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PubMed2003

Forecasting, warning, and detection of malaria epidemics: a case study.

Our aim was to assess whether a combination of seasonal climate forecasts, monitoring of meteorological conditions, and early detection of cases could have helped to prevent the 2002 malaria emergency in the highlands of western Kenya. Seasonal climate forecasts did not anticipate the heavy rainfall. Rainfall data gave timely and reliable early warnings; but monthly surveillance of malaria out-patients gave no effective alarm, though it did help to confirm that normal rainfall conditions in Kisii Central and Gucha led to typical resurgent outbreaks whereas exceptional rainfall in Nandi and Kericho led to true malaria epidemics. Management of malaria in the highlands, including improved planning for the annual resurgent outbreak, augmented by simple central nationwide early warning, represents a feasible strategy for increasing epidemic preparedness in Kenya.

Climate↗

PubMed1998

A geographic information system forecast model for strategic control of fasciolosis in Ethiopia.

A geographic information system (GIS) forecast model based on moisture and thermal regime was developed to assess the risk of Fasciola hepatica, a temperate species, and its tropical counterpart, Fasciola gigantica, in Ethiopia. Agroecological map zones and corresponding environmental features that control the distribution and abundance of the disease and its snail intermediate hosts were imported from the Food and Agriculture Organization (FAO) Crop Production System Zones (CPSZ) database on east Africa and used to construct a GIS using ATLAS GIS 3.0 software. Base temperatures of 10 degrees C and 16 degrees C were used for F. hepatica and F. gigantica, respectively, to calculate growing degree days in a previously developed climate forecast system that was modified to allow use of monthly climate data values. The model was validated by comparison of risk indices and environmental features to available survey data on fasciolosis. Monthly Fasciola risk indices of four climatic regions in Ethiopia were used to project infection transmission patterns under varying climatic conditions and strategic chemotherapeutic fasciolosis control schemes. Varying degrees of F. hepatica risk occurred in most parts of the country and distinct regional F. hepatica transmission patterns could be identified. In the humid west, cercariae-shedding was predicted to occur from May to October. In the south it occurred from April to May and September to October, depending on the annual abundance of rain. In the north-central and central regions, risk was highest during heavy summer rains and pasture contamination with metacercariae was predicted to occur during August-September, except in wet years, when it may start as early as July and extend up to October. At cooler sites above altitude of 2800 m, completion of an infection cycle may require more than a year. Fasciola gigantica risk was present in the western, southern and north-central regions of the country at altitudes of 1440-2560 m. However, a transmission cycle could be completed in a single year only at elevations below 1700 m. The greatest risk of F. gigantica infection was in the humid western region. Regional strategic chemotherapy schemes of two or three treatments per year were developed. Results suggest that the model can be extrapolated to all CPSZ in the country and adapted for use in control of other vector-borne diseases of economic and public health importance.

Animals↗

PubMed2001

Antipsychotic prescription use and costs for persons with schizophrenia in the 1990s: current trends and five year time series forecasts.

Real advances in schizophrenia pharmacotherapy have been made over this decade with the development of more efficacious treatment options with fewer side-effects. These advances have high per-unit direct costs that may have a profound effect on drug budgets of systems caring for persons with schizophrenia. The objective of this study was to describe the changes in utilization and cost for antipsychotic prescriptions by atypical, clozapine, decanoate products, and traditional neuroleptics in a large naturalistic setting, i.e. the Georgia Medicaid population. Secondly, this study forecasted the categorized antipsychotic prescription utilization through the year 2002. Administrative claims data spanning 1990-1997 for Medicaid eligible persons suffering from schizophrenia in the state of Georgia were supplemented with psychiatric institutional data obtained from the Georgia Department of Human Resources. A total of 16227 Medicaid-eligible recipients had a code indicative of schizophrenia (ICD-9-CM=295.(**)) and were at least 16 years of age at the time of their first diagnosis. The mean recipient prescription use and expenditures were tallied for each month of the study and stratified by prescription category (atypical, clozapine, decanoate, and traditional antipsychotic). ARIMA time series models were identified and estimated using these monthly PMPM utilization and expenditures estimates to forecast 5 years beyond the last month of the study. The total use of antipsychotics increased modestly throughout the study period, and the use of atypicals, clozapine, and decanoate products increased substantially, while a decrease was observed for traditional antipsychotics. In 1995 dollars, antipsychotic expenditures increased from a mean of approximately $10 PMPM in 1990 to $95 projected for the year 2002. This transition from traditional oral antipsychotics to atypicals and decanoate products has a profound effect on drug expenditures for systems paying for the care of persons with schizophrenia. Further studies to determine the value of the transitions of therapy described in this study need to be evaluated using a system-wide- or Medicaid perspective.

Adult↗

PubMedDate not supplied

Forecasting medical work at mass-gathering events: predictive model versus retrospective review.

INTRODUCTION: Mass-gathering events are dynamic and challenge traditional medical management systems. To improve the system for the provision of first aid at mass-gathering events, an evaluation of two models that assist in forecasting the number of patients presenting for first-aid services was conducted. METHOD: A prospective evaluation of a recurrent, mass-gathering event was undertaken comparing predicted patient presentations and ambulance transfers generated by a predictive model developed by Arbon et al and a retrospective review of seven years of historical, event data as described by Zeitz et al. RESULTS: Patient presentation rate (per 1,000 patrons) for this event was 1.6 and the transport to hospital rate (per 1,000 patrons) was 0.07. The retrospective review closely predicted the actual overall attendance. Both methods forecast the number of patients presenting on a daily basis. The prediction proved to be more accurate, on a day-by-day basis, using the Zeitz method. CONCLUSION: The Arbon method is particularly useful for events where there is no or limited information about previous medical work. Retrospective review of data generated from specific events (Zeitz method) considers the unique and individual variability that can occur from event to event and is more accurate at predicting patient presentations when the data are available. Both methods have the potential to be used more frequently to adequately and efficiently plan for the resources required for specific events.

Ambulances↗

PubMedDate not supplied

An atlas of forecasted molecular data. 2. Vibration frequencies of main-group and transition-metal neutral gas-phase diatomic molecules in the ground state.

This atlas of diatomic-molecular vibration frequencies parallels the previously offered Atlas of Internuclear Separations. The Atlas was produced by mining the data from Huber and Herzberg and training neural network software to forecast new data. New protocols were employed with the powerful software, which was originally designed for forecasting the financial markets. The Atlas presents 1920 additional vibration frequencies for use until critical tables are available to fill the needs more precisely. The precision of the predictions is characterized by the average fractional 1% confidence limit, that is, 10.66%. The accuracies of the predictions are determined in two ways. First, 221 of the 224 Huber and Herzberg data values used for training and validation fall within the prediction confidence limits or fall outside by less than 10% of the Huber and Herzberg values, and 181 values agree (within the limits). Second, 87 of 101 comparison data values, consisting of literature data and some additional Huber and Herzberg values, fall within the prediction confidence limits or fall outside by less than half the prediction values, and 44 of the 101 values agree (within the limits).

Journal Article↗

PubMed1999

Forecasting the in vivo performance of four low solubility drugs from their in vitro dissolution data.

PURPOSE: To assess the usefulness of biorelevant dissolution tests in predicting food and formulation effects on the absorption of four poorly soluble, lipophilic drugs. METHODS. Dissolution was studied with USP Apparatus II in water, milk, SIFsp, FaSSIF, and FeSSIF. The in vitro dissolution data were compared on a rank order basis with existing in vivo data for the tested products under fasted and fed state conditions. RESULTS: All drugs/formulations showed more complete dissolution in bile salt/lecithin containing media and in milk than in water and SIFsp (USP 23). Comparisons of the in vitro dissolution data in biorelevant media with in vivo data showed that in all cases it was possible to forecast food effects and differences in absorption between products of the same drug with the physiologically relevant media (FaSSIF, FeSSIF and milk). Differences between products (both in vitro or in vivo) were less pronounced than differences due to media composition (in vitro) or dosing conditions (in vivo). CONCLUSIONS: Although biorelevant dissolution tests still have issues which will require further refinement, they offer a promising in vitro tool for forecasting the in vivo performance of poorly soluble drugs.

Adamantane↗

PubMed2006

Alone but feeling no pain: Effects of social exclusion on physical pain tolerance and pain threshold, affective forecasting, and interpersonal empathy.

Prior findings of emotional numbness (rather than distress) among socially excluded persons led the authors to investigate whether exclusion causes a far-reaching insensitivity to both physical and emotional pain. Experiments 1-4 showed that receiving an ostensibly diagnostic forecast of a lonesome future life reduced sensitivity to physical pain, as indicated by both (higher) thresholds and tolerance. Exclusion also caused emotional insensitivity, as indicated by reductions in affective forecasting of joy or woe over a future football outcome (Experiment 3), as well as lesser empathizing with another person's suffering from either romantic breakup (Experiment 4) or a broken leg (Experiment 5). The insensitivities to pain and emotion were highly intercorrelated.

Adolescent↗

PubMed2000

Quantifying the uncertainty in forecasts of anthropogenic climate change

Forecasts of climate change are inevitably uncertain. It is therefore essential to quantify the risk of significant departures from the predicted response to a given emission scenario. Previous analyses of this risk have been based either on expert opinion, perturbation analysis of simplified climate models or the comparison of predictions from general circulation models. Recent observed changes that appear to be attributable to human influence provide a powerful constraint on the uncertainties in multi-decadal forecasts. Here we assess the range of warming rates over the coming 50 years that are consistent with the observed near-surface temperature record as well as with the overall patterns of response predicted by several general circulation models. We expect global mean temperatures in the decade 2036-46 to be 1-2.5 K warmer than in pre-industrial times under a 'business as usual' emission scenario. This range is relatively robust to errors in the models' climate sensitivity, rate of oceanic heat uptake or global response to sulphate aerosols as long as these errors are persistent over time. Substantial changes in the current balance of greenhouse warming and sulphate aerosol cooling would, however, increase the uncertainty. Unlike 50-year warming rates, the final equilibrium warming after the atmospheric composition stabilizes remains very uncertain, despite the evidence provided by the emerging signal.

Journal Article↗

PubMed2003

Rapid i.v. loading with phenytoin with subsequent dose adaptation using non-steady-state serum levels and a Bayesian forecasting computer program to predict maintenance doses.

OBJECTIVE: To evaluate the suitability of a phenytoin loading dose regimen; to assess whether dose-individualization was necessary and to investigate the reliability of a Bayesian forecasting method for phenytoin dose adaptation using non-steady-state levels in hospital-admitted patients. METHOD: An initial loading dose (15 mg phenytoin acid/kg BW) was given i.v. over 4 h, followed by standardized maintenance doses given i.v. in 12-h intervals from days 1 to 5 (175 mg </= 70 kg; 202 mg > 70 kg BW). The evening dose of day 5 was individualized based on three serum trough levels: L1 (after 16 h), L2 (morning day 4) and L3 (morning day 5). RESULTS: Ninety of 136 consecutive patients were evaluable in a prospective study for the standardized phase; 50 of them had additional serum levels in the individualized phase. There was no exclusion of patients with interacting co-medication. Seventy-seven per cent (L1) and 68% (L3) of patients showed therapeutic values (10-20 mg/L). The prediction error of the forecasting was 3.95 mg/L, the root mean squared error 6.27 mg/L (target trough level 11 mg/L). Seventy per cent of the levels (n=50) were within the 68% confidence interval. CONCLUSION: The effectiveness and safety of the regimen with rapid i.v. loading and the necessity to individualize phenytoin dosing after day 5 were demonstrated.

Adolescent↗

PubMed1999

Regional variations in grass pollen seasons in the UK, long-term trends and forecast models.

BACKGROUND: Three sites in the UK have daily records of pollen spanning several decades, giving the longest data sets worldwide. Previous research on London data revealed decreasing severity of grass pollen seasons. This is often taken as a model for the whole country but comparisons with Derby and Cardiff, in different regions of local climate and land-use, emphasize the need for regional studies. OBJECTIVE: The grass pollen seasons were analysed for three contrasting long-term sites to provide regional insight into the changing incidence of hay fever. METHODS: Pollen was monitored by volumetric instruments using standard techniques. Data have been taken from 1961 to 1993 to examine variation in grass pollen seasons in relation to land-use changes, cumulative temperatures and rainfall. Models were developed to predict total seasonal catches. RESULTS: At Cardiff the annual counts and severity increased in the 1960s, declined in the 1970s and rose again in the 1980s. At Derby and London the annual counts and severity declined but at different rates. Start dates have tended to become earlier at Cardiff and Derby, but later at London. Trends in annual counts and severity are similar to changes in grassland areas but they cannot be accounted for entirely by these. Weather in spring and early summer has tended to become warmer but there are no sustained patterns in June and July. No trends are apparent in the rainfall records for these months. The maximum explanation (r2 >/= 95%) in forecast models was obtained using 10-day aggregates of weather. CONCLUSION: The contrasting patterns both in the pollen records and land-use changes between the three sites emphasize the need for regional data. The predictive models achieved a high degree of explanation enabling pollen season severity to be forecast with high confidence shortly before the start date.

Humans↗

PubMed1975

Reliability of forecasts of annoyance reactions. A study of exposure to noise and air pollution.

Studies of the effect of external environmental factors on the individual are often carried out in order to obtain a basis for forecasts. The aim of the case studies reported has been to check the reliability of predictions of annoyance from four different external sources of discomfort. The results confirm the assumption that forecasts based on empirical studies provide a reliable picture of what the occurrence and extent of the annoyance reactions will be.

Air Pollution↗

PubMed2000

Forecasting summertime surface-level ozone concentrations in the Lower Fraser Valley of British Columbia: an ensemble neural network approach.

Empirical models for predicting daily maximum hourly average ozone concentrations were developed for 10 monitoring stations in the Lower Fraser Valley (LFV) of British Columbia. According to data from 1991 to 1996, ensemble neural network models increased explained variance an average of 7% over multiple linear regression models using the same input variables. Without modification, all models performed poorly on days when the observed peak ozone concentration exceeded 82 parts per billion, the National Ambient Air Quality Objective. When numbers of extreme events in training data were increased using a histogram equalization process, models were able to forecast exceedances with improved accuracy. Modified generalized additive model (GAM) plots and associated measures of input variable importance and interaction were generated for a subset of the trained models and used to investigate relationships between input variables and ozone levels. The neural network models displayed a high degree of interaction among inputs, and it is likely the ability of these model types to account for interactions, rather than the nonlinearity of individual input variables, that explains their improved forecast skill. Inspection of GAM-style plots indicated that the relative importance of input variables in the ensemble neural network models varied with geographic location within the LFV. Four distinct groups of stations were identified, and rankings of inputs within the groups were generally consistent with physical intuition and results of prior studies.

Algorithms↗

PubMed1999

Forecasting surgical groups' total hours of elective cases for allocation of block time: application of time series analysis to operating room management.

BACKGROUND: Allocation of the correct amount of operating room (OR) "block time" can provide surgeons with access to sufficient OR time to complete their elective cases while optimally matching staffing with the elective case workload (to maximize labor productivity). To evaluate how to predict accurately total hours of elective cases performed by a surgical group using data from surgical services information systems, the authors addressed the following questions: (1) How many previous 4-week periods of data should be used to minimize error in forecasting a surgical group's total hours of elective cases? (2) Using the number of 4-week periods from question #1, can we detect trends or correlations between successive periods that could be used to improve forecasting accuracy? (3) How can results from questions #1 and #2 be used to calculate an upper prediction bound (upper limit) for the total hours of elective cases that will be completed in a future period? Prediction bounds can be used to budget staffing accurately. METHODS: Time series analysis was performed on total hours of elective cases over 39 consecutive 4-week periods from 17 surgical groups. RESULTS: The average of 12 consecutive periods' total hours of elective cases had an appropriate error profile. The observations within each series of 12 consecutive 4-week periods followed a normal distribution, with each observation of total hours of elective cases not correlated with the subsequent observation. CONCLUSIONS: The average of the most recent 12 4-week periods can be used to predict surgical groups' future use of block time.

Algorithms↗

PubMed1986

A graphical method for forecasting radiation exposure from multi-aged fallout from nuclear weapons.

After a nuclear attack it may be necessary for emergency workers, such as firemen, utility workers and medical personnel, to perform urgent tasks in areas highly contaminated by radioactive fallout. To assist the control of radiation exposure of these workers, it will be useful to provide means to forecast radiation exposures both inside and outside the fallout shelter. The method described in this paper is intended for use during the first few days to weeks after the attack, after which time more sophisticated methods may become available. This method requires only a radiation-rate meter, special graph paper, and a timepiece. Communications with Emergency Operating Centers or other sources of information are not necessary. The method permits the determination of the age of fallout and future exposure rates for a location that might be subjected to a number of different fallout clouds, without requiring knowledge of the weapon yields or times of detonation. This method will provide results with less accuracy if different-aged fallout clouds arrive simultaneously. The method is self-correcting so that if the actual decay rate is different than that which is assumed, the forecasted rates will have less error than results obtained by previous methods.

Nuclear Warfare↗

PubMed1993

Bayesian forecasting of gentamicin pharmacokinetics in pediatric intensive care unit patients.

The predictive performance of a one compartment Bayesian forecasting program was evaluated in pediatric intensive care unit patients with normal renal function. Gentamicin pharmacokinetic parameters were determined in 44 PICU patients (0.8 month to 14 years old) from all available serum concentrations and doses by nonlinear least squares regression. Population pharmacokinetic parameter estimates were established from 27 of the PICU patients. Mean prediction error (ME) and mean absolute error (MAE) for 2 future sets of peak and trough gentamicin serum concentrations with the use of the population parameter estimates with and without feedback were evaluated in the remaining 17 patients. Mean clearance (+/- SD) and volume of distribution for all 44 patients were 0.123 +/- 0.041 liter/hour/kg and 0.424 +/- 0.116 liter/kg, respectively. Bayesian forecasting of the second set of peak and trough concentrations with feedback from the first set of peak and trough concentrations resulted in smaller bias (peak ME, -0.15 mg/liter; trough ME, 0.13 mg/liter) and better accuracy (peak MAE, 0.91 mg/liter; trough MAE, 0.28 mg/liter) compared with the population parameter estimates alone (peak ME, 0.4 mg/liter; trough ME, 0.28 mg/liter; peak MAE, 1.21 mg/liter; trough MAE, 0.57 mg/liter). This study indicates that gentamicin volume of distribution in PICU patients is larger than non-PICU literature values. The Bayesian program, with specific population parameter estimates for PICU patients, provides accurate initial and subsequent predictions of gentamicin serum concentrations.

Adolescent↗

PubMed1988

An approach to forecast aminoglycoside-related nephrotoxicity from routinely collected clinical data.

Routinely collected clinical data on 104 critically ill patients who had received an aminoglycoside (gentamicin or tobramycin) were evaluated using a proposed approach to forecast aminoglycoside-related nephrotoxicity. Observed steady-state peak and trough concentrations were greater than the respective predicted values when one-compartment model was assumed. This difference was particularly eminent for trough concentrations. The bias (difference between predicted and observed values) for trough concentrations was analyzed assuming tissue accumulation by an extended least-squares method to estimate population pharmacokinetics. The mean values for terminal half-life of gentamicin and tobramycin in patients who did not develop nephrotoxicity were estimated to be approximately 50 and 116 h, respectively. By using these values, the bias of trough concentration was found to be greater in patients who developed nephrotoxicity during or within 60 days after the therapy than in those who did not. Our results suggest that assessing the bias of steady-state trough concentrations of aminoglycosides can provide a useful index to forecast an aminoglycoside-induced nephrotoxicity.

Adolescent↗

PubMed1994

Bayesian forecasting of serum vancomycin concentrations with non-steady-state sampling strategies.

The application of three non-steady-state sampling strategies and the fitting of either three or five pharmacokinetic parameter estimates by a two-compartment Bayesian forecasting program was evaluated retrospectively in 27 adult patients with stable renal function. Sampling strategies included a single midpoint concentration, a set of peak and trough concentrations, and three serial vancomycin concentrations. The most precise and least-bias predictions of steady-state peak vancomycin concentrations were observed by using population-based parameter estimates [mean prediction error (ME) = -0.40 and mean absolute error = 5.77]. The addition of non-steady-state feedback concentration(s) did not provide additional information for predictions of future steady-state peak concentrations. The least-bias prediction of steady-state trough vancomycin concentrations was seen when a single midpoint non-steady-state concentration was used (ME = 0.92 and -0.17 for five and three fitted parameter estimates, respectively). The MEs of serial and peak and trough feedback strategies were similar in magnitude to those obtained using population parameters, but in opposite directions (underprediction vs. overprediction, respectively). The fitting of only three parameters produced results similar to those using five parameters. The results from this study confirm our previous evaluation that non-steady-state concentrations provide very minimal information to Bayesian forecasting of future steady-state concentrations.

Adult↗

PubMed1995

Bayesian forecasting of serum vancomycin concentrations in neonates and infants.

A dynamic pharmacokinetic model for i.v. vancomycin administration was developed and tested in 47 neonates and infants. Twenty-nine patients (Group 1), having two or more concentrations, were used to estimate population parameters by nonlinear least-squares analysis. Multiple stepwise linear regression techniques showed that estimated creatinine clearance, Clcr, and postnatal age were significant demographic factors related to vancomycin clearance (CL). No strong associations were found for the apparent volume of distribution. A one-compartment model was constructed using the associations of CLcr and postnatal age with vancomycin CL. Eighteen patients (Group 2), receiving 35 courses of vancomycin therapy, with both initial and subsequent sets of peak and trough concentrations, were used to test the predictive performance of the model with and without the use of Bayesian forecasting. Using only population-based parameters, the respective mean error (ME) (bias) and mean absolute error (MAE) (precision) for predicting subsequent peak concentrations were -1.20 and 3.89 mg/L and for trough concentrations, 0.83 and 2.23 mg/L, respectively. For the Bayesian method, these values were, respectively, 0.45 and 4.13 mg/L for peak concentrations and 1.55 and 2.40 mg/L for trough concentrations. When predicted concentrations occurred within 30 days of feedback concentrations, the Bayesian method tended to be slightly less biased and more precise than the population-based parameters. The opposite was true > 30 days of the initial set of feedback concentrations. The use of population-specific pharmacokinetic parameters and Bayesian forecasting should allow accurate dosage regimen design as well as minimize the need for monitoring serum vancomycin concentrations in neonates and young infants.

Bayes Theorem↗