Forecasting environmental migration to the United Kingdom, 2010 - 2060: an exploration using Bayesian models

Over the next fifty years the potential impact on human livelihoods of environmental change could be considerable. One possible response may be increased levels of human mobility. This paper offers a first quantification of the levels of environmental migration to the United Kingdom that might be expected. The authors apply Bijak and Wi?niowski’s (2010) methodology for forecasting migration using Bayesian models. They seek to advance the conceptual understanding of forecasting in three ways. First, the paper is believed to be the first time that the Bayesian modelling approach has been attempted in relation to environmental mobility. Second, the paper examines the plausibility of Bayesian modelling of UK immigration by cross-checking expert responses to a Delphi survey with the expectations about environmental mobility evident in the recent research literature. Third, the values and assumptions of the expert evidence provided in the Delphi survey are interrogated to illustrate the limited set of conditions under which the forecasts of environmental mobility, as set out in this paper, are likely to hold

What do Bayesian methods offer population forecasters?

The Bayesian approach has a number of attractive properties for probabilistic forecasting. In this paper, we apply Bayesian time series models to obtain future population estimates with uncertainty for England and Wales. To account for heterogeneity found in the historical data, we add parameters to represent the stochastic volatility in the error terms. Uncertainty in model choice is incorporated through Bayesian model averaging techniques. The resulting predictive distributions from Bayesian forecasting models have two main advantages over those obtained using traditional stochastic models. Firstly, data and uncertainties in the parameters and model choice are explicitly included using probability distributions. As a result, more realistic probabilistic population forecasts can be obtained. Second, Bayesian models formally allow the incorporation of expert opinion, including uncertainty, into the forecast. Our results are discussed in relation to classical time series methods and existing cohort component projections. This paper demonstrates the flexibility of the Bayesian approach to simple population forecasting and provides insights into further developments of more complicated population models that include, for example, components of demographic change

Integrated Modelling of European Migration: Background, specification and results

The aims of this paper are to present the background and specification of the Integrated Modelling of European Migration (IMEM) model. Currently, international migration data are collected by individual countries with separate collection systems and designs. This creates problems when attempting to understand or predict population movements between countries as the reported data are inconsistent in terms of their availability, definitions and quality. Rather than wait for countries to harmonise their migration data collection and reporting systems, we propose a model to overcome the limitations of the various data sources. In particular, we propose a Bayesian model for harmonising and correcting the inadequacies in the available data and for estimating the completely missing flows. The focus is on estimating recent international migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA) from 2002 to 2008, using data collected by Eurostat and other national and international institutions. We also include additional information provided by experts on the effects of undercount, measurement and accuracy. The methodology is integrated and capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Rancang Bangun Aplikasi Mobile Perhitungan Indeks Massa Tubuh Dan Berat Badan Ideal

Technology is growing rapidly, provides an easy way to do various activities. An example is a mobile application for the calculation of body mass index and ideal weight. The first step of making the application is the system requirements analysis, system design, coding, and implementation into a computer program using J2ME programming language. Last step is testing the application using mobile devices, Nokia C2, Nokia 5233 and Nokia N78. By using this application, it will be easy to know the state of a person\u27s weight, while the BBI calculation can be used to find the ideal weigh

Augmenting migration statistics with expert knowledge

International migration statistics vary considerably from one country to another in terms of measurement, quality and coverage. Furthermore, immigration tend to be captured more accurately than emigration. In this paper, we first describe the need to augment reported flows of international migration with knowledge gained from experts on the measurement of migration statistics, obtained from a multi-stage Delphi survey. Second, we present our methodology for translating this information into prior distributions for input into the Integrated Modelling of European Migration (IMEM) model, which is designed to estimate migration flows amongst countries in the European Union (EU) and European Free Trade Association (EFTA), by using recent data collected by Eurostat and other national and international institutions. The IMEM model is capable of providing a synthetic data base with measures of uncertainty for international migration flows and other model parameters.

Estimation of usefulness of monitoring tissue polypeptide antigen - TPA-M concentrations in the effectiveness surgical treatment of urinary bladder cancer

BACKGROUND: Of all cancer tumours, urinary bladder cancer is the fourth must common in men and the seventh in women. The aim of this work was to answer the question whether tissue polypeptide antigen (TPA-M) determination in patients after electroresection of urinary bladder cancer can be used to establish the probability of tumour recurrence. MATERIAL AND METHODS: The research included 98 patients, all of whom had undertaken electroresection of urinary bladder tumour (TURT), which enabled its removal, and then estimation of malignancy and progression stage according to the international TNM scale. The mean age was 62.7 years. All patients had blood samples taken to determine TPA-M and then underwent routine cystoscopy examination. RESULTS: The patients with tumour recurrence (60, mean age 64 ± 10) had TPA 30.2 ± 4.3 U/l, the patients without recurrence (38, mean age 61.3 ± 11) had TPA-M 26.2 ± 3.18 U/l (p > 0.1). Taking the TPA-M threshold point 85 U/l as normal, true-positive results were 16.3%, true-negative were 31.6%, falsepositive results were 7.1% and false-negative were 44.9%. The ROC curves with the calculated area under them are the measurement of the diagnostic estimation of TPA-M concentrations in specificity and sensitivity categories. CONCLUSIONS: For the examined group the calculated P was 0.45. If P value is under 0.5 it is considered that the test should not be used in diagnosing recurrence of urinary bladder cancer

High-Migration Events and Future Labour Force in Europe. Brief No. 39.

Migration is complex, highly uncertain, and marked by unexpected changes. Political crises, economic downturns, and human-made or natural disasters can set large numbers of people on the move, just as we saw in 2015 – 2016 for migration from Syria and in 2022 from Ukraine. However, some political crises, such as the Taliban’s return to power in Afghanistan in 2021 did not bring unprecedentedly large numbers of refugees into Europe, despite concerns among policymakers at the beginning of the crisis. Migration events are impossible to predict in terms of their onset, scale, duration and in terms of how many people will return or settle in what destinations

New perspectives for migration foresight and preparedness: Insights from the QuantMig Project

This paper summarizes new perspectives for studying migration futures, drawing on the results of the European Union-funded project QuantMig: Quantifying Migration Scenarios for Better Policy. The paper presents advances in conceptualizing, explaining, estimating and forecasting international migration, considering various forms of uncertainty, and acknowledging the complexity of migration processes and the agency of various actors involved. The authors propose and evaluate a range of tools aimed at improving the estimates of current and predictions of future migration levels, and enhancing operational preparedness across various time horizons. A brief overview of these tools is provided, followed by a discussion of key implications and recommendations for migration and migration-related policies. The goal is to underscore the opportunities for making these policies more robust, future-proof and better aligned with the needs of both host societies and migrants themselves