial distribution of the average wind speed over the entire region. First, the topographic surface of the island was modelled using two different neural techniques and by exploiting the information extracted from a digital elevation model of the region. Then, GMR was used for automatic modelling of the terrain roughness. Afterwards, a statistical analysis of the wind data allowed for the estimation of the parameters of the Weibull wind probability distribution function. In the last sections of the paper, the expected values of the Weibull distributions were regionalized using the GMR neural network. [Copyright &y& Elsevier]

Stimulated by the recent advances in computational tools for the simulation of seismic wave propagation problems in realistic geological configurations, this paper presents a 3D physicsbased numerical analysis of near-source ground motion during the MW 6.0 2012 May 29 earthquake in the Po Plain, Northern Italy. To reproduce with sufficient accuracy some of the most peculiar features of the near-source strong-motion records and of the spatial variability of damage distribution, this study required a sequence of investigations, starting from the analysis of a wide set of near-source records, to the calibration of an improved kinematic seismic source model, up to the development of a 3D numerical model of the portion of the Po Plain interested by the earthquake. The latter includes the basin geometry, characterized by sediment thickness sharply varying from few tens of metres to some kilometres. The spatial resolution of the numerical model is suitable to propagate frequencies up to about 1.5 Hz. Numerical simulations were performed using the open-source high-performance code SPEED, based on the Discontinuous Galerkin Spectral Elements method. The 3D numerical model, coupled with the updated slip distribution along the rupturing fault, proved successful to reproduce with good agreement, measured through quantitative goodness-of-fit criteria, the most relevant features of the observed ground motion. These include: (i) the large fault normal velocity peaks at the near-source stations driven by updip directivity effects; (ii) the small-scale variability at short distance from the source, resulting in the out-of-phase motion at stations separated by only 3 km distance; (iii) the propagation of prominent trains of surface waves, especially in the Northern direction; (iv) the map of earthquake-induced ground uplift with maximum values of about 10 cm, in substantial agreement with geodetic measurements and (v) the two-lobed pattern of the peak ground velocity map, well correlated with the distribution of macroseismic intensity. [ABSTRACT FROM AUTHOR]

In this paper it was developed and tested a hydrologically based, spatially distributed crop yield model for the purpose of modeling pasture dynamics within theMediterranean environment of Marghine Goceano, in Sardinia region, Italy. The model uses daily information of weather drivers given by temperature, precipitation, and solar radiation, and provides daily spatially distributed estimates of soil water content, runoff, and pasture growth, including leaf area index (LAI) and biomass. Pasture grass growth for 6 years (2001-2006) was simulated, and yearly average biomass yield (t ha-1) was compared against ground-based and satellite-based estimates from previous studies, finding acceptable model performance. Intraseasonal biomass dynamics was evaluated during year 2004 and compared against pointwise ground measures from former studies, with acceptable results. The spatially distributed leaf area index maps were compared against their satellite-derived counterparts (9.3-km pixel size, 2005-2006), available on a biweekly basis. The pasture model provides acceptable performance in depicting daily, spatially distributed dynamics of pasture grass, and may be useful when tackling a number of issues, including, e.g., (1) assessment of pasture (and fodder) productivity under current climate and management, (2) short-term to medium-term forecast of pasture yield for seasonal herding, and (3) modified pasture conditions under prospective climate change using climate forcing from general circulation models and other climate models. Future developments may regard inclusion of nutrient dynamics and study of (over)grazing effect upon pasture dynamics. [ABSTRACT FROM AUTHOR]

Abstract: The paper presents an energy and environmental extended input–output model combined with the life cycle assessment, applied to assess the energy and environmental benefits arising from the Italian policy of tax deduction for energy retrofit actions of buildings. The study allowed to assess the advantages due to the above policy, taking into account both direct and indirect energy saving and avoided CO2 emissions obtained with the retrofit actions and indirect energy consumption and related CO2 emissions due to the realization of the above actions. Moreover, the authors defined an original model to assess the indirect rebound effect caused by the energy saving actions. The obtained results showed that a reliable evaluation of the benefits arising from sustainable policies strongly depends on the indirect rate of the energy consumption and energy saving, that in the examined case study has the same order of magnitude of the direct one, and on the rebound effect, that can partially avoid the obtained benefits. The study represents one of the first Italian experiences aimed at assessing the effectiveness of sustainable production and consumption strategies. It can be used to support decision-makers in the selection of policies aimed at reducing energy and environmental impacts caused by final consumptions. [Copyright &y& Elsevier]

The paper reports the results of a research aimed at analyzing and interpreting the cracking pattern on the Cappella dei Principi (Prince's Chapel, the Medici's mausoleum) in the Basilica of San Lorenzo (Florence, Italy). The research was motivated by the sudden collapse of a keystone of an internal barrel vault sustaining one of the lateral apses. After a brief description of the geometry of the structure, the principal results obtained from in situ surveys (flat-jack tests and cored samples) are described; then the numerical analyses developed both to obtain the static identification of the monument and to assess the possible causes leading to the observed failure are illustrated. The numerical modeling operation has been performed step by step, from linear and quite simple models built with plane elements up to a nonlinear model with three-dimensional elements. The nonlinear FEM, which has been tuned by utilizing the results of the in situ measures, is allowed to both qualitatively and quantitatively reproduce the behavior of the structure and its static problems in the area of the barrel vault over the side apses, allowing for justification of the manifested damage. The comprehension of the structural behavior allows identification of a proper retrofitting strategy. [ABSTRACT FROM AUTHOR]

Longshore sediment transport is affected by coastal structures, which cause phenomena such as the erosion and deposition of sediments. These phenomena may also occur at locations far from the coastal structure. The prediction and management of shoreline evolution are necessary to protect coasts; they should take into account both long-term and short-term effects and should consider the presence or absence of coastal structures. In this paper several models that predict shoreline evolution behind a breakwater have been analyzed. The results of the predictions have been compared with real shoreline evolution measured in the Natural Ocean Engineering Laboratory (NOEL) in Reggio Calabria, where an experiment concerning the possibility of converting wave energy into electricity using a particular device placed in a breakwater is being investigated. A breakwater was installed in March 2005 and is still there, and it has altered the natural coastal processes affecting the shoreline profile. Comparisons were made in June 2005 (3 months after the installation of the breakwater) and in September 2010. The results indicate that the shoreline profile is not symmetrical about the centerline of the structure, but the salient (the point where advancement is prominent) is displaced toward the south side such that erosion is deeper on the north side. [ABSTRACT FROM AUTHOR]

These days, security and efficiency of transportation networks are usually supported by wireless communication systems. In all cases, the radio-link reliability strongly depends on propagation properties and, therefore, effective prediction tools and models are requested in the design and planning phases of the radio system. In this paper, a mixed rays—modes approach to the propagation modeling in real tunnels is presented. The propagating field is computed as the superimposition of many characteristic modes, whose amplitudes are properly estimated thanks to a limited and, therefore, fast ray-tracing procedure; the geometrical optics rules are also used to model the main effects of the possible tunnel curvature. Moreover, an equivalent wall roughness is introduced in order to approximately account for the actual tunnel transversal shape and for the presence of inner elements and objects. The model is compared with some other different existing models and with measurements carried out inside an underground line in a neighborhood of Naples. The achieved performance is in line with the published scientific data. [ABSTRACT FROM PUBLISHER]

In this paper we attempt to measure the educational mismatch, seen as a problem of overeducation, using a multidimensional and fuzzy methodology. Educational mismatch can be difficult to measure because many factors can converge to its definition and the traditional unidimensional indicators presented in literature can offer a restricted view of the problem. We discovered two dimensions that properly define overeducation. The first includes information regarding job satisfaction, the use of expertise and the coherence between study and work, but also the measure on which the traditional indicator is based and the second concern earning aspects. We then calculate a degree of membership to the set of overeducated workers using the defined dimensions. We believe that in this manner we can partially overcome the rigidity of the traditional measures. Our findings suggested that generally women have a degree of mismatch higher than men and the graduates in Pharmacy, Medicine and Engineering are the least overeducated in terms of the first dimension, even if in terms of the earnings dimension they have similar mismatches to the other fields of education. Self-employment and collaboration contracts reduce overeducation when the first dimension is considered; on the other hand, when the second dimension is taken into account graduates with collaboration contracts are the most mismatched out of those having a job. Additionally, university reform introduced in the academic year 2001-2002 in the Italian higher education system is shown as not contributing to a reduction of the overeducation phenomenon. [ABSTRACT FROM AUTHOR]

The term 'Context Sensitive Solutions' was adopted by the Federal Highway Administration in 1997 and is a synonym of flexibility that allows the designer to balance the safety, mobility and preservation of environmental resources. When the optimal use of design criteria produces an unacceptable solution, the correct application of design value outside the current guidelines with a particular attention to safety and legal risk is needed. In this case, a feasible alternative meets the purpose of design and is considered constructible and maintainable within social, economic and environmental constraints. Unlike in many other countries, road standards in Italy do not permit to work out a simple solution to the problem of flexibility. Specifically, one of the most debated subjects, concerning the items of the Italian Ministerial Decree (MD) 5/11/2001 confer with a designer the possibility of deviating from prescriptive obligations on condition to suggest some appropriate safety analysis. However, it does not indicate any methodology to objectively quantify removal effect from the reference values established by the rule. At this purpose, the paper suggests an analytical instrument for controlling design values outside the current guidelines applying a methodology based on interval analysis, a technique generally used for managing uncertain variables. The procedure applied to designing a planimetric curve has identified the most significant variables and produced some range in which they may be retained acceptable, though outside the limits of the geometric standard. [ABSTRACT FROM AUTHOR]

Abstract: On October 9th 1963 a huge landslide fell into the Vajont artificial reservoir in Northern Italy, and displaced the water which overtopped the dam and produced a destructive wave that inundated the valley causing about 2000 casualties and complete devastation. The landslide has been the subject of many geological studies, and is one of the largest ever documented in literature. Nevertheless, only a small number of hydraulic analyses have been conducted relating the sliding motion to the consequent water waves and describing the formation of different waves and how they interfered with each other. A numerical model, capable of doing so, has not yet been presented. In this paper, a horizontal bi-dimensional finite volume model is proposed in order to study the wave generated by the Vajont landslide. We hereby introduce a moving wall reproducing the effects of the landslide. [Copyright &y& Elsevier]

Abstract: The paper addresses the issues of modelling and managing Intermodal Transportation Systems (ITS) at the operational level, considering the impact of the new Information and Communication Technologies (ICT). ITS are regarded as discrete event systems and are modelled in a timed Petri net framework. In order to show the efficiency of the ITS modelling and controlling technique, the case study of the ferry terminal of Trieste (Italy) is considered. The results show that the approach can be employed to verify the potential of ICT for efficient real time management of ITS, and their impact on the ITS infrastructures. [Copyright &y& Elsevier]

Abstract: For the generation of susceptibility maps on medium scales (1:25,000 to 1:50,000) using statistical techniques, a reliable landslide inventory is needed, together with factor maps used as inputs. This paper compares landslide susceptibility maps obtained with the same methodology but using different landslide inventories: the official Italian landslide inventory GeoIFFI for the Lombardy Region and a recently mapped inventory (DF2001). The analysis included four main steps: (i) preparation of debris flow inventories using both random and spatial partitions and factor maps as explanatory variables; (ii) calculation of accountability and reliability indices for a preliminary susceptibility analysis and selection of an appropriate combination of the factor maps for detailed analysis; (iii) evaluation and validation of the obtained susceptibility maps; and (iv) comparison of the results and selection of the final map. The study area is located in the Valtellina Valley in the Central Italian Alps. The analysis identified highly susceptible areas of shallow landslides that may generate debris flows. It was demonstrated that more precisely delimited source areas for landslide-induced debris flows produce better susceptibility maps. However, the improvement of these maps was relatively limited when the inventories were randomly subdivided. Higher improvements were observed after the subdivision of the inventories into three geographical parts with different geomorphological characteristics. Although the modelling showed very similar results if evaluation is made using standard techniques, the spatial pattern of the susceptibility maps was highly variable and dependent on the combination of the factor maps used. [Copyright &y& Elsevier]

Abstract: To evaluate the spatial variability of ozone concentrations, two studies were undertaken in the montane environment of Trentino region, northern Italy, in 2007. In the first study, a 225 km2 area was considered. Here, a randomized design was used to evaluate the variability of ozone concentration at 1 and 225 km2 scale. Measurements were carried out by passive samplers between May and June 2007. In a second study, the whole 6207 km2 area of Trentino was considered. The area is covered by five grid cells of the European Monitoring and Evaluation Programme (EMEP). A systematic 15 × 15 km grid was used to allocate 15 passive samplers over the entire province, resulting into 1–4 samplers for each of the 5 EMEP grid cells (2500 km2 each) overlapping the study area. Measurements were carried out between June and September 2007. Accuracy of passive samplers was checked by direct comparison with conventional ozone analysers. Significant differences (P = 0.034) were found in ozone concentration among 1 × 1 km quadrates within the 225 km2 study area, while variability within the 1 × 1 km grid cells (coefficient of variation, CV′ = 0.12) slightly exceed the measurement error (CV′ = 0.08). At larger scales (225, 2500 and 6207 km2), ozone concentration shows much higher variability (CV′ from 0.18 to 0.28, with peak values at 0.40). Reported differences lead to very different AOT40 estimates even within the same EMEP grid cell. These findings suggest that 1 × 1 km resolution seems appropriate for ozone concentration modelling. On the other hand, significant sub-grid variation may exist at the resolution adopted by the EMEP model. Coupled with the likely variability of other important meteorological, soil and vegetation variables, our findings suggest that ozone risk assessment for vegetation based on large-scale modelled AOT40 and flux needs to be considered with great caution. The evidence reported in this paper asks for more detailed national-scale modelling, and the development of methods to incorporate local scale variations into large-scale models. [Copyright &y& Elsevier]

Statistically distinguishing density-dependent from density-independent populations and selecting the best demographic model for a given population are problems of primary importance. Traditional approaches are PBLR (parametric bootstrapping of likelihood ratios) and Information criteria (IC), such as the Schwarz information criterion (SIC), the Akaike information criterion (AIC) or the Final prediction error (FPE). While PBLR is suitable for choosing from a couple of models, ICs select the best model from among a set of candidates. In this paper, we use the Structural risk minimization (SRM) approach. SRM is the model selection criterion developed within the Statistical learning theory (SLT), a theory of great generality for modelling and learning with finite samples. SRM is almost unknown in the ecological literature and has never been used to analyze time series. First, we compare SRM with PBLR in terms of their ability to discriminate between the Malthusian and the density-dependent Ricker model. We rigorously repeat the experiments described in a previous study and find out that SRM is equally powerful in detecting density-independence and much more powerful in detecting density-dependence. Then, we compare SRM against ICs in terms of their ability to select one of several candidate models; we generate, via stochastic simulation, a huge amount of artificial time series both density-independent and dependent, with and without exogenous covariates, using different dataset sizes, noise levels and parameter values. Our findings show that SRM outperforms traditional ICs, because generally a) it recognizes the model underlying the data with higher frequency, and b) it leads to lower errors in out-of-samples predictions. SRM superiority is specially apparent with short time series. We finally apply SRM to the population records of Alpine ibex Capra ibex living in the Gran Paradiso National Park (Italy), already investigated by other authors via traditional statistical methods; we both analyze their models and introduce some novel ones. We show that models that are best according to SRM show also the lowest leave-one-out cross-validation error. [ABSTRACT FROM AUTHOR]

Viral liver infections with parenteral transmission in Western countries are mostly caused by hepatitis B and hepatitis C viruses (HBV and HCV). This paper presents a mathematical model that describes the history of the spread of HBV and HCV infections in the general population in Italy. The analysis of the model and the results also provide some new insight into the mechanisms of the epidemics. The model structure is based on an underlying analysis of the various effects of the infection progression in the host, in order to incorporate into its parameters most of the information available from the literature. Moreover, incidence and prevalence curves of both HBV and HCV infections and of HBV/HCV co-infections are generated and qualitative aspects of the epidemic, such as possible endemic steady states and the basic reproduction number, are also analyzed. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of describing the spread of COVID-19 by a mathematical model introducing all the possible control actions as prevention (informative campaign, use of masks, social distancing, vaccination) and medication. The model adopted is similar to SEIQR, with the infected patients split into groups of asymptomatic subjects and isolated ones. This distinction is particularly important in the current pandemic, due to the fundamental the role of asymptomatic subjects in the virus diffusion. The influence of the control actions is considered in analysing the model, from the calculus of the equilibrium points to the determination of the reproduction number. This choice is motivated by the fact that the available organised data have been collected since from the end of February 2020, and almost simultaneously containment measures, increasing in typology and effectiveness, have been applied. The characteristics of COVID-19, not fully understood yet, suggest an asymmetric diffusion among countries and among categories of subjects. Referring to the Italian situation, the containment measures, as applied by the population, have been identified, showing their relation with the government's decisions; this allows the study of possible scenarios, comparing the impact of different possible choices. [ABSTRACT FROM AUTHOR]

Background: Emerging and re-emerging infectious diseases such as Zika, SARS, ncovid19 and Pertussis, pose a compelling challenge for epidemiologists due to their significant impact on global public health. In this context, computational models and computer simulations are one of the available research tools that epidemiologists can exploit to better understand the spreading characteristics of these diseases and to decide on vaccination policies, human interaction controls, and other social measures to counter, mitigate or simply delay the spread of the infectious diseases. Nevertheless, the construction of mathematical models for these diseases and their solutions remain a challenging tasks due to the fact that little effort has been devoted to the definition of a general framework easily accessible even by researchers without advanced modelling and mathematical skills. Results: In this paper we describe a new general modeling framework to study epidemiological systems, whose novelties and strengths are: (1) the use of a graphical formalism to simplify the model creation phase; (2) the implementation of an R package providing a friendly interface to access the analysis techniques implemented in the framework; (3) a high level of portability and reproducibility granted by the containerization of all analysis techniques implemented in the framework; (4) a well-defined schema and related infrastructure to allow users to easily integrate their own analysis workflow in the framework. Then, the effectiveness of this framework is showed through a case of study in which we investigate the pertussis epidemiology in Italy. Conclusions: We propose a new general modeling framework for the analysis of epidemiological systems, which exploits Petri Net graphical formalism, R environment, and Docker containerization to derive a tool easily accessible by any researcher even without advanced mathematical and computational skills. Moreover, the framework was implemented following the guidelines defined by Reproducible Bioinformatics Project so it guarantees reproducible analysis and makes simple the developed of new user-defined workflows. [ABSTRACT FROM AUTHOR]

The Piedmont Region in NW Italy has recently deployed an ambitious and pioneering agricultural water pricing reform aimed at integrating and effectively enforcing EU's Water Framework Directive principles of cost recovery, polluter-pays and affordability. This paper develops a multi-model ensemble framework encompassing 5 mathematical programming models (2 Positive Mathematical Programming models, 2 Positive Multi-Attribute Utility Programming models and 1 Weighted Goal Programming model) that represent the observed behavior of socioeconomic agents to: 1) simulate the impacts of the Piedmontese water pricing reform on land use allocation and management, water conservation, profit and water tariff revenue; 2) sample modeling uncertainty through the ensemble spread; and 3) explore potential tipping points through use of scenario-discovery techniques. Our research suggests that the key challenge to the reform lies in the management of rice fields, an extensive (17% of the agricultural area), water-demanding and relatively low-added-value crop that nonetheless delivers significant ecosystem services (e.g. water retention) of historical and cultural relevance to the region. The ensemble experiment suggests that rice agriculture rapidly dwindles in the price range 0.012–0.074 EUR/m3 depending on the model. Before reaching this tipping point, agricultural water pricing can reduce withdrawals up to 1.7%–9.5%, while reducing profit between 4.9% and 5.6% and achieving a 57- to 65-fold increase in water tariff revenue. • We combine a multi-model ensemble experiment with scenario discovery techniques. • Our approach samples modeling and scenario uncertainty to identify tipping points. • Our approach is illustrated using the agricultural water pricing in Piedmont (IT). • Results show historical rice fields dwindle in the price range 0.014–0.074 EUR/m3. • Conserving rice fields considerably limits pricing water conservation potential. [ABSTRACT FROM AUTHOR]

The relationship between tourist demand and supply is investigated employing four time series models. To test for Granger causality a bivariate vector autoregression framework is used. Empirical results from each model are derived for the island of Sardinia (Italy) over the time span 1955 to 2004. The first model suggests supply is demand-driven; the second model implies a bi-directional Granger-causal relationship between demand and capacity. The third and fourth models indicate demand is quality-driven. This empirical finding implies that an environmental conservation policy may be feasible without compromising the number of tourists visiting Sardinia and hence its economic growth. [ABSTRACT FROM AUTHOR]

Background: Varicella is a highly infectious disease with a significant public health and economic burden, which can be prevented with childhood routine varicella vaccination. Vaccination strategies differ by country. Some factors are known to play an important role (number of doses, coverage, dosing interval, efficacy and catch-up programmes), however, their relative impact on the reduction of varicella in the population remains unclear. This paper aims to help policy makers prioritise the critical factors to achieve the most successful vaccination programme with the available budget.Methods: Scenarios assessed the impact of different vaccination strategies on reduction of varicella disease in the population. A dynamic transmission model was used and adapted to fit Italian demographics and population mixing patterns. Inputs included coverage, number of doses, dosing intervals, first-dose efficacy and availability of catch-up programmes, based on strategies currently used or likely to be used in different countries. The time horizon was 30 years.Results: Both one- and two-dose routine varicella vaccination strategies prevented a comparable number of varicella cases with complications, but two-doses provided broader protection due to prevention of a higher number of milder varicella cases. A catch-up programme in susceptible adolescents aged 10-14 years old reduced varicella cases by 27-43 % in older children, which are often more severe than in younger children. Coverage, for all strategies, sustained at high levels achieved the largest reduction in varicella. In general, a 20 % increase in coverage resulted in a further 27-31 % reduction in varicella cases. When high coverage is reached, the impact of dosing interval and first-dose vaccine efficacy had a relatively lower impact on disease prevention in the population. Compared to the long (11 years) dosing interval, the short (5 months) and medium (5 years) interval schedules reduced varicella cases by a further 5-13 % and 2-5 %, respectively. Similarly, a 10 % increase in first-dose efficacy (from 65 to 75 % efficacy) prevented 2-5 % more varicella cases, suggesting it is the least influential factor when considering routine varicella vaccination.Conclusions: Vaccination strategies can be implemented differently in each country depending on their needs, infrastructure and healthcare budget. However, ensuring high coverage remains the critical success factor for significant prevention of varicella when introducing varicella vaccination in the national immunisation programme. [ABSTRACT FROM AUTHOR]