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PubMed2005

Forecasting municipal solid waste generation in a fast-growing urban region with system dynamics modeling.

Both planning and design of municipal solid waste management systems require accurate prediction of solid waste generation. Yet achieving the anticipated prediction accuracy with regard to the generation trends facing many fast-growing regions is quite challenging. The lack of complete historical records of solid waste quantity and quality due to insufficient budget and unavailable management capacity has resulted in a situation that makes the long-term system planning and/or short-term expansion programs intangible. To effectively handle these problems based on limited data samples, a new analytical approach capable of addressing socioeconomic and environmental situations must be developed and applied for fulfilling the prediction analysis of solid waste generation with reasonable accuracy. This study presents a new approach--system dynamics modeling--for the prediction of solid waste generation in a fast-growing urban area based on a set of limited samples. To address the impact on sustainable development city wide, the practical implementation was assessed by a case study in the city of San Antonio, Texas (USA). This area is becoming one of the fastest-growing regions in North America due to the economic impact of the North American Free Trade Agreement (NAFTA). The analysis presents various trends of solid waste generation associated with five different solid waste generation models using a system dynamics simulation tool--Stella. Research findings clearly indicate that such a new forecasting approach may cover a variety of possible causative models and track inevitable uncertainties down when traditional statistical least-squares regression methods are unable to handle such issues.

Cities↗

PubMed1979

Forecasting health manpower requirements: the case of thoracic surgeons.

This paper presents projections of the future demand for thoracic surgery. Estimates of the future supplies of thoracic surgeons are constructed based on three alternative annual Board-certification rates. The consequences of varying supplies of thoracic surgeons, for a given level of expected demand, are presented in terms of expected work-load levels. Since it is costly to society if there are too few thoracic surgeons and since it is an obvious waste of resources if there are too many, no single estimate for an optimal annual increase in the number of thoracic surgeons is suggested. Important inadequacies of data for both forecasting demand and determining work loads are noted.

Certification↗

PubMed2001

Forecasting the consequences of accidental releases of radionuclides in the atmosphere from ensemble dispersion modelling.

The RTMOD system is presented as a tool for the intercomparison of long-range dispersion models as well as a system for support of decision making. RTMOD is an internet-based procedure that collects the results of more than 20 models used around the world to predict the transport and deposition of radioactive releases in the atmosphere. It allows the real-time acquisition of model results and their intercomparison. Taking advantage of the availability of several model results, the system can also be used as a tool to support decision making in case of emergency. The new concept of ensemble dispersion modelling is introduced which is the basis for the decision-making application of RTMOD. New statistical parameters are presented that allow gathering the results of several models to produce a single dispersion forecast. The devised parameters are presented and tested on the results of RTMOD exercises.

Air Movements↗

PubMed1998

Multi-drug resistant tuberculosis in Finland--a forecast.

Since the collapse of the Soviet system, travel between the St Petersburg district and the Baltic states and Finland has increased substantially. Although it is difficult to obtain exact figures on the number of cases of tuberculosis (TB) and multi-drug resistant (MDR) TB in these countries, there is strong evidence of growing epidemics, bringing added epidemiological threat to Finland. The purpose of this study is to produce a short-term "worst case" forecast of the spatial development of a threatened MDR-TB epidemic in Finland. The method applied is a chorological multistep procedure using statistical and geographical methods and a simulation technique. Instead of focusing on populations of carriers and susceptibles, emphasis is placed on identifying the primary influences directing the epidemic as a spatial process. This was done by dividing Finland into small-area units and by assigning the risk of obtaining MDR-TB to each unit based on socioeconomic and structural characteristics of the population. The simulated 6 year cumulative distribution of new MDR-TB cases showed a marked concentration of cases in the capital region and in a cluster of municipalities along the west coast. Although socioeconomic factors are important in explaining the distribution of cases, frequent and widespread international contacts seemed to be equally important at the beginning of the epidemic.

Disease Outbreaks↗

PubMed2000

Forecasting blowfly strike in Queensland sheep flocks.

The occurrence of blowfly strike between 1993 and 1999, derived from the reported use of pesticides for flystrike control, was investigated in 247 sheep flocks in Queensland, Australia using autoregressive techniques. Although there was a small increase (0. 0016 per year) in flystrike incidence during the study period, this long-term linear trend was not significant (p=0.53). The occurrence of flystrike was best described by an autoregressive model that included flystrike in the previous 2 months: flystrike(t)=0.0170+0. 0392 flystrike(t-1)+0.3589 flystrike(t-2). Flystrike was associated with the southern oscillation index (SOI). The SOI is based on barometric pressure readings and is associated with periods of below- (negative SOI) and above-average (positive SOI) rainfall in northern Australia. Flystrike incidence was significantly (p=0.03) greater in months in which the SOI was positive. The strongest correlation (r=0.33) was found between flystrike incidence and the SOI 2 months previously. Using the SOI, the best-fitting autoregressive model describing flystrike was flystrike(t)=0.0238+0. 3033 flystrike(t-2)+0.0009 SOI(t-2). The incidence of flystrike was significantly (p<0.05) correlated with average monthly radiation (r=0.26), but not with average monthly maximum and minimum temperature, total rainfall, evaporation and vapour pressure. The best-fitting autoregressive model describing flystrike occurrence based on these variables was flystrike(t)=-0.0259+0.3610 flystrike(t-2)+0.0022 radiation(t). Results suggest that a useful early-warning system could be developed based on the correlation between flystrike incidence and the SOI up to 2 months previously. Such attempts to forecast flystrike may assist decision-making by wool producers with respect to flystrike control options, leading to more efficient control of blowfly strike in their industry.

Animals↗

PubMed2006

[Impact and forecasting of hepatitis A immunization in French armed forces, 1990-2004].

BACKGROUND: Hepatitis A is a public health problem specially for migrants or travellers from industrialized countries with a low hepatitis A endemic level. French armed forces adopted an immunization strategy which first targeted overseas forces and subsequently was extended to all armed forces. In this work we studied the impact of this policy. METHODS: Epidemiological surveillance data from 1990 to 2004 was analyzed by Poisson regression and exponential models of decrease used to forecast future rates. RESULTS: From the 826 cases of hepatitis A reported during the study period, 266 (32.2%) occurred in overseas forces and 560 (67.8%) in forces stationed in France. Three periods could be identified in the decline of annual incidence: before 1994, with an average rate of 23.2 per 100,000; from 1994 to 1998: 10.2; and after 1998: 1.2 for all French armed forces. For overseas armed forces, the average rate was 117 per 100,000 before 1994 and 17.1 from 1994 to 1998 (p<0.001). For armed forces stationed in France, the average rate was 12.2 per 100,000 before 1998 and 0.9 after (p<0.001). For overseas armed forces, models clearly described the declining incidence subsequent to targeted immunization in 1995 and for armed forces stationed in France, the decline with generalized immunization starting in 1998. DISCUSSION: The impact of immunization against hepatitis A virus was significant both in an overseas population and in a population staying in France where the risk level can be considered low due to the low endemic rate in France. These results suggest that immunization should be proposed not only for travellers but also for the general population based on real knowledge of the situation and cost-effectiveness analyses.

Forecasting↗

PubMed1993

Suggestions for forecasting and monitoring facial growth.

If facial improvement is to be an objective of orthodontic treatment, it is first necessary to define good looks. For various reasons this has been a neglected field of research. This article draws on both previous and new research to define the basis of attractiveness, and then describes methods by which these features can be indexed. The use of such measurements is recommended for forecasting growth, and for monitoring it before, during, and after treatment.

Beauty↗

PubMedDate not supplied

Fuzzy neural identification and forecasting techniques to process experimental urban air pollution data.

This paper focuses on the processing of experimentally measured pollution data. Measuring locally both air quality parameters and atmospheric data can show how complex can be their interrelations and how they change spatially. Furthermore, apart from physical and biochemical dependencies, two important aspects need to be incorporated in the model, traffic data and topographic information, like presence and configuration of buildings and roads. Since estimating the evolution of pollutant in the urban air can have significant economic impact already on a short term basis as well as relevant consequences on public health on a medium-long term scale, various interdisciplinary researches are under way on this subject. In this work, we pursue two goals. The first one is to derive a representative model of the multivariate relationships that should be able to reproduce local interactions; the second goal of the paper is to predict, when possible, the short term evolution of pollutants in order to prevent the onset of above threshold levels of pollutants that can be dangerous to humans. The threshold levels of interest are fixed by both EU recommendations and regional regulations. As a by-product of the research, we could derive some directives to be supplied to local authorities to properly organize car traffic in advance based on the estimated parameters. The case study here proposed is that of Villa San Giovanni, a small town at the tip of Italy, located just in front of Sicily, on the Messina Strait. This is a significant case, since the city is affected by the heavy traffic directed (and coming from) Sicily. The main results here reported include the short time prediction of the concentration of hydrocarbons (HC) in the local air, the comparison between different methods based on fuzzy neural systems, and the proposal of local models of non-linear interactions among traffic, atmospheric and pollution data. Additionally, comments on a longer horizon forecast are given.

Air Pollution↗

PubMed2004

Assessing the accuracy of forecasting: applying standard diagnostic assessment tools to a health technology early warning system.

OBJECTIVES: Early warning systems are an integral part of many health technology assessment programs. Despite this finding, to date, there have been no quantitative evaluations of the accuracy of predictions made by these systems. We report a study evaluating the accuracy of predictions made by the main United Kingdom early warning system. METHODS: As prediction of impact is analogous to diagnosis, a method normally applied to determine the accuracy of diagnostic tests was used. The sensitivity, specificity, and predictive values of the National Horizon Scanning Centre's prediction methods were estimated with reference to an (imperfect) gold standard, that is, expert opinion of impact 3 to 5 years after prediction. RESULTS: The sensitivity of predictions was 71 percent (95 percent confidence interval [CI], 0.36-0.92), and the specificity was 73 percent (95 percent CI, 0.64-0.8). The negative predictive value was 98 percent (95 percent CI, 0.92-0.99), and the positive predictive value was 14 percent (95 percent CI, 0.06-0.3). CONCLUSIONS: Forecasting is difficult, but the results suggest that this early warning system's predictions have an acceptable level of accuracy. However, there are caveats. The first is that early warning systems may themselves reduce the impact of a technology, as helping to control adoption and diffusion is their main purpose. The second is that the use of an imperfect gold standard may bias the results. As early warning systems are viewed as an increasingly important component of health technology assessment and decision making, their outcomes must be evaluated. The method used here should be investigated further and the accuracy of other early warning systems explored.

Diagnostic Techniques and Procedures↗

PubMed2006

Real-time epidemic forecasting for pandemic influenza.

The ongoing worldwide spread of the H5N1 influenza virus in birds has increased concerns of a new human influenza pandemic and a number of surveillance initiatives are planned, or are in place, to monitor the impact of a pandemic in near real-time. Using epidemiological data collected during the early stages of an outbreak, we show how the timing of the maximum prevalence of the pandemic wave, along with its amplitude and duration, might be predicted by fitting a mass-action epidemic model to the surveillance data by standard regression analysis. This method is validated by applying the model to routine data collected in the United Kingdom during the different waves of the previous three pandemics. The success of the method in forecasting historical prevalence suggests that such outbreaks conform reasonably well to the theoretical model, a factor which may be exploited in a future pandemic to update ongoing planning and response.

Disease Outbreaks↗

PubMed2002

Forecasting trial outcomes: lawyers assign higher probability to possibilities that are described in greater detail.

The study of judgment under uncertainty has revealed that people judge the probability of an event to be higher when the event is described as a disjunction of constituent events or when they judge constituent events separately. These observations have motivated the development of support theory (Y. Rottenstreich & A. Tversky, 1997; A. Tversky & D. J. Koehler, 1994), a descriptive model of judgment under uncertainty. The major predictions of support theory are that (1) the judged probabilities of complementary events sum to 1; (2) the judged probabilities of n > 2 exclusive and exhaustive events generally sum to more than 1; and (3) the judged probability of an event generally increases when it is described as a disjunction of specific possibilities. We test these predictions in 6 studies of experienced attorneys who judged the likelihood of particular trial outcomes or were asked to offer advice on whether or not to accept a settlement offer. The results demonstrate that attorneys are indeed susceptible to bias in forecasting trial outcomes, consistent with support theory.

Forecasting↗

PubMed2000

Focalism: a source of durability bias in affective forecasting.

The durability bias, the tendency to overpredict the duration of affective reactions to future events, may be due in part to focalism, whereby people focus too much on the event in question and not enough on the consequences of other future events. If so, asking people to think about other future activities should reduce the durability bias. In Studies 1-3, college football fans were less likely to overpredict how long the outcome of a football game would influence their happiness if they first thought about how much time they would spend on other future activities. Studies 4 and 5 ruled out alternative explanations and found evidence for a distraction interpretation, that people who think about future events moderate their forecasts because they believe that these events will reduce thinking about the focal event. The authors discuss the implications of focalism for other literatures, such as the planning fallacy.

Affect↗

PubMedDate not supplied

Using stated preference modeling to forecast the effect of medication attributes on prescriptions of alcoholism medications.

OBJECTIVE: The objective of this study was to forecast physicians' preferred rate of prescriptions of alcoholism medications given different medications attributes (i.e., efficacy, side effects, compliance, price, mode of administration, method of action). METHODS: Stated preference modeling was used. Data came from a survey of 1388 physicians specializing in addiction medication (65% response rate). Physicians were given four hypothetical scenarios, each in which they were asked to choose between prescribing one of two hypothetical alcoholism medications with given attributes or prescribing no medication. RESULTS: Prescribing decisions were elastic with respect to the efficacy of the medication (1.35 and 1.65 using two efficacy measures). A 10% increase in the percentage of patients who would remain abstinent on the medication would lead to a 13.5% increase in the percentage of patients prescribed the medication. Prescribing decisions were inelastic with respect of nonserious side effects (-0.24), compliance (0.80), and price (-0.25). The market share of alcoholism medications with extremely favorable characteristics (i.e., 80% abstinence rate, a 95% no heavy drinking rate, a 10% side effect rate, a 80% compliance rate, and a price of US dollars 0.25) was predicted to be 53%, and 47% of the population would not be prescribed a medication to prevent alcoholism. CONCLUSIONS: The market share of new medications to treat alcoholism among addiction specialists could surpass the low usage rates of existing medications if those medications have better attributes. However, prescription levels may not reach that expected for treatment of other diseases.

Alcohol Deterrents↗

PubMed2002

Waiting time information services: how well do different statistics forecast a patient's wait?

This study investigates how accurately the waiting times of patients about to join a waiting list are predicted by the types of statistics disseminated via web-based waiting time information services. Data were collected at a public hospital in Sydney, Australia, on elective surgery activity and waiting list behaviour from July 1995 to June 1998. The data covered 46 surgeons in 10 surgical specialties. The accuracy of the tested statistics varied greatly, being affected more by the characteristics and behaviour of a surgeon's waiting list than by how the statistics were derived. For those surgeons whose waiting times were often over six months, commonly used statistics can be very poor at forecasting patient waiting times.

Data Collection↗

PubMed2002

Self-organization in leaky threshold systems: the influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting.

Threshold systems are known to be some of the most important nonlinear self-organizing systems in nature, including networks of earthquake faults, neural networks, superconductors and semiconductors, and the World Wide Web, as well as political, social, and ecological systems. All of these systems have dynamics that are strongly correlated in space and time, and all typically display a multiplicity of spatial and temporal scales. Here we discuss the physics of self-organization in earthquake threshold systems at two distinct scales: (i) The "microscopic" laboratory scale, in which consideration of results from simulations leads to dynamical equations that can be used to derive the results obtained from sliding friction experiments, and (ii) the "macroscopic" earthquake fault-system scale, in which the physics of strongly correlated earthquake fault systems can be understood by using time-dependent state vectors defined in a Hilbert space of eigenstates, similar in many respects to the mathematics of quantum mechanics. In all of these systems, long-range interactions induce the existence of locally ergodic dynamics. The existence of dissipative effects leads to the appearance of a "leaky threshold" dynamics, equivalent to a new scaling field that controls the size of nucleation events relative to the size of background fluctuations. At the macroscopic earthquake fault-system scale, these ideas show considerable promise as a means of forecasting future earthquake activity.

Animals↗

PubMed2004

Forecast and control of epidemics in a globalized world.

The rapid worldwide spread of severe acute respiratory syndrome demonstrated the potential threat an infectious disease poses in a closely interconnected and interdependent world. Here we introduce a probabilistic model that describes the worldwide spread of infectious diseases and demonstrate that a forecast of the geographical spread of epidemics is indeed possible. This model combines a stochastic local infection dynamics among individuals with stochastic transport in a worldwide network, taking into account national and international civil aviation traffic. Our simulations of the severe acute respiratory syndrome outbreak are in surprisingly good agreement with published case reports. We show that the high degree of predictability is caused by the strong heterogeneity of the network. Our model can be used to predict the worldwide spread of future infectious diseases and to identify endangered regions in advance. The performance of different control strategies is analyzed, and our simulations show that a quick and focused reaction is essential to inhibiting the global spread of epidemics.

Aerospace Medicine↗

PubMed2004

Cross-scale interactions, nonlinearities, and forecasting catastrophic events.

Catastrophic events share characteristic nonlinear behaviors that are often generated by cross-scale interactions and feedbacks among system elements. These events result in surprises that cannot easily be predicted based on information obtained at a single scale. Progress on catastrophic events has focused on one of the following two areas: nonlinear dynamics through time without an explicit consideration of spatial connectivity [Holling, C. S. (1992) Ecol. Monogr. 62, 447-502] or spatial connectivity and the spread of contagious processes without a consideration of cross-scale interactions and feedbacks [Zeng, N., Neeling, J. D., Lau, L. M. & Tucker, C. J. (1999) Science 286, 1537-1540]. These approaches rarely have ventured beyond traditional disciplinary boundaries. We provide an interdisciplinary, conceptual, and general mathematical framework for understanding and forecasting nonlinear dynamics through time and across space. We illustrate the generality and usefulness of our approach by using new data and recasting published data from ecology (wildfires and desertification), epidemiology (infectious diseases), and engineering (structural failures). We show that decisions that minimize the likelihood of catastrophic events must be based on cross-scale interactions, and such decisions will often be counterintuitive. Given the continuing challenges associated with global change, approaches that cross disciplinary boundaries to include interactions and feedbacks at multiple scales are needed to increase our ability to predict catastrophic events and develop strategies for minimizing their occurrence and impacts. Our framework is an important step in developing predictive tools and designing experiments to examine cross-scale interactions.

Animals↗

PubMed2001

Scaling laws and forecasting in athletic world records.

In this study, we analysed running world records and found that the mean speed of the race, mu, as a function of the record time, tau, can be described asymptotically by two well-defined scaling laws of the form mu approximately tau(-beta). There is a break in the scaling laws (approximately 1000 m) between the shorter and the longer races at a characteristic time of around 150-170 s, after which a new scaling regime emerges. This is the first occasion that this characteristic time has been clearly found in physical terms; we interpreted it as the transition time between the anaerobic and the aerobic energy expenditure of athletes. This phenomenon is independent of the athletes' sex and is also found in swimming races with similar values of the characteristic time. We also investigated the forecasting of world records using historical data. Using an approach based on the identification of non-Poissonian events for a sequence of temporal point processes, we found that the sequence of improvements in all athletic records from 1900 to the present day cannot be considered as a sequence of completely random events.

Anaerobic Threshold↗