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PubMed1999

The interpretation of "likely" depends on the context, but "70%" is 70%--right? The influence of associative processes on perceived certainty.

Past research has demonstrated that interpretations of vague verbal forecasts (e.g., "likely") differ as a function of the context to which they refer. Experiments 1 and 2 demonstrate that precise numeric forecasts (e.g., "70%") are also susceptible to such context effects. Participants read descriptions of target events and experts' numeric forecasts. Perceptions of certainty, expressed on nonnumeric scales, differed as a function of context manipulations. The results of Experiments 3a, 3b, and 4 indicate that these effects can be mediated by perceptions of an event's representativeness independently of subjective base rates. The results are also consistent with the idea that two types of semi-independent processing--associative and rule based--can have important influences on perceptions of certainty. Implications of this distinction for research on judgments and decisions under uncertainty are discussed.

Humans↗

PubMed2003

Predicted recurrences of mass coral mortality in the Indian Ocean.

In 1998, more than 90% of shallow corals were killed on most Indian Ocean reefs. High sea surface temperature (SST) was a primary cause, acting directly or by interacting with other factors. Mean SSTs have been forecast to rise above the 1998 values in a few decades; however, forecast SSTs rarely flow seamlessly from historical data, or may show erroneous seasonal oscillations, precluding an accurate prediction of when lethal SSTs will recur. Differential acclimation by corals in different places complicates this further. Here I scale forecast SSTs at 33 Indian Ocean sites where most shallow corals died in 1998 (ref. 1) to identify geographical patterns in the timing of probable repeat occurrences. Reefs located 10-15 degrees south will be affected every 5 years by 2010-2025. North and south from this, dates recede in a pattern not directly related to present SSTs; paradoxically, some of the warmest sites may be affected last. Temperatures lethal to corals vary in this region by 6 degrees C, and acclimation of a modest 2 degrees C by corals could prolong their survival by nearly 100 years.

Acclimatization↗

PubMed2005

Average remaining lifetimes can increase as human populations age.

Increases in median ages, the most commonly used measure of population ageing, are rapid in today's wealthier countries, and population ageing is widely considered to be a significant challenge to the well-being of citizens there. Conventional measures of age count years since birth; however, as lives lengthen, we need to think of age also in terms of years left until death or in proportion to the expanding lifespan. Here we propose a new measure of ageing: the median age of the population standardized for expected remaining years of life. We show, using historical data and forecasts for Germany, Japan and the United States, that although these populations will be growing older, as measured by their median ages, they will probably experience periods in which they grow younger, as measured by their standardized median ages. Furthermore, we provide forecasts for these countries of the old-age dependency ratio rescaled for increases in life expectancy at birth. These ratios are forecasted to change much less than their unscaled counterparts, and also exhibit periods when the population is effectively growing younger.

Adult↗

PubMed2002

Development and validation of a simulation model for blowfly strike of sheep.

A comprehensive simulation model for sheep blowfly strike due to Lucilia sericata (Meigen) (Diptera: Calliphoridae), which builds on previously published versions but also incorporates important new empirical data, is used to explain patterns of lamb and ewe strike recorded on 370 farms in south-west, south-east and central England and Wales. The model is able to explain a significant percentage of the variance in lamb strike incidence in all four regions, and ewe strike in three of the four regions. The model is able to predict the start of seasonal blowfly strike within one week in three of the four regions for both ewes and lambs, and within 3 weeks in the fourth region. It is concluded that the accuracy of the model will allow it to be used to assess the likely efficacy of new control techniques and the effects of changes in existing husbandry practices on strike incidence. The model could also be used to give sheep farmers advance warning of approaching strike problems. However, the ability to forecast future strike patterns is dependent on the accuracy of the weather projections; the more long-term the forecast, the more approximate the prediction is likely to be. When applied on a regional basis, model forecasts indicate expected average patterns of strike incidence and may not therefore be appropriate for individual farmers whose husbandry practices differ substantially from the average.

Animals↗

PubMed1996

Human immunodeficiency virus infection dynamics in east Africa deduced from surveillance data.

Knowledge of human immunodeficiency virus type 1 (HIV) incidence patterns in East African HIV epidemics like that in Uganda is fundamental for guiding interventions and forecasting the future course of the pandemic, yet they are difficult to determine from surveillance data. The authors deduce hypotheses of HIV incidence dynamics from birth cohort analyses of Ugandan acquired immunodeficiency syndrome (AIDS) incidence from 1987 to 1992 and from the age and sex distribution of sexually transmitted disease: an age dependency for HIV risk; a period effect of varying HIV incidence growth; and a replenishment of HIV-susceptible populations through demographic renewal. The hypotheses are tested by incorporating them into a model that generates patterns of HIV incidence, prevalence, and AIDS cases that are consistent with empiric data. When applied to Uganda, the modeled HIV incidence is characterized by a short temporal concentration of high incidence, followed by a decline, stabilization, and concentration in younger ages. The ensuing HIV dynamics result in a rapid build-up and subsequent stabilization of prevalence and mortality in years 10 and 13, respectively, after epidemic onset. When this model is used to forecast scenarios from 1980 to 2000, HIV prevalence declines in some populations, which is different from earlier scenarios. The techniques presented provide an empiric basis to better direct interventions, forecast epidemic impacts, and evaluate determinants of changing incidence and prevalence patterns.

Acquired Immunodeficiency Syndrome↗

PubMed1998

Intervention decision model to prevent spiking mortality of turkeys.

Based on the daily records on turkeys' mortalities for the series of flocks placed on different farms in a relatively compact geographical area for the period of approximately 2 yr and other relevant explanatory variables, the goal of the research was to design a decision model to determine whether or not to use the fluorquinolone antibiotic, sarafloxacin, to prevent spiking mortality of turkeys. The core of the designed decision model is the forecasting model that attempts to ex-ante predict the cumulative flock mortality for the period between 8 and 28 d of age. Forecasts were generated with the parameters of the linear regression model where continuous values of daily mortalities served as a dependent variable. The decision variable is a binary (yes/no) choice variable, where "yes" means "go ahead with treatment" and "no" means "do nothing". If the predicted cumulative mortality for the period between 8 and 28 d of age exceeds 9% of the total initial placement, the model generates a "yes" signal. If the predicted cumulative mortality for the same period is below 9% of the total initial placement, the model generates a "no" signal. The results indicate a reasonable accuracy of the prediction model where the number of correct prediction increases and the number of incorrect predictions falls very fast as the forecasting window shortens. The intervention decision model could help veterinarians in making decisions on whether or not to treat the suspect flocks.

Aging↗

PubMed1999

Effects of prognosis, perceived benefit, and decision style on decision making and critical care on decision making in critical care.

OBJECTIVE: To assess the effects of prognostic estimates, perceived benefit of treatment, and practice style on decision-making in critical care. DESIGN: Randomized assignment of subjects to either of two versions of a questionnaire designed to elicit treatment decisions for six intensive care unit cases based on actual patients. One version offered optimistic survival forecasts; the other, pessimistic forecasts. SUBJECTS: A random sample of 120 clinicians obtained from the Canadian Critical Care Society was contacted by mail. One version of the questionnaire was randomly assigned and mailed to each. Thirty-four replies, 17 for each version (response rate, 28%), were received and analyzed. MEASUREMENTS AND MAIN RESULTS: A list of treatment/management options was developed for each case, in three categories: recommended, questionable, and unacceptable. Subjects were also able to list new options that they would order that were not on the list. The dependent variables were the number of actions ordered in each category and the total for each case. Perceived benefit was measured by comparing subjective estimates of the probability of survival with the optimistic/pessimistic forecast given in the case. Practice style was assessed by correlating the total number of actions ordered across all possible pairs of cases. There were no significant differences between the two questionnaires on actions ordered either by category or by amount per category. Perceived benefit did not appear to be an important factor in decision-making. However, statistically significant correlations provide evidence for practice style in intensive care unit decision-making on an interventionist/noninterventionist dimension. CONCLUSIONS: There is no evidence that erroneous or biased prognostic estimates affect intensive care unit treatment choices. Neither the principle of maximizing expected utility nor the Rule of Rescue appear to affect these decisions systematically, but practice style does.

Canada↗

PubMed2006

Determining the contribution of Antarctica to sea-level rise using data assimilation methods.

The problem of forecasting the future behaviour of the Antarctic ice sheet is considered. We describe a method for optimizing this forecast by combining a model of ice sheet flow with observations. Under certain assumptions, a linearized model of glacial flow can be combined with observations of the thickness change, snow accumulation, and ice-flow, to forecast the Antarctic contribution to sea-level rise. Numerical simulations show that this approach can potentially be used to test whether changes observed in Antarctica are consistent with the natural forcing of a stable ice sheet by snowfall fluctuations. To make predictions under less restrictive assumptions, improvements in models of ice flow are needed. Some of the challenges that this prediction problem poses are highlighted, and potentially useful approaches drawn from numerical weather prediction are discussed.

Journal Article↗

PubMed2006

Immunological exposures in Norwegian agriculture and pre-eclampsia.

Immune system perturbations are involved in pre-eclampsia pathophysiology. We hypothesised that immunomodulating substances, such as mycotoxins, endotoxins or pesticides, affect pre-eclampsia risk. Associations between indicators of immunomodulating exposures in agriculture and pre-eclampsia are reported. In a Norwegian family cohort based on participants in agricultural censuses conducted by Statistics Norway 1969-89, 183 313 pregnancies to farmers were identified in the Medical Birth Registry of Norway. Cases notified as pre-eclampsia as well as pregnancies indicated by hypertension in combination with proteinuria were included. Data on farm production and meteorologically based fungal forecasts 1973-90 (a marker of temperate and humid climatic conditions known to favour fungal growth and mycotoxin formation in grain) were obtained and allocated to each farm. Pre-eclampsia prevalence rates were studied in strata of exposure indicators using Poisson regression models. Adjusted rate ratios (RR) and 95% confidence intervals [CI] were computed. We identified 4912 cases, equivalent to 26.8 pre-eclampsia cases per 1000 pregnancies [95% CI 26.1, 27.6]. Pre-eclampsia showed moderate associations with animal farming, RR 1.14, [95% CI 1.07, 1.22] and moderate negative associations with grain production, RR 0.93, [95% CI 0.86, 1.01], and two or more fungal forecasts appearing in any year 1973-90, RR 0.90 [95% CI 0.84, 0.97], using no years with two or more forecasts as reference. Exposure to immunomodulating substances as indicated by grain farming, animal farming and fungal warnings could possibly have moderate effects on pre-eclampsia risk, thus supporting the study hypothesis. The use of exposure indicators as surrogates for real exposures may introduce a non-differential misclassification of the exposure that would attenuate any true exposure-outcome association. The use of exposure proxies warrants that inferences from the study should be made with caution.

Adolescent↗

PubMed1994

Migration and market wage risk.

The author presents an approach to the analysis of labor migration that incorporates the role of market wage variability as a source of information in individual migration decisions. "The focus...is on quantifying the effects of the origin market acting through amenities and the share of market-specific wage variability as it affects forecasts of alternative wages and forecast precision. A subsample of employed males...from the [U.S.] National Longitudinal Survey of Youth (NLS) age 16 to 22 years is used for estimation. The empirical results are consistent with the theoretically predicted relationship between migration propensities and regional differences in the information content of wages. In addition, the results provide evidence that risk aversion deters migration given uncertainty, measured by forecast precision, about alternative market wage levels."

Americas↗

PubMed2000

Inductive learning approaches to rainfall-runoff modelling.

Trying to model the rainfall-runoff process is a complex activity as it is influenced by a number of implicit and explicit factors--for example, precipitation distribution, evaporation, transpiration, abstraction, watershed topography, and soil types. However, this kind of forecasting is particularly important as it is used to predict serious flooding, estimate erosion and identify problems associated with low flow. Inductive learning approaches (e.g. decision trees and artificial neural networks) are particularly well suited to problems of this nature as they can often interpret underlying factors (such as seasonal variations) which cannot be modelled by other techniques. In addition, these approaches can easily be trained on the explicit factors (e.g. rainfall) and the inexplicit factors (e.g. abstraction) that affect river flow. Inductive learning approaches can also be extended to account for new factors that emerge over a period of time. This paper evaluates the application of decision trees and two artificial neural network models (the multilayer perceptron and the radial basis function network) to river flow forecasting in two flood prone UK catchments using real hydrometric data. Comparisons are made between the performance of these approaches and conventional flood forecasting systems.

Algorithms↗

PubMed1994

Prediction of acetaminophen concentrations in overdose patients using a Bayesian pharmacokinetic model.

A pharmacokinetic program using population-based parameter estimates and a Bayesian forecasting model was retrospectively evaluated for predicting acetaminophen serum concentrations in overdose patients. Dynamic disposition factors known to affect acetaminophen disposition (emesis, activated charcoal, N-acetylcysteine, etc.) were included in the program. Twenty six patients who reported an acetaminophen ingestion of at least 70 mg/kg within 24 h of presentation to the hospital and had at least one measured acetaminophen concentration were included. Prediction of initial acetaminophen concentrations using only population-based parameter estimates resulted in a percent mean error (%ME) and percent mean absolute error (%MAE) of 9.3 and 42.2, respectively. Using only the initial concentration as feedback, the Bayesian forecasting model accurately predicted the second acetaminophen concentration (%ME = 4.0, %MAE = 23.6). The Bayesian model also accurately predicted all concentrations within 8 h of the ingestion (%ME = 10.6, %MAE = 24.0). The prediction of concentrations between 2 to 4 h and 4 to 4.5 h after ingestion with only population-based parameter estimates resulted in %ME of 17.0 and 13.2, respectively, and %MAE of 36.5 and 35.1, respectively. Our data suggests that acetaminophen serum concentrations occurring within the first 4.5 h after ingestion can be reliably predicted by the set of population-based parameter estimates evaluated. Once a single acetaminophen concentration is available, the Bayesian forecasting model can accurately predict subsequent concentrations within the first 8 h after an acetaminophen ingestion.

Acetaminophen↗

PubMed1999

Cytomegalovirus infection in infants: an example of a chronopharmacological approach.

A case of a male infant at the age of 3 months with cytomegalovirus (CMV) infection, diagnosed 40 days after the first symptoms, was discussed. While the right dosage and schedule during the initial treatment with ganciclovir (Cymevene) were agreed on, the right time of further application of anti-CMV IgG (Cytotest) and ganciclovir was unclear. Daily mean temperature was taken as an overall measure based on 7 single readings (6:00, 9:00, 12:00, 15:00, 18:00, 21:00 and 24:00 h +/- 10 min). Dynamics of daily mean temperature was studied by descriptive statistics, regression analysis, autocorrelation and periodogram regression analysis (software package "6-D Statistics" PC ver.4.5-98 by B. P. Komitov) with the purpose of identifying the time periods of viral DNA replications and CMV population growth inclinations. A five-step procedure was applied: (1) description of a tendency in the daily mean temperature; (2) studying variations in time series of the daily mean temperature; (3) decomposition of cyclic variations; (4) reconstruction of time series; (5) best model determination and forecasting. Three main cycles in variations of daily mean temperature were revealed (period T approximately 2.25-3.25, 5.5 and 12.25 days, p < 0.05) until the 37th day of therapy, when a strongly decreasing trend of daily mean temperature emerged. The cycle of 2.25-3.25 days disappeared and the daily mean temperature continued to decrease significantly on the background of improvement of the clinical status. It was concluded that (1) cyclic patterns in daily mean temperature (periods T = 2.25-3.25 and 12.25 days) during the etiologic medication stages could be due to the life-cycle of 2-4 days of the cytomegalovirus and a cycle in the viral population growth, respectively. The above findings confirmed previous results on the period of viral DNA replication from in vitro studies. It was possible to forecast the right moment of replication and viral load to adjust the treatment schemes and improve the outcome; (2) the complex time-series approach has shown to be very useful and effective in analyzing and forecasting the temporal dynamics of daily mean temperature in order to optimize the clinical management in this particular case of an infant with CMV infection.

Antiviral Agents↗

PubMedDate not supplied

[Bayesian prediction of chloramphenicol blood levels in children with sepsis and malnutrition].

OBJECTIVE: To validate the population pharmacokinetic parameters of chloramphenicol in pediatric patients with sepsis and malnutrition (PPSM) using a bayesian forecasting program. DESIGN: Retrospective evaluation of predictive performance of a bayesian program in PPSM. SETTING: Tertiary care center. PATIENTS: Fifteen MPSP and ten NMPSP that receiving treatment with chloramphenicol. METHODS AND MAIN RESULTS: In the first part of the study, the medical records of 10 MPSP and 10 NMPSP who had received treatment with chloramphenicol were reviewed. The population pharmacokinetic parameter values for each group were estimated using a nonparametric expectation maximization algorithm (NPEM). In the second part, data gathered from five other MPSP receiving chloramphenicol were entered into a bayesian program. Chloramphenicol pharmacokinetic values for each of these five patients were estimated, first using the values of NMPSP as a priori distribution and then repeating the analysis using the MPSP values. The bayesian serum chloramphenicol concentrations predicted for each population model were compared with the actual peaks and troughs. The specific model for MPSP permitted forecasting the peak and trough serum chloramphenicol concentrations with less bias and a better precision compared with the NMPSP population model. CONCLUSIONS: These data indicate that chloramphenicol pharmacokinetics in PPSM can be predicted with minimal bias and good precision using a bayesian forecasting program, allowing a better control of the chloramphenicol serum concentrations. In addition, the limited number of samples required by the bayesian method may represent an important economical benefit for the patient.

Anti-Bacterial Agents↗

PubMed2003

[Prognosis of the course of complicated ulcer disease and mortality in aged and senile patients].

The developed system for forecasting the course of the disease in elderly and senile patients made it possible to distinguish two variants of the ulcer course: favorable and unfavorable. Its application confirmed that it is possible to use the forecast evaluation system in studies of remote results. In case of an unfavorable forecast, this provides the ground for urgent recommendations for surgical treatment in this group of patients without waiting for life-threatening complications to develop.

Aged↗

PubMed2002

Air pollution modeling: a tool for management of regional air quality.

Ambient air composition over the earth has undergone several changes. Anthropogenic pollutants generated locally often have regional air quality affected significantly. In addition to the short-term episodic effects, atmospheric pollutants are known to generate long-term adverse effects, which are difficult to forecast statistically. The air pollution dispersion modeling exercise forecasts fairly accurate air quality for a given emission scenario, incorporating geographical and meteorological conditions. Industrial Source Complex Dispersion Model is used to forecast ground level concentrations (GLC) of an industrial region as case study. The usefulness of mathematical modeling and computational simulation techniques used to predict the horizontal and vertical pollutant concentrations of pollutants are explained in this paper. Finally a case study of an industrial area in Gujarat region is presented to arrive at setting up of air quality monitoring station for monitoring/management of regional air quality.

Air Movements↗

PubMed2004

[Prognosis of the course of postoperative period after aortocoronary bypass procedure based on laboratory data].

The purpose of the case study was to define the decision rules for prognosticating, on the basis of laboratory data, the early postoperative clinical course after coronary artery bypass grafting. The method of discriminative analysis was made use in the resolution of tasks. The clinical data was based on the examination results of 508 patients after coronary artery bypass grafting with extracorporeal artificial blood circulation. The results are the detected biochemical and hematological parameters that can be used in prognosticating an early postoperative course and in constructing the linear discriminative functions for all days of the postoperative period, which makes it possible to forecast the risk of lethality with a probability of 85.71%. The above results can be equally used to prognosticate the below: linear discriminative functions for the second postoperative day ensuring the forecast of the risk of inflammatory complication with a probability of 91.67%; and linear discriminative functions for the fifth-sixth postoperative days ensuring the forecast of the lethal outcome with a probability of 83.33%.

Adult↗

PubMed2004

Trichothecene mycotoxins and their determinants in settled dust related to grain production.

We hypothesise that inhalant exposure to mycotoxins causes developmental outcomes and certain hormone-related cancers that are associated with grain farming in an epidemiological study. The aim of the present study was to identify and validate determinants of measured trichothecene mycotoxins in grain dust as work environmental trichothecene exposure indicators. Settled grain dust was collected in 92 Norwegian farms during seasons of 1999 and 2000. Production characteristics and climatic data were studied as determinants of trichothecenes in settled dust samples obtained during the production of barley (N = 59), oats (N = 32), and spring wheat (N = 13). Median concentrations of trichothecenes in grain dust were <20, 54, and < 50 mg/kg (ranges < 20-340, < 30-2400, and < 50-1200) for deoxynivalenol (DON), HT-2 toxin (HT-2) and T-2 toxin (T-2) respectively. Late blight potato rot (fungal) forecasts have been broadcast in Norway to help prevent this potato disease. Fungal forecasts representing wet, temperate, and humid meteorological conditions were identified as strong determinants of trichothecene mycotoxins in settled grain dust in this study. Differences in cereal species, production properties and districts contributed less to explain mycotoxin concentrations. Fungal forecasts are validated as indicators of mycotoxin exposure of grain farmers and their use in epidemiological studies may be warranted.

Agricultural Workers' Diseases↗