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PubMed2006

Climate variability and forecasting surface water recovery from acidification: modelling drought-induced sulphate release from wetlands.

Climate-induced drought events have been shown to have a significant influence on sulphate (SO(4)(2-)) export from forested catchments in central Ontario, subsequently delaying recovery of surface waters from acidification. Field and modelling studies have demonstrated that water table drawdown during drought periods promotes oxidation of previously stored (reduced) sulphur (S) compounds in wetlands, with subsequent efflux of SO(4)(2-) upon re-wetting. Although climate-induced changes in processes are generally not integrated into soil-acidification models, MAGIC (Model of Acidification of Groundwater in Catchments) includes a wetland compartment that incorporates redox processes driven by drought events. The potential confounding influence of climate-induced drought events on acidification recovery at Plastic Lake, south-central Ontario (under proposed future S emission reductions) was investigated using MAGIC and two climate scenarios: monthly precipitation and runoff based on long-term means (average-climate scenario), and variable precipitation and runoff based on the past 20 years of observed monthly data (variable-climate scenario). The variable-climate scenario included several periods of summer drought owing to lower than average rainfall and higher then average temperature. Nonetheless, long-term regional trends in precipitation and temperature suggest that the variable-climate scenario may be a conservative estimate of future climate. The average-climate scenario indicated good recovery potential with acid neutralising capacity (ANC) reaching approximately 40 micromol(c)L(-1) by 2020 and 50 micromol(c)L(-1) by 2080. In contrast, the forecasted recovery potential under the variable-climate scenario was very much reduced. By 2080, ANC was forecasted to increase to 2.6 micromol(c)L(-1) from -10.0 micromol(c)L(-1) in 2000. Elevated SO(4)(2-) efflux following drought events (introduced under the variable-climate scenario) has a dramatic impact on simulated future surface water chemistry. The results clearly demonstrate that prediction of future water quality, using models such as MAGIC, should take into account changes or variability in climate as well as acid deposition.

Acid Rain↗

PubMed1995

Nonlinear forecasting and the dynamics of cardiac rhythm.

Since the initial development of the electrocardiogram, cardiologists have made dramatic advances in the description and understanding of cardiac arrhythmias. Despite these successes, the analysis of cardiac rhythm has remained largely descriptive. Recently, the principles of nonlinear dynamics, or chaos theory, have been applied to the quantitative analysis of cardiac rhythm in a variety of diverse situations. In chaos theory, three types of signals can be defined: periodic signals, which repeat themselves over some finite time interval, chaotic signals, which, while deterministic, demonstrate complex behavior and do not repeat themselves, and random signals, which are unpredictable and nondeterministic. The technique of nonlinear forecasting defines trajectories in a suitably defined phase space and uses the future evolution of trajectories that are close to each other over short distances to make predictions for times further into the future. The ability to reliably predict the future evolution of the trajectories derived from any signal is an important characteristic of the underlying dynamics of the signal and can therefore used to determine those dynamics. The foundation of nonlinear forecasting is reviewed, and an algorithm is described that can be used to determine the underlying dynamics of a signal and has been applied to the analysis of R-R interval data.

Algorithms↗

PubMed2001

Using forecasting models to estimate the effects of changes in the composition of claims for selective serotonin reuptake inhibitors on expenditures.

BACKGROUND: The use of selective serotonin reuptake inhibitors (SSRIs) as antidepressant therapy has increased considerably since the introduction of fluoxetine in 1989. By 1999, 3 of the 4 available SSRIs were among the top 10 most frequently used drugs in the United States. In addition, SSRIs were one of the major contributors to the growth in psychotropic medication expenditures during the past 5 years. OBJECTIVE: The purpose of this article was to examine the utilization patterns of the 4 most commonly used SSRIs and their contribution to rising antidepressant medication expenditures among claimants in a publicly funded drug program. Using the results of forecasting models, we explored possible ways to control these growing expenditures. METHODS: Cross-sectional antidepressant claims and expenditure data from the Ontario Drug Benefits program for 1992 to 1998 were examined. Five scenarios were modeled in which future SSRI expenditures and claims were predicted using exponential smoothing models. RESULTS: If the historical patterns of use continued, a 20% increase in the 1998 level of expenditures was expected to occur by the year 2000. Predicted expenditures are sensitive to the composition of the SSRI claims. Exclusive use of 1 of the 4 major SSRIs (fluvoxamine, fluoxetine, paroxetine, and sertraline) could decrease projected expenditures by 30% or increase them by 11%. An "equal shares" approach, in which each of the 4 SSRIs are used in equal proportions in the population, may reduce expenditures by approximately 8%. CONCLUSIONS: The current trends in the utilization data suggest that sertraline and paroxetine are being used as first-line treatments. The results of the forecasting models suggest that growing expenditures could be curbed if these 2 antidepressants were not used in that manner. Short of limiting the drugs available on benefit formularies, there may be a way to control costs through the use of a prescribing algorithm. Although our results support the use of fluoxetine for first-line SSRI treatment as a cost-control measure, we do not definitively recommend its adoption. These findings contribute to the discussion about using fixed versus flexible formularies as a potential cost-control mechanism.

Adult↗

PubMed1999

Forecasting patient services: a 21st century vision of an academic health centre.

This article provides an overview of the development and implementation of the McGill University Health Centre model for forecasting patient services in the year 2004, and advice on how to apply the model. Critical success factors and case examples are highlighted. The insights provided will be of value to hospitals and other institutions that recognize the necessity of engaging in long-range planning and forecasting.

Academic Medical Centers↗

PubMed1987

Forecasting cataract surgeries and intraocular lens implantation to 1990 using a model of population dynamics.

Extending the recently observed dramatic growth rates of cataract surgery and intraocular lens implantation into the future is not necessarily valid because of changes in population size, new incidence of cataracts, and rates of treatment for patients diagnosed in current as well as in previous years. Accelerated treatment of the pool of previously diagnosed patients caused a sharp growth in cataract surgery since 1980, but at the same time reduced patients and thus the potential for continued high growth rates. This paper describes a model that produces forecasts through explicit consideration of the many aspects of population dynamics. It provides an opportunity to examine how forecasts might vary under different assumptions about advances in medical technology.

Adult↗

PubMedDate not supplied

Application of an ensemble technique based on singular spectrum analysis to daily rainfall forecasting.

In previous work, we have proposed a constructive methodology for temporal data learning supported by results and prescriptions related to the embedding theorem, and using the singular spectrum analysis both in order to reduce the effects of the possible discontinuity of the signal and to implement an efficient ensemble method. In this paper we present new results concerning the application of this approach to the forecasting of the individual rain-fall intensities series collected by 135 stations distributed in the Tiber basin. The average RMS error of the obtained forecasting is less than 3mm of rain.

Forecasting↗

PubMed2002

Forecasting demand of emergency care.

This paper describes a model that can forecast the daily number of occupied beds due to emergency admissions in an acute hospital. Out of sample forecasts 32 day days in advance. have an RMS error of 3% of the mean number of beds used for emergency admissions. We find that the number of occupied beds due to emergency admissions is related to both air temperature and PHLS data on influenza like illnesses. We find that a period of high volatility, indicated by GARCH errors, will result in an increase in waiting times in the A&E Department. Furthermore. volatility gives more warning of waiting times in A&E than total bed occupancy.

Emergency Service, Hospital↗

PubMed1997

Nonlinear forecasting measurements of the human EEG during evoked emotions.

Forecasting ability applied to a single EEG time sequence may quantify loss of memory of past brain states. This fundamental property of complex dynamical systems could prove to be an important measure of current brain states. The present study examined nonlinear forecasting (or nonlinear predictability) estimates of the scalp-recorded EEG in 76 healthy volunteers in response to emotionally charged (negative, positive and control neutral) video-clip stimuli. EEG was recorded from 18 sites (10-20 system). The obtained results indicate that the negative emotional impact led to a more predictable EEG dynamics, compared with neutral or positive emotional video content, and this effect was restricted to the posterior cerebral sites. The studied signatures of EEG dynamics succeed also in specific discrimination between effects of positive and negative film categories: significantly more predictable dynamics over posterior cerebral sites in response to negative film category was accompanied by enhanced predictability in answer to positive film category over frontocortical loci. It is concluded that these findings suggest the association of basic cortical nonlinear mechanisms with the specific physiological processes of emotional processing.

Adolescent↗

PubMed2004

Forecasting recidivism in mentally ill offenders released from prison.

Little research has focused on assessing the risk of mentally ill offenders (MIOs) released from state prisons. Here we report findings for 333 mentally ill offenders released from Washington State prisons. Logistic regression identified sets of variables that forecasted felony and violent reconviction as accurately as state-of-the-art risk assessment instruments. Sums of simple recoded versions of these variables predicted reoffense as well as complex logistic regression equations. Five of these 9 variables were found to be relative protective factors. Findings are discussed in terms of the value of stock correctional variables in forecasting risk, the need to base actuarial risk assessments on local data, the importance of protective factors in assessing MIO risk, and the need for dynamic, situational, and clinical variables that can further sharpen predictive accuracy of emergent risk in the community.

Adult↗

PubMed1993

Economic forecast.

There has been a great deal of speculation in the media about whether or not there are genuine signs of economic recovery in the UK--the now infamous 'Green Shoots'. Although economic growth is picking up, the rate of acceleration is still very weak. Despite this, many commentators are forecasting that the rate of economic growth will steadily increase throughout the rest of the year. Indeed, the forecast for overall economic growth (Gross Domestic Product) for 1993 has been revised upwards from 0.8% to 1.7% since March.

Economics↗

PubMedDate not supplied

[Inpatient health care utilization for musculoskeletal disorders and injuries: a forecast study for Germany up to 2010].

BACKGROUND: The study is part of the project "Orthopaedics 2010 -- evaluation of the demand for the orthopaedic work force in the year 2010", initiated by the professional association of orthopaedists (BVO). The aim is to estimate the prospective number of orthopaedists for the sufficient medical care of musculoskeletal disorders and injuries. METHODS: The main data source was the official statistics of discharge rates from 1994 to 1999 and the German population forecasts from 1994 to 2010 of the Federal Office of Statistics, Wiesbaden, Germany. An univariate forecasting analysis was done using the Granger and Newbold method. RESULTS: All diagnostic categories of musculoskeletal disorders (arthropathies, dorsopathies, rheumatism, osteopathies) will increase up to four-fold from 1994 to 2010. Three of the four diagnostic categories of injuries (dislocations, sprains and strains; contusion; injuries and open wounds) will decrease by up to 15 percent, the diagnostic category of fractures will increase (10 percent). The stratified analyses by gender and age reveal that women and persons over 65 years old are more often affected by musculoskeletal disorders and injuries. CONCLUSIONS: Both demographic changes and changes in the utilization of inpatient care will lead to a substantial increase of hospital cases up to 2010. The presented results should be looked at together with their confidence limits as interval estimations. In addition, there are independent external factors such as the new prospective payment system (G-DRGs) that will influence the hospital admission rates as well.

Age Distribution↗

PubMed2003

Long-term variation in surface ozone and its precursors in Athens, Greece: a forecasting tool.

INTENTION, GOAL, SCOPE, BACKGROUND: Photochemical pollution is a very complex process involving meteorological, topographic, emission and chemical parameters. The most important chemical mechanisms involved in the atmospheric process have already been identified and studied. However, many unknown parameters still exist because of the large number of participating chemical reactions. OBJECTIVE: The present study investigates the processes involved in the photochemical pollution effect of an urban station located in the greater area of the Athens basin and gives a plausible explanation for the different seasonal ozone development between that station and another rural one. Furthermore, the distribution of the mean monthly surface ozone observed at the urban station during 1987-2001 is examined in order to create a relevant forecasting tool. METHODS: Averaged hourly data of O3 and NOx observations monitored at the above mentioned stations, during 1987-2001, have been used in order to derive the daytime (7:00-15:00) values. Trajectories calculated by using a 2D-trajectory code and meteorological data, during the period 1988-1996, have also been used. RESULTS AND DISCUSSION: At the urban station, the percentage negative trend of NO and NOx data in winter and summer is higher than that in spring and autumn, while the percentage ozone trend is maximum in the summer. On the contrary, the negative surface ozone trend at the rural station exhibits a minimum in summer and a maximum in autumn and winter. The mean seasonal wind-rose for the selected months shows that the northward wind flow dominates during June, the month of the lowest negative ozone trend in the rural station. Finally, the development of the forecasting tool shows that the mean monthly surface ozone data during the period (1987-2001) demonstrates a semi-log distribution. CONCLUSIONS: Air transport effect on the air pollution of the rural station (not blocked by mountains) is deduced as a possible reason for the different seasonal ozone development observed between the rural and the urban station. Finally, the discrepancies between the theoretical probabilities deduced by the model and the empirical ones appear to be very small, and the corresponding correlation coefficient is 0.99. RECOMMENDATION AND OUTLOOK: However, to interpret the aforementioned statistical results about the negative trends in ozone and its precursors, additional parameters can be taken into account. Changes in NOx concentrations, for instance, can result not only from changes in emissions or meteorological conditions. There might also be a contribution through changes in the atmospheric composition. A study of the contribution of changes in atmospheric composition to trends of observed NOx concentrations requires that a series of steps be taken (removal of meteorological influence in the time series, calculation of trends in OH concentrations, etc.).

Air Movements↗

PubMed2005

MODELKEY. Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity.

BACKGROUND: Triggered by the requirement of Water Framework Directive for a good ecological status for European river systems till 2015 and by still existing lacks in tools for cause identification of insufficient ecological status MODELKEY (http:// www.modelkey.org), an Integrated Project with 26 partners from 14 European countries, was started in 2005. MODELKEY is the acronym for 'Models for assessing and forecasting the impact of environmental key pollutants on freshwater and marine ecosystems and biodiversity'. The project is funded by the European Commission within the Sixth Framework Programme. OBJECTIVES: MODELKEY comprises a multidisciplinary approach aiming at developing interlinked tools for an enhanced understanding of cause-effect-relationships between insufficient ecological status and environmental pollution as causative factor and for the assessment and forecasting of the risks of key pollutants on fresh water and marine ecosystems at a river basin and adjacent marine environment scale. New modelling tools for risk assessment including generic exposure assessment models, mechanistic models of toxic effects in simplified food chains, integrated diagnostic effect models based on community patterns, predictive component effect models applying artificial neural networks and GIS-based analysis of integrated risk indexes will be developed and linked to a user-friendly decision support system for the prioritisation of risks, contamination sources and contaminated sites. APPROACH: Modelling will be closely interlinked with extensive laboratory and field investigations. Early warning strategies on the basis of sub-lethal effects in vitro and in vivo are provided and combined with fractionation and analytical tools for effect-directed analysis of key toxicants. Integrated assessment of exposure and effects on biofilms, invertebrate and fish communities linking chemical analysis in water, sediment and biota with in vitro, in vivo and community level effect analysis is designed to provide data and conceptual understanding for risk arising from key toxicants in aquatic ecosystems and will be used for verification of various modelling approaches. CONCLUSION AND PERSPECTIVE: The developed tools will be verified in case studies representing European key areas including Mediterranean, Western and Central European river basins. An end-user-directed decision support system will be provided for cost-effective tool selection and appropriate risk and site prioritisation.

Animals↗

PubMed1999

Forecasting hospital expenditure in Victoria: lessons from Europe and Canada.

This paper specifies an econometric model to forecast State government expenditure on recognised public hospitals in Victoria. The OECD's recent cross-country econometric work exploring factors affecting health spending was instructive. The model found that Victorian Gross State Product, population aged under 4 years, the mix of public and private patients in public hospitals, introduction of casemix funding and funding cuts, the proportion of public beds to total beds in Victoria and technology significantly impacted on expenditure. The model may have application internationally for forecasting health costs, particularly in short and medium-term budgetary cycles.

Adolescent↗

PubMed2001

Forecasting generation of urban solid waste in developing countries--a case study in Mexico.

Based on a study of the composition of urban solid waste (USW) and of socioeconomic variables in Morelia, Mexico, generation rates were estimated. In addition, the generation of residential solid waste (RSW) and nonresidential solid waste (NRSW) was forecasted by means of a multiple linear regression (MLR) analysis. For residential sources, the independent variables analyzed were monthly wages, persons per dwelling, age, and educational level of the heads of the household. For nonresidential sources, variables analyzed were number of employees, area of facilities, number of working days, and working hours per day. The forecasted values for residential waste were similar to those observed. This approach may be applied to areas in which available data are scarce, and in which there is an urgent need for the planning of adequate management of USW.

Developing Countries↗

PubMed2002

Forecasting peak daily ozone levels--I. A regression with time series errors model having a principal component trigger to fit 1991 ozone levels.

This research was motivated by the need to warn the population of Milwaukee, WI, on high-ozone days. A statistical model for the peak daily 1-hr ozone level is proposed. A Regression with Time Series Errors (RTSE) model, which includes a principal component (PC) trigger, is the basis for forecasting the peak daily 1-hr ozone level. The RTSE model, with a PC trigger, is first employed to estimate daily peak ozone measured at the University of Wisconsin, Milwaukee-North (UWM-N), during the 1991 ozone season. The RTSE model uses peak daily temperature, morning vector average wind direction, and the PC trigger as predictor variables. The PC trigger was designed to summarize atmospheric circumstances when peak ozone was greater than 100 parts per billion (ppb). It is verified that the RTSE model, with a PC trigger, significantly improves the prediction of peak daily ozone, particularly peak ozone greater than 100 ppb. In comparison with the RTSE model without the PC trigger, the RTSE model with a PC trigger raised the R2 from 0.680 to 0.809. It is suggested that the RTSE model, with the PC trigger, is an adequate statistical model that has the potential for real-time ozone forecasting.

Air Pollutants↗

PubMed2004

Forecasting daily maximum surface ozone concentrations in Brunei Darussalam--an ARIMA modeling approach.

A time series approach using autoregressive integrated moving average (ARIMA) modeling has been used in this study to obtain maximum daily surface ozone (O3) concentration forecasts. The order of the fitted ARIMA model is found to be (1,0,1) for the surface O3 data collected at the airport in Brunei Darussalam during the period July 1998-March 1999. The model forecasts of one-day-ahead maximum O3 concentrations have been found to be reasonably close to the observed concentrations. The model performance has been evaluated on the basis of certain commonly used statistical measures. The overall model performance is found to be quite satisfactory as indicated by the values of Fractional Bias, Normalized Mean Square Error, and Mean Absolute Percentage Error as 0.025, 0.02, and 13.14% respectively.

Air Pollutants↗

PubMed2006

Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

Air Pollutants↗