Probiotics in the prevention of clinical manifestations of common infectious diseases in children and in the elderly

Infectious diseases put an enormous burden on both children and the elderly in the forms of respiratory, gastrointestinal and oral infections. There is evidence suggesting that specific probiotics may be antagonistic to pathogens and may enhance the immune system, but the clinical evidence is still too sparce to make general conclusions on the disease-preventive effects of probiotics. This thesis, consisting of four independent, double-blind, placebo-controlled clinical trials, investigated whether Lactobacillus GG (LGG) or a specific probiotic combination containing LGG would reduce the risk of common infections or the prevalence of pathogens in healthy and infection-prone children and in independent and institutionalised elderly people. In healthy day-care children, the 7-month consumption of probiotic milk containing Lactobacillus GG appeared to postpone the first acute respiratory infection (ARI) by one week (p=0.03, adjusted p=0.16), and to reduce complicated infections (39% vs. 47%, p<0.05, adjusted p=0.13), as well as the need for antibiotic treatment (44% vs. 54%, p=0.03, adjusted p=0.08) and day-care absences (4.9 vs. 5.8 days, p=0.03, adjusted p=0.09) compared to the placebo milk. In infection-prone children, the 6-month consumption of a combination of four probiotic bacteria (LGG, L. rhamnosus LC705, Propionibacterium freudenreichii JS, Bifidobacterium breve 99) taken in capsules appeared to reduce recurrent ARIs (72% vs. 82%, p<0.05; adjusted p=0.06), and the effect was particularly noticeable in a subgroup of children with allergic diseases (12% vs. 33%, p=0.03), although no effect on the presence of nasopharyngeal rhinovirus or enterovirus was seen. The 5-month consumption of the same probiotic combination did not show any beneficial effects on the respiratory infections in frail, institutionalised elderly subjects. In healthy children receiving Lactobacillus GG, the reduction in complications resulted in a marginal reduction in the occurrence of acute otitis media (AOM) (31% vs. 39%, p=0.08; adjusted p=0.19), and the postponement of the first AOM episode by 12 days (p=0.04; adjusted p=0.09). However, in otitis-prone children, a probiotic combination did not reduce the occurrence of AOM or the total prevalence of common AOM pathogens (Streptococcus pneumoniae, Haemophilus influenzae, Moraxella catarrhalis), except in the case of children with allergic diseases, in whom probiotics reduced recurrent AOM episodes (0% vs. 14%, p=0.03). In addition, interaction between probiotics and bacterial carriage was seen: probiot-ics reduced AOM in children who did not carry any bacterial pathogens (63% vs. 83%), but the effect was the reverse in children carrying bacteria in the nasopharynx (74% vs 62%) (p<0.05). Long-term probiotic treatment, either LGG given in milk to healthy children for 7 months or a combination of probiotics given in capsules to institutionalised elderly subjects for 5 months, did not reduce the occurrence of acute diarrhoea. However, when the probiotic combination (LGG, L. rhamnosus LC705, Propionibacterium JS) was given in cheese to independent elderly subjects for 4 months, the oral carriage of high Candida counts was reduced in the probiotic group vs. the placebo group (21% vs. 34%, p=0.01, adjusted p=0.004). The risk of hyposalivation was also reduced in the probiotic group (p=0.05). In conclusion, probiotics appear to slightly alleviate the severity of infections by postponing their appearance, by reducing complications and the need for antimicrobial treatments. In addition, they appear to prevent recurrent infections in certain subgroups of children, such as in infection-prone children with allergic diseases. Alleviating ARI by probiotics may lead to a marginal reduction in the occurrence of AOM in healthy children but not in infection-prone children with disturbed nasopharyngeal microbiota. On the basis of these results it could be supposed that Lactobacillus GG or a specific combination containing LGG are effective against viral but not against bacterial otitis, and the mechanism is probably mediated through the stimulation of the immune system. A specific probiotic combination does not reduce respiratory infections in frail elderly subjects. Acute diarrhoea, either in children or in the elderly, is not prevented by the continuous, long-term consumption of probiotics, but the consumption of a specific probiotic combination in a food matrix is beneficial to the oral health of the elderly, through the reduction of the carriage of Candida.

Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Exploiting ground-based measurements of the Global Positioning System for numerical weather prediction

Data assimilation provides an initial atmospheric state, called the analysis, for Numerical Weather Prediction (NWP). This analysis consists of pressure, temperature, wind, and humidity on a three-dimensional NWP model grid. Data assimilation blends meteorological observations with the NWP model in a statistically optimal way. The objective of this thesis is to describe methodological development carried out in order to allow data assimilation of ground-based measurements of the Global Positioning System (GPS) into the High Resolution Limited Area Model (HIRLAM) NWP system. Geodetic processing produces observations of tropospheric delay. These observations can be processed either for vertical columns at each GPS receiver station, or for the individual propagation paths of the microwave signals. These alternative processing methods result in Zenith Total Delay (ZTD) and Slant Delay (SD) observations, respectively. ZTD and SD observations are of use in the analysis of atmospheric humidity. A method is introduced for estimation of the horizontal error covariance of ZTD observations. The method makes use of observation minus model background (OmB) sequences of ZTD and conventional observations. It is demonstrated that the ZTD observation error covariance is relatively large in station separations shorter than 200 km, but non-zero covariances also appear at considerably larger station separations. The relatively low density of radiosonde observing stations limits the ability of the proposed estimation method to resolve the shortest length-scales of error covariance. SD observations are shown to contain a statistically significant signal on the asymmetry of the atmospheric humidity field. However, the asymmetric component of SD is found to be nearly always smaller than the standard deviation of the SD observation error. SD observation modelling is described in detail, and other issues relating to SD data assimilation are also discussed. These include the determination of error statistics, the tuning of observation quality control and allowing the taking into account of local observation error correlation. The experiments made show that the data assimilation system is able to retrieve the asymmetric information content of hypothetical SD observations at a single receiver station. Moreover, the impact of real SD observations on humidity analysis is comparable to that of other observing systems.

On the behaviour of some physical parameterization methods in high-resolution numerical weather prediction models

Modern-day weather forecasting is highly dependent on Numerical Weather Prediction (NWP) models as the main data source. The evolving state of the atmosphere with time can be numerically predicted by solving a set of hydrodynamic equations, if the initial state is known. However, such a modelling approach always contains approximations that by and large depend on the purpose of use and resolution of the models. Present-day NWP systems operate with horizontal model resolutions in the range from about 40 km to 10 km. Recently, the aim has been to reach operationally to scales of 1 4 km. This requires less approximations in the model equations, more complex treatment of physical processes and, furthermore, more computing power. This thesis concentrates on the physical parameterization methods used in high-resolution NWP models. The main emphasis is on the validation of the grid-size-dependent convection parameterization in the High Resolution Limited Area Model (HIRLAM) and on a comprehensive intercomparison of radiative-flux parameterizations. In addition, the problems related to wind prediction near the coastline are addressed with high-resolution meso-scale models. The grid-size-dependent convection parameterization is clearly beneficial for NWP models operating with a dense grid. Results show that the current convection scheme in HIRLAM is still applicable down to a 5.6 km grid size. However, with further improved model resolution, the tendency of the model to overestimate strong precipitation intensities increases in all the experiment runs. For the clear-sky longwave radiation parameterization, schemes used in NWP-models provide much better results in comparison with simple empirical schemes. On the other hand, for the shortwave part of the spectrum, the empirical schemes are more competitive for producing fairly accurate surface fluxes. Overall, even the complex radiation parameterization schemes used in NWP-models seem to be slightly too transparent for both long- and shortwave radiation in clear-sky conditions. For cloudy conditions, simple cloud correction functions are tested. In case of longwave radiation, the empirical cloud correction methods provide rather accurate results, whereas for shortwave radiation the benefit is only marginal. Idealised high-resolution two-dimensional meso-scale model experiments suggest that the reason for the observed formation of the afternoon low level jet (LLJ) over the Gulf of Finland is an inertial oscillation mechanism, when the large-scale flow is from the south-east or west directions. The LLJ is further enhanced by the sea-breeze circulation. A three-dimensional HIRLAM experiment, with a 7.7 km grid size, is able to generate a similar LLJ flow structure as suggested by the 2D-experiments and observations. It is also pointed out that improved model resolution does not necessary lead to better wind forecasts in the statistical sense. In nested systems, the quality of the large-scale host model is really important, especially if the inner meso-scale model domain is small.

Studies on orographic effects in a numerical weather prediction model

Numerical models, used for atmospheric research, weather prediction and climate simulation, describe the state of the atmosphere over the heterogeneous surface of the Earth. Several fundamental properties of atmospheric models depend on orography, i.e. on the average elevation of land over a model area. The higher is the models' resolution, the more the details of orography directly influence the simulated atmospheric processes. This sets new requirements for the accuracy of the model formulations with respect to the spatially varying orography. Orography is always averaged, representing the surface elevation within the horizontal resolution of the model. In order to remove the smallest scales and steepest slopes, the continuous spectrum of orography is normally filtered (truncated) even more, typically beyond a few gridlengths of the model. This means, that in the numerical weather prediction (NWP) models, there will always be subgridscale orography effects, which cannot be explicitly resolved by numerical integration of the basic equations, but require parametrization. In the subgrid-scale, different physical processes contribute in different scales. The parametrized processes interact with the resolved-scale processes and with each other. This study contributes to building of a consistent, scale-dependent system of orography-related parametrizations for the High Resolution Limited Area Model (HIRLAM). The system comprises schemes for handling the effects of mesoscale (MSO) and small-scale (SSO) orographic effects on the simulated flow and a scheme of orographic effects on the surface-level radiation fluxes. Representation of orography, scale-dependencies of the simulated processes and interactions between the parametrized and resolved processes are discussed. From the high-resolution digital elevation data, orographic parameters are derived for both momentum and radiation flux parametrizations. Tools for diagnostics and validation are developed and presented. The parametrization schemes applied, developed and validated in this study, are currently being implemented into the reference version of HIRLAM.