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PubMed1994

Global tuberculosis incidence and mortality during 1990-2000.

Forecasts of tuberculosis morbidity and mortality are presented for the decade 1990-99. An estimated 88 million new cases of tuberculosis, of which 8 million will be attributable to HIV infection, will occur in the world during the decade; 30 million people are predicted to die of tuberculosis in the same period, including 2.9 million attributable to HIV infection. The number of new tuberculosis cases occurring each year is predicted to increase from 7.5 million (143 cases per 100,000) in 1990 to 8.8 million (152 per 100,000) in 1995 and 10.2 million (163 per 100,000) in the year 2000. In 1990, 2.5 million persons were estimated to have died of tuberculosis; at the same level of availability of treatment, it is predicted that 3.0 million tuberculosis deaths will occur in 1995 and 3.5 million in 2000. Demographic factors, such as population growth and changes in the age structure of populations, will account for 79.5% of the predicted increases in new cases. Age-specific incidence rates in sub-Saharan Africa are increasing due to the HIV epidemic and will account for the remaining 20.5% of the forecast increase in new cases. In WHO's South-East Asian Region and in Central and South America the age-specific incidence rates are expected to fall during 1990-2000, but at a slower rate than in previous years because of the expected increase in HIV seroprevalence.(ABSTRACT TRUNCATED AT 250 WORDS)

AIDS-Related Opportunistic Infections↗

PubMed1996

Will modern caries management reduce restorations in dental practice?

Dentists have difficulty diagnosing caries presence and activity. Modern caries management suggests that lesions in low risk patients should not be restored until the radiolucency extends into the outer third of interproximal dentin. Even stained fissures need not be restored in the absence of occlusal dentin radiolucency. If this standard were adopted, what affect would it have on the amount of operative treatment delivered? This report created a model to forecast the change in work volume caused by new caries management strategies. The model considered two identical groups of 1,000 adult teeth with a normal distribution of 1,000 radiographic lesions in each group. Group I would have all lesions restored at baseline, but Group II would have only lesions in the dentin restored. Each year for ten years the model forecasts the number of replacement restorations for both groups, plus initial restorations for Group II. A sensitivity analysis was conducted using slow progression rates (Group IIa) and fast progression rates (Group IIb). After ten years, Group IIa has 49% and Group IIb had 32% fewer restorations than Group I. It is concluded that the model is robust and modern caries management may significantly reduce operative workload.

Adult↗

PubMed1998

Use of time-series analysis in infectious disease surveillance.

This article reviews the practical aspects of the use of ARIMA (autoregressive, integrated, moving average) modelling of time series as applied to the surveillance of reportable infectious diseases, with special reference to the widely available SSS1 package, produced by the Centers for Disease Control and Prevention. The main steps required by ARIMA modelling are the selection of the time series, transformations of the series, model selection, parameter estimation, forecasting, and updating of the forecasts. The difficulties most likely to be encountered at each step are described and possible solutions are offered. Examples of successful and unsuccessful modelling are presented and discussed. Other methods, such as INAR modelling or Markov chain analysis, which can be applied to situations where ARIMA modelling fails are also dealt with, but they are less practical. ARIMA modelling can be carried out by adequately trained nonspecialists working for local agencies. Its usefulness resides mostly in providing an estimate of the variability to be expected among future observations. This knowledge is helpful in deciding whether or not an unusual situation, possibly an outbreak, is developing.

Communicable Disease Control↗

PubMed2004

Estimates of global prevalence of childhood underweight in 1990 and 2015.

CONTEXT: One key target of the United Nations Millennium Development goals is to reduce the prevalence of underweight among children younger than 5 years by half between 1990 and 2015. OBJECTIVE: To estimate trends in childhood underweight by geographic regions of the world. DESIGN, SETTING, AND PARTICIPANTS: Time series study of prevalence of underweight, defined as weight 2 SDs below the mean weight for age of the National Center for Health Statistics and World Health Organization (WHO) reference population. National prevalence rates derived from the WHO Global Database on Child Growth and Malnutrition, which includes data on approximately 31 million children younger than 5 years who participated in 419 national nutritional surveys in 139 countries from 1965 through 2002. MAIN OUTCOME MEASURES: Linear mixed-effects modeling was used to estimate prevalence rates and numbers of underweight children by region in 1990 and 2015 and to calculate the changes (ie, increase or decrease) to these values between 1990 and 2015. RESULTS: Worldwide, underweight prevalence was projected to decline from 26.5% in 1990 to 17.6% in 2015, a change of -34% (95% confidence interval [CI], -43% to -23%). In developed countries, the prevalence was estimated to decrease from 1.6% to 0.9%, a change of -41% (95% CI, -92% to 343%). In developing regions, the prevalence was forecasted to decline from 30.2% to 19.3%, a change of -36% (95% CI, -45% to -26%). In Africa, the prevalence of underweight was forecasted to increase from 24.0% to 26.8%, a change of 12% (95% CI, 8%-16%). In Asia, the prevalence was estimated to decrease from 35.1% to 18.5%, a change of -47% (95% CI, -58% to -34%). Worldwide, the number of underweight children was projected to decline from 163.8 million in 1990 to 113.4 million in 2015, a change of -31% (95% CI, -40% to -20%). Numbers are projected to decrease in all subregions except the subregions of sub-Saharan, Eastern, Middle, and Western Africa, which are expected to experience substantial increases in the number of underweight children. CONCLUSIONS: An overall improvement in the global situation is anticipated; however, neither the world as a whole, nor the developing regions, are expected to achieve the Millennium Development goals. This is largely due to the deteriorating situation in Africa where all subregions, except Northern Africa, are expected to fail to meet the goal.

Body Weight↗

PubMed2005

Population modeling for a captive squirrel monkey colony.

Population modeling for a squirrel monkey colony breeding in a captive laboratory environment was approached with the use of two different mathematical modeling techniques. Deterministic modeling was used initially on a spreadsheet to estimate future census figures for animals in various age/sex classes. Historical data were taken as input parameters for the model, combined with harvesting policies to calculate future population figures in the colony. This was followed by a more sophisticated stochastic model that is capable of accommodating random variations in biological phenomena, as well as smoothing out measurement errors. Point estimates (means) for input parameters used in the deterministic model are replaced by probability distributions fitted into historical data from colony records. With the use of Crystal Ball (Decisioneering, Inc., Denver, CO) software, user-selected distributions are embedded in appropriate cells in the spreadsheet model. A Monte Carlo simulation scheme running within the spreadsheet draws (on each cycle) random values for input parameters from the distribution embedded in each relevant cell, and thus generates output values for forecast variables. After several thousand runs, a distribution is formed at the output end representing estimates for population figures (forecast variables) in the form of probability distributions. Such distributions provide the decision-maker with a mathematical habitat for statistical analysis in a stochastic setting. In addition to providing standard statistical measures (e.g., mean, variance, and range) that describe the location and shape of the distribution, this approach offers the potential for investigating crucial issues such as conditions surrounding the plausibility of extinction.

Animals↗

PubMed2002

Modifications to canonical structure sequence patterns: analysis for L1 and L3.

The conformation of five of the six hypervariable loops that form the antigen-binding site of antibodies is limited to a small set of structures designated as canonical structures. The canonical structure model has been constituted as a fundamental tool for the modeling of antibodies. The detailed study of tens of crystallographic structures of antibodies has shown the validity of this model in the great majority of cases. The robustness of the forecast capacity of this model depends fundamentally on the precision with which the sequence patterns that characterize each canonical structure form can be defined. Nevertheless, due to the enormous quantity of structural information about antibodies generated during the last decade, it is difficult to avoid mistakes or confusion in the model. In the present work, we propose some corrections to the model for loops L1 and L3 that permit defining sequence patterns that avoid confusion and make better forecasting of the canonical structure model possible.

Animals↗

PubMed2004

Decision making in controlling virus yellows of sugar beet in the UK.

Virus yellows is an important disease affecting yield in sugar beet in the UK. Myzus persicae (Sulzer) is the most effective and efficient aphid vector of the three viruses causing the disease: beet yellows virus, beet mild yellowing virus and beet chlorosis virus. Control of virus yellows disease is thus focused on the study and control of this aphid species. UK national surveys of virus yellows began in 1946 and these data helped to formulate disease forecasting schemes to optimise control. Over the years, in addition to improvements in farm hygiene, periodic changes and developments in control of the disease have occurred. To accommodate these important developments, virus yellows forecasting schemes have evolved accordingly. The most recent version has been adapted to take account of the current widespread use of imidacloprid seed treatment. Its application offers potential to optimise the rational use of aphicides such as imidacloprid so as to benefit beet growers and the environment by reducing prophylactic use of seed treatment.

Animals↗

PubMed1997

A Bayesian formulation of the Kalman filter applied to the estimation of individual pharmacokinetic parameters.

A general method of Bayesian forecasting employing the dynamic linear model has been adapted to the problem of estimating individual pharmacokinetic parameters. The Bayesian forecasting method incorporates an efficient Kalman filter algorithm for updating pharmacokinetic parameter estimates when further observations are made. The Kalman filter is more general and flexible than other Bayesian methods currently used and simulation studies have demonstrated its practicality for three different pharmacokinetic models. The method serves as the basis for a computer program for general clinical use.

Algorithms↗

PubMed1999

The Effects of Subject-Defined Categories on Judgmental Accuracy in Confidence Assessment Tasks.

The accuracy of confidence judgments can be determined using measures of discrimination and calibration. The present paper utilizes a new assessment methodology that decomposes the confidence assessment task, allowing us to investigate discrimination and calibration skills in greater depth than has been done in previous studies. Researchers investigating the goodness of confidence judgments have typically grouped forecasters' assessments into experimenter-defined categories, generally in equal widths of.10. In the present research, subjects created their own categories and later assigned confidence judgments to the categories, separating the tasks of discriminating categories (discrimination) and assigning numbers to categories (calibration). Further, the typical assessment procedure assumes that subjects are able to discriminate equally across the confidence scale. Since subjects in the present study defined their own assessment categories, they could locate those categories at any point on the scale. A final issue of interest was whether subjects were able to determine accurately the number of categories into which they could discriminate. Sixty subjects performed 1 of 2 tasks, general knowledge or forecasting, in both relatively easy and relatively hard conditions. Results showed a trade-off in performance: Calibration generally became worse as the number of categories increased, while discrimination generally improved. Overall accuracy was not affected by the number of categories used. Further, subjects partitioned categories more at the high end of the scale. Finally, measures showed that subjects were not accurate in their beliefs about their own discrimination ability. Copyright 1999 Academic Press.

Journal Article↗

PubMed1991

Dengue surveillance in French Polynesia: an attempt to use the excess number of laboratory requests for confirmation of dengue diagnosis as an indicator of dengue activity.

The excess number of weekly laboratory requests for confirmation of dengue diagnosis over the expected number of requests forecasted by the modified Serfling method is proposed for the surveillance of dengue in French Polynesia, in addition to conventional methods. Retrospective analysis of the seasonal curves of dengue activity related to the number of laboratory requests is described for the years 1982-1987 where dengue type 4 was the only active flavivirus at the time when the forecast was initiated. By using past epidemic data, the probability of failing to recognize an increase in excess of requests as possibly epidemic was of 13.2% and 5.8%, respectively, when the criterion for epidemic increase was set respectively at 2 and 3 successive weeks during which the epidemic threshold is exceeded. A weekly surveillance was set up prospectively for 1988 using these criteria.

Clinical Laboratory Techniques↗

PubMed1990

Predictability and intraindividual variability of serum theophylline concentrations in patients with obstructive lung disease: 12-h versus 24-h dosing.

The predictability and intraindividual variability of serum theophylline concentrations (STC) after different dosing schedules were investigated in 24 patients with chronic obstructive lung disease (COLD). Three oral regimens were compared in 3 groups of 8 randomly assigned patients. Group I:Drug A once daily in the evening; Group II: Drug A b.d.; Group III: Drug B b.d. The doses for each patient were estimated by Bayesian forecasting aiming at an STC of 10-15 mg/l. STC and FEV1 were measured on two consecutive days at steady-state. The day-to-day variability of STC was less than 20% in all three groups. The within-day fluctuation in Group I amounted to 259% (median) compared to 57% and 38% in Groups II and III, respectively. Dose adjustment by Bayesian forecasting resulted in a therapeutic STC in most patients with a b.d. regimen, whereas for the once daily dose the prediction was not satisfactory. No difference in lung function was found between the 24-h and 12-h dosing, probably because of the large intersubject variability in FEV1. Therefore, the question whether the differences in STC profile are of clinical importance in COLD can only be investigated in a larger group of patients.

Adult↗

PubMed1987

[Time series analysis of the influence of prevention using the example of the occurrence of accidents in Zurich before and after Tempo 50].

In the evaluation of the effect of preventive measures data often arise at fixed time intervals and it is likely that successive observations are stochastically dependent. By means of the example of the "possible reduction of traffic injuries after the introduction of a speed limitation (50 km/h) in Zurich" it is shown how time series methods can help to assess the efficiency of such measures. For the series before the intervention a statistical model is identified which describes the probability structure of the series. This model is used to forecast the course of the series one would expect when no intervention takes place. The forecast and the actual series are then plotted in the same figure and the difference is analysed with a test. In addition to that the magnitude of the effect and its standard error are estimated (intervention analysis). The series "numbers of accidents with injuries" showed after the intervention a yearly reduction of approximately 250 accidents (14%) with a corresponding standard error of 30. The reduction is markedly less pronounced in the series "number of seriously injured persons" than in the series "number of slightly injured persons".

Accidents, Traffic↗

PubMed1998

Feature extraction and state identification in biomedical signals using hierarchical fuzzy clustering.

Many problems in the field of biomedical signal processing can be reduced to a task of state recognition and event prediction. Examples can be found in tachycardia detection from ECG signals, epileptic seizure or psychotic attack prediction from an EEG signal, and prediction of vehicle drivers falling asleep from both signals. The problem generally treats a set of ordered measurements and asks for the recognition of some patterns of observed elements that will forecast an event or a transition between two different states of the biological system. It is proposed to apply clustering methods to grouping discontinuous related temporal patterns of a continuously sampled measurement. The vague switches from one stationary state to another are naturally treated by means of fuzzy clustering. In such cases, an adaptive selection of the number of clusters (the number of underlying semi-stationary processes) can overcome the general non-stationary nature of biomedical signals and enable the formation of a warning cluster. The algorithm suggested for the clustering is a new recursive algorithm for hierarchical fuzzy partitioning. Each pattern can have a non-zero membership in more than one data subset in the hierarchy. A 'natural' and feasible solution to the cluster validity problem is suggested by combining hierarchical and fuzzy concepts. The algorithm is shown to be effective for a variety of data sets with a wide dynamic range of both covariance matrices and number of members in each class. The new method is applied to state recognition during recovery from exercise using the heart rate signal and to the forecasting of generalised epileptic seizures from the EEG signal.

Algorithms↗

PubMed2003

[Artificial neural networks. Theory and applications in anesthesia, intensive care and emergency medicine].

Artificial neural networks (ANN) are constructed to simulate processes of the central nervous system of higher creatures. An ANN consists of a set of processing units (nodes) which simulate neurons and are interconnected via a set of "weights" (analogous to synaptic connections in the nervous system) in a way which allows signals to travel through the network in parallel. The nodes (neurons) are simple computing elements. They accumulate input from other neurons by means of a weighted sum. If a certain threshold is reached the neuron sends information to all other connected neurons otherwise it remains quiescent. One major difference compared with traditional statistical or rule-based systems is the learning aptitude of an ANN. At the very beginning of a training process an ANN contains no explicit information. Then a large number of cases with a known outcome are presented to the system and the weights of the inter-neuronal connections are changed by a training algorithm designed to minimise the total error of the system. A trained network has extracted rules that are represented by the matrix of the weights between the neurons. This feature is called generalisation and allows the ANN to predict cases that have never been presented to the system before. Artificial neural networks have shown to be useful predicting various events. Especially complex, non-linear, and time depending relationships can be modelled and forecasted. Furthermore an ANN can be used when the influencing variables on a certain event are not exactly known as it is the case in financial or weather forecasts. This article aims to give a short overview on the function of ANN and their previous use and possible future applications in anaesthesia, intensive care, and emergency medicine.

Anesthesiology↗

PubMed2004

A model to estimate the lifetime health outcomes of patients with type 2 diabetes: the United Kingdom Prospective Diabetes Study (UKPDS) Outcomes Model (UKPDS no. 68).

AIMS/HYPOTHESIS: The aim of this study was to develop a simulation model for type 2 diabetes that can be used to estimate the likely occurrence of major diabetes-related complications over a lifetime, in order to calculate health economic outcomes such as quality-adjusted life expectancy. METHODS: Equations for forecasting the occurrence of seven diabetes-related complications and death were estimated using data on 3642 patients from the United Kingdom Prospective Diabetes Study (UKPDS). After examining the internal validity, the UKPDS Outcomes Model was used to simulate the mean difference in expected quality-adjusted life years between the UKPDS regimens of intensive and conventional blood glucose control. RESULTS: The model's forecasts fell within the 95% confidence interval for the occurrence of observed events during the UKPDS follow-up period. When the model was used to simulate event history over patients' lifetimes, those treated with a regimen of conventional glucose control could expect 16.35 undiscounted quality-adjusted life years, and those receiving treatment with intensive glucose control could expect 16.62 quality-adjusted life years, a difference of 0.27 (95% CI: -0.48 to 1.03). CONCLUSIONS/INTERPRETATIONS: The UKPDS Outcomes Model is able to simulate event histories that closely match observed outcomes in the UKPDS and that can be extrapolated over patients' lifetimes. Its validity in estimating outcomes in other groups of patients, however, remains to be evaluated. The model allows simulation of a range of long-term outcomes, which should assist in informing future economic evaluations of interventions in type 2 diabetes.

Amputation, Surgical↗

PubMed2004

Time series analysis of long-term data sets of atmospheric mercury concentrations.

Different aspects and techniques of time series analysis were used to investigate long-term data sets of atmospheric mercury in the Northern Hemisphere. Two perennial time series from different latitudes with different seasonal behaviour were chosen: first, Mace Head on the west coast of Ireland (53 degrees 20'N, 9 degrees 54'W), representing Northern Hemispherical background conditions in Europe with no indications for so-called atmospheric mercury depletion events (AMDEs); and second, Alert, Canada (82 degrees 28'N, 62 degrees 30'W), showing strong AMDEs during Arctic springtime. Possible trends were extracted and forecasts were performed by using seasonal decomposition procedures, autoregressive integrated moving average (ARIMA) methods and exponential smoothing (ES) techniques. The application of time series analysis to environmental data is shown in respect of atmospheric long-term data sets, and selected advantages are discussed. Both time series have not shown any statistically significant temporal trend in the gaseous elemental mercury (GEM) concentrations since 1995, representing low Northern Hemispherical background concentrations of 1.72+/-0.09 ng m(-3) (Mace Head) and 1.55+/-0.18 ng m(-3) (Alert), respectively. The annual forecasts for the GEM concentrations in 2001 at Alert by two different techniques were in good agreement with the measured concentrations for this year.

Journal Article↗

PubMed2004

Operational atmospheric modeling system CARIS for effective emergency response associated with hazardous chemical releases in Korea.

The Chemical Accidents Response Information System (CARIS) was developed at the Center for Chemical Safety Management in South Korea in order to track and predict the dispersion of hazardous chemicals in the case of an accident or terrorist attack involving chemical companies. The main objective of CARIS is to facilitate an efficient emergency response to hazardous chemical accidents by rapidly providing key information in the decision-making process. In particular, the atmospheric modeling system implemented in CARIS, which is composed of a real-time numerical weather forecasting model and an air pollution dispersion model, can be used as a tool to forecast concentrations and to provide a wide range of assessments associated with various hazardous chemicals in real time. This article introduces the components of CARIS and describes its operational modeling system. Some examples of the operational modeling system and its use for emergency preparedness are presented and discussed. Finally, this article evaluates the current numerical weather prediction model for Korea.

Accidents, Occupational↗

PubMed2006

Assessing potential removal of low-head dams in urban settings: an example from the Ottawa River, NW Ohio.

This is a study of the scientific component of an effort to restore an urban river by removing a low-head dam. The Secor Dam is owned by a local government entity near Toledo, Ohio. The proposed removal of the last structure impeding flow on the Ottawa River has broad appeal, but the owner is concerned about liability issues, particularly potential changes to the flood regime, the presence of contaminated sediments behind the dam, and possible downstream transport of reservoir sediments. Assessing sediment contamination involved sediment sampling and analysis of trace metals and organic contaminants. Forecasting sediment transport involved field methods to determine the volume and textural properties of reservoir and upstream sediment and calculations to determine the fate of reservoir sediments. Forecasting changes in the flood regime involved HEC-RAS hydrological models to determine before and after dam removal flood scenarios using LiDAR data imported into an ArcGIS database. The resulting assessment found potential sediment contamination to be minor, and modeling showed that the removal of the dam would have minimal impacts on sediment transport and flood hazards. Based on the assessment, the removal of the dam has been approved by its owners.

Disasters↗

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