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PubMed1975

The future of medical eduction: forecast of the Council of Deans.

This paper reports the results of a Delphi probe of the perceptions of medical school deans regarding the most significant changes in medical education and in the health care system which they expect to influence medical education over the next 20 years. The study, conducted in the first quarter of 1974, included an analysis of 54 potential changes distilled from over 440 suggestions. A composite view of the probability of occurring, impact on the system and percentage of deans favoring the change are presented. In general, the future is believed to hold more positive changes than negative ones, and those most likely to occur will come about in the near term. The results disclose few surprising conclusions but provide a structural description of areas of consensus and disagreement among deans.

Delivery of Health Care↗
PubMed1983

Forecasting optometry grade point average.

Preoptometry grades. Optometry College Admission Test (OCAT) scores, and a number of other variables were evaluated as predictors of the grade point average earned by optometry students (N = 494) after two years at Southern California College of Optomery. The OCAT Quantitative Ability test was found to be the best single predictor (r = +0.37). This prediction was enhanced (multiple r = +0.55) with the addition of the OCAT Study Reading test score, preoptometry grade point average in college mathematics and science courses, and a rating of the preoptometry college attended. A predicted grade point average for optometry school courses was computed for each student by additively combining these variables, weighted according to their relative predictive validities. By comparing the computed values of students who actually earned a high grade point average in optometry school with those whose average was low, we were able to establish a predicted grade point cutoff score. It is shown that this can be useful in evaluating the potential of an applicant to achieve academic success in optometry school.

Achievement↗
PubMed1987

Forecasting asthmatic wheezing using temperature velocity.

A model was constructed to predict pediatric asthmatic wheezing visits to the emergency department. All wheezing visits to the Children's Hospital of Philadelphia Emergency Department were analyzed for 1982 and 1983, for ages two to 18. Nine thousand four hundred twenty-five visits fit the study requirements, 27% of the total number of emergency department visits for all causes. The a priori hypothesis used to construct the model was that temperature change, not absolute temperature, would be a good predictor of emergency department visits. Although not attempting to prove a cause-and-effect relationship, by studying temperature velocity (the rate of change of temperature) and the direction of change of temperature (a seasonal variable reflecting rising or falling temperature), a model was created that was highly significant (P less than 0.0001) and could explain 35% of the daily variation in asthmatic emergency department visits (R2 = 35%, r = 0.59). When weekly emergency department visits were analyzed, the model could explain 49% of the variation in the number of emergency department visits (R2 = 49%, r = 0.70). Carbon monoxide, barometric pressure, and relative humidity were also statistically significant predictors but were clinically insignificant, explaining only a few percentage points of the total variation. By taking advantage of the seasonal pattern of wheezing through the use of temperature velocity, predictive models for asthmatic wheezing can be greatly improved. They may also aid in planning emergency department staffing, and even help prevent emergency department visits by premedication or lifestyle change during high-risk periods.

Adolescent↗
PubMed2005

Forecasting changes in amphibian biodiversity: aiming at a moving target.

Amphibian population declines and sudden species' extinctions began to be noted at the beginning of the 1980s. Understanding the causes of the losses is hampered by our poor knowledge of the amphibian fauna in many parts of the world. Amphibian taxa are still being described at a high rate, especially in the tropics, which means that even quantifying species lost as a percentage of the current fauna can be a misleading statistic in some parts of the globe. The number of species that have gone missing is only one measure of the loss of biodiversity. Long-term studies of single-species populations are needed, but this approach has its limits. Amphibian populations often show great annual variation in population size making it difficult, if not impossible, to use short-term studies as a basis for deciding if a population is increasing or decreasing in the long term. Aggregating single studies into databases and searching for patterns of variation is a way of overcoming this limitation. Several databases on species and population time series are available or in development. These records show that declines are continuing worldwide with some species and populations, especially in the tropics and at higher elevations, at greater risk of extinction than others. Unfortunately, amphibian databases with population time series have much less information for the tropics compared to the temperate zone, and less for Africa and Asia compared with Europe and North America. Focusing limited resources using comprehensive statistical designs is a way to maximize the efficiency and effectiveness of monitoring efforts. It is clear that, in the first decades of the twenty-first century, the regions of the globe with the highest diversity of amphibian species will experience the greatest rates of decrease of forests and increase in human population size, fertilizer use, agricultural production, creation of new croplands and irrigation. Many of these changes are likely negatively to affect amphibian species diversity, and their influence must be understood before concluding, at least for amphibians, that the 2010 millennium assessment goal of significantly reversing the rate of loss of Earth's biodiversity can be met.

Amphibians↗
PubMed2001

Predicting dose-time profiles of solar energetic particle events using Bayesian forecasting methods.

Bayesian inference techniques, coupled with Markov chain Monte Carlo sampling methods, are used to predict dose-time profiles for energetic solar particle events. Inputs into the predictive methodology are dose and dose-rate measurements obtained early in the event. Surrogate dose values are grouped in hierarchical models to express relationships among similar solar particle events. Models assume nonlinear, sigmoidal growth for dose throughout an event. Markov chain Monte Carlo methods are used to sample from Bayesian posterior predictive distributions for dose and dose rate. Example predictions are provided for the November 8, 2000, and August 12, 1989, solar particle events.

Bayes Theorem↗
PubMed1998

Environmental information systems in malaria risk mapping and epidemic forecasting.

Every year between one and two million African children under five die of malaria. If one adds to this the contribution of malaria to all-cause infant mortality then clearly the burden of the disease is catastrophic--a disaster quietly happening each and every year. New tools are needed urgently to support those currently available for control of the disease. An effective vaccine remains elusive. This article outlines the potential contribution to malaria control services of satellite information, which is being used by resource managers in other sectors. In particular, it highlights the lessons which can be learned from early warning systems in other areas, especially those designed to respond to famine. An appendix provides a brief introduction to satellite data and their interpretation.

Africa South of the Sahara↗
PubMed2006

Forecasting the spread of invasive rainbow smelt in the Laurentian Great Lakes region of North America.

Rainbow smelt (Osmerus mordax) have invaded many North American lakes, often resulting in the extirpation of native fish populations. Yet, their invasion is incipient and provides the rationale for identifying ecosystems likely to be invaded and where management and prevention efforts should be focused. To predict smelt presence and absence, we constructed a classification-tree model based on habitat data from 354 lakes in the native range for smelt in southern Maine. Maximum lake depth, lake area, and Secchi depth (surrogate measure of lake productivity) were the most important predictors. We then used our model to identify lakes vulnerable to invasion in three regions outside the smelt's native range: northern Maine (52 of 244 lakes in the non-native range), Ontario (4447 of 8110), and Wisconsin (553 of 5164). We further identified a subset of lakes with a strong potential for impact (potential-impact lakes) based on the presence of fish species that are affected by rainbow smelt. Ninety-four percent of vulnerable lakes in the non-native range in Maine are also potential-impact lakes, as are 94% and 58% of Ontario and Wisconsin's vulnerable lakes, respectively. Our modeling approach can be applied to other invaders and regions to identify invasion-prone ecosystems, thus aiding in the management of invasive species and the efficient allocation of invasive species mitigation and prevention resources.

Animals↗