The objective of the course is to improve the ability of students to think, conceive, design, conduct, analyze and interpret research in molecular epidemiology that is highly valid, and highly relevant – relevant either from a biological, from a clinical or from a public health perspective.

Miquel Porta is Head of Clinical & Molecular Epidemiology of Cancer Unit, Municipal Institute of Medical Research (IMIM).

Professor of Preventive Medicine & Public Health, School of Medicine, Universitat Autònoma de Barcelona (UAB).

Adjunct Professor, Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill (UNC).

After graduating from the UAB School of Medicine in 1981, he was during 3 years a Fellow with the Division of Clinical Pharmacology of UAB. He was then awarded a Fulbright scholarship to pursue the Master of Public Health (MPH) program at UNC, and was later a Burroughs Wellcome Postdoctoral Fellow in Pharmacoepidemiology at UNC.

Other than at the UAB School of Medicine, Dr. Porta has also taught on molecular epidemiology, clinical epidemiology and pharmacoepidemiology at other institutions, including McGill University (Montreal, Canada), the European Educational Programme in Epidemiology (Firenze, Italy), the Westfälische Wilhelms-Universität (Münster, Germany), several universities in Brazil and Mexico, and at Harvard, where he was on sabbatical in 1998-1999.

From 1994 to 1998 he was President of the Spanish Society of Epidemiology (SEE). From 2002 to 2005 he was European Councillor of the International Epidemiological Association (IEA) and Chairman of the IEA European Epidemiology Federation.

This course focuses on the concepts necessary to formulate projects in the health communication area. It aims also to provide understanding about the multiple actors involved in both the impact of new technologies in health information and the public participation in decision making processes for the development of new treatments.

Objectives:

Objectives:

This Course seeks to provide students with the main areas of analysis in contemporary empirical research that examines the social regulation of biotechnology.

Specific objectives:

To identify the key approaches and debates in the field of social studies of biotechnology and biomedicine;

To discuss the societal, economic and ethical repercussions of the politics of regulation;

To understand the heterogeneity of uses and social meanings associated with the applications of biotechnology;

To analyse the multiple inequalities in terms of power, property and citizens’ interactions with biotechnology;

To evaluate the main fields of knowledge in contemporary research around health and biotechnology, in particular: reprogenetics, genomics, and new life sciences.

Objectives:

The Course will occur in 2 days: 10th and 17th July 2010

 
 
Objectivos:
 
·         Formação dos profissionais de saúde preparando-os para um exercício
·         Tecnicamente diferenciado e de qualidade;
·         Desenvolvimento de rotinas de utilização dos principais grupos fármaco-
·         terapêuticos;
·         Promoção do uso racional de medicamentos;
·         Estabelecimento de princípios gerais de tratamento para as patologias
·         Mais prevalentes na comunidade;
·         Troca de experiências entre as realidades do ambulatório e hospitalar;
·         Promoção da multidisciplinaridade das equipas de profissionais de saúde;
·         Formação pós-graduada dos profissionais de saúde, valorizando a sua
·         Qualificação profissional e preparando-os para o exercício tecnicamente diferenciado da sua profissão.

The dates of the course will be 12th, 26th and 27th November

Tutors:

Carlos Daniel Paulino, Giovani Silva and Paulo Soares

Centro de Estatística e Aplicações da Universidade de Lisboa/ Instituto Superior Técnico (EAUL/IST - UTL)

Timetable

28th February and 1st March 2011: 9:00am to 00:30pm and 2:00pm to 5:30pm

2nd March 2011: 9:00 am to 1:00pm

Place:

Rua das Taipas, 135, 4050-600 Porto

Inscriptions:

Normal 300,00 euros; Student 200,00 euros

Maximum Number of Participants: 30

Contacts: (351) 222019325 - ispup.secretaria@gmail.com; www.ispup.up.pt

Target Public:

Statisticians and researchers from all areas, interest in understand Bayesian methods and how to apply them using free software. Students must have basic knowledge about statistical modeling.

Henrique Barros, Institute of Public Health, University of Porto

Ana Martins, Institute of Public Health, University of Porto

Christoph Lange, Clinical Infectious Disease, Research Centre Borstel, Germany

Jeffrey V. Lazarus, Global Fund to Fight AIDS, Tuberculosis and Malaria

Jessika Deblonde, International Centre for Reproductive Health, Ghent University

Joana Bettencourt, National Coordination for HIV/Aids Infection

Joana Soares Ferreira, National Coordination for HIV/Aids Infection

Lucas Wiessing, European Monitoring Centre for Drugs and Drug Addition

Miriam Sabin, UNAIDS

Natália Ribeiro, Infection Control Committee and of Infectious Diseases Department, Hospital São João

Raquel Duarte, University of Porto Medical School

Pauline EMMETT
Centre for Child and Adolescent Health – University of Bristol, UK

Marion M. HETHERINGTON
Institute of Psychological Sciences – University of Leeds, UK

Carla LOPES, Elisabete RAMOS, Ana Cristina SANTOS, Andreia OLIVEIRA
Department of Hygiene and Epidemiology - University of Porto Medical School,
Institute of Public Health - University of Porto

Objective:
To know and better understand the concepts and methods related with the evaluation of nutritional determinants in health, emphasizing longitudinal approaches in childhood. To discuss early nutritional determinants of obesity and preventive strategies.

Objectives

To understand the importance of the geographical space and new technologies of geographic information in the analysis of health data.

To understand the basic concepts of cartography, georeferencing and spatial analysis of health data.

To learn the use of Geographic Information Systems (GIS) and Global Positioning Systems (GPS) in the analysis of health and environmental data

Professor:

Carmen María Cadarso-Suárez

Unit of Biostatistics-School of Medicine.

University of Santiago de Compostela.

Programme:

0.     Introduction to R.

1. Generalized Linear Models - GLMs

1.1. Some theory about the GLM.

1.2. Estimation and inference.

1.3. GLMs with R. Practical examples.

2. Introduction to flexible regression methods

2.1. Polynomial regression. Piecewise polynomial regression.

2.2. Regression splines: B-splines (bs), natural splines (ns).

2.3. Penalized regression splines.

2.4. Smoothing regression techniques.

2.4.1. Univariate smooth functions (Smoothers).

2.4.2. Smoothing bases: P-splines (ps),  thin plate regression splines (tp),..

2.4.3. Effective number of “degrees-of-freedom” of an smoother.

2.5. Exercises with R.

3. Generalized Additive Models– GAMs

3.1. Some theory about the GAM.

3.1.1. Estimation and inference.

3.1.2. Multivariate selection of smoothing parameters.

3.2. GAM including interactions. Tensor product bases (te).

3.3. GAMs with R.

3.3.1. The mgcv package.

3.3.2. GAMs in practice: Real data examples.

References:

Hastie T.J. and Tibshirani T.J. (1990). Generalized Additive Models. Chapman & Hall.

McCullagh P. and Nelder J.A. (1989). Generalized Linear Models. Second Edition. Chapman &Hall/CRC.

Wood S. (2006). Generalized Additive Models. An introduction with R. Chapman & Hall/CRC.

Detailed Programme

This course is designed to provide an introduction to Bayesian approaches to statistical modelling and associated methods (such as Markov Chain Monte Carlo (MCMC) techniques and variants of that. The focus will be very much on practical implementation of the methods using the statistical programming language R and related packages (including links between R and OpenBUGS).

The course is arranged into sessions:

·         Introduction to Bayesian Modelling and MCMC

Review of the Bayesian Approach, MCMC and Hastings-Metropolis algorithm, model checking and inferential ideas.

·         Common Applications of Bayesian Modelling

Examples of implementing a range of standard models using R and links between R and OpenBUGS, including Linear and Generalised Linear Mixed models, survival models, temporal and spatio-temporal models, Generalised Additive models.

·         Practical Workshop

An opportunity for groups of participants to work through modelling examples and associated computer implementation for themselves

·         Extensions and more Advanced Ideas

A brief discussion of more advanced  techniques, including Reversible Jump (RJMCMC), and Approximate Bayesian Computation (ABC)

Enquadramento e objectivos:

Um sistema apoio à decisão é um sistema computacional interativo cujo objetivo é ajudar os decisores – profissionais de saúde – a utilizar os dados e modelos de forma a identificar e a resolver problemas com vista à tomada de decisões em saúde.

Para tal são necessárias competências nas áreas de extração de conhecimentos – data mining – usando modelos que procuram automaticamente regularidades e padrões. Esses padrões e regularidades podem ser generalizados de forma a serem úteis em decisões futuras.

São objetivos do curso que os participantes adquiram conhecimentos na utilização de uma aplicação computacional na análise estatística de dados em ambiente R e na construção de um sistema de apoio à decisão em saúde.

Destinatários:

Investigadores e estudantes universitários pré- e pós- graduados com conhecimentos de estatística descritiva e inferência básica e que pretendam aperfeiçoar as suas competências na modelação de dados supervisionados e não supervisionados utilizando as capacidades da ferramenta de acesso livre R.

Tem um limite de 15 participantes e a seleção será efetuada com base na avaliação do curriculum vitae.

Informação Geral

Responsável pelo curso: Doutor Milton Severo (Faculdade de Medicina da Universidade do Porto; Instituto de Saúde Pública da Universidade do Porto) é licenciado em Matemática pela Universidade de Aveiro, Mestre em Análise de Dados e Sistemas de Apoio à Decisão pela Faculdade de Economia de Universidade do Porto e Doutorado em Saúde Pública pela Faculdade de Medicina da Universidade do Porto. O seu trabalho tem abordado essencialmente a modelação de problemas na área da epidemiologia, saúde pública, nutrição e educação médica. Possui mais de uma centena de trabalhos publicados a nível internacional e nacional.

Valor de Inscrição: €120 (40% de desconto para estudantes da Universidade do Porto)

Local: Instituto de Saúde Pública da Universidade do Porto - Rua das Taipas, nº 135, Porto

Duração e Horário: segundas, quartas e sextas, das 14h00 às 18h00.

Contactos:

Institute of Public Health, University of Porto

Rua das Taipas, nº 135, Porto (Portugal)

 Tlf. + 351 222 061 820 (Ext. 105)

Fax + 351 222 061 821

O curso dirige-se a profissionais de saúde que trabalham com doentes com tuberculose.

Tem um limite de 70 participantes e a seleção será efetuada com base na avaliação do curriculum vitae. 

· Identify and evaluate the fundamentals, limits and strengths of qualitative methodology in health-related contexts.

· Analyze the suitability of various strategies for qualitative research in healthcare.

·  Understand the ethical dimensions involved in the use of qualitative methodology.

· Design a research proposal based on qualitative methods to obtain external funding.

· Be aware of the guidelines for publishing qualitative studies.

· Identify software to support the analysis of qualitative data in health.

O curso dirige-se a profissionais de saúde que trabalham com doentes com tuberculose.

Tem um limite de 70 participantes e a seleção será efetuada com base na avaliação do curriculum vitae.

Responsável pelo curso: Doutora Raquel Duarte (Centro Hospitalar de Vila Nova de Gaia/Espinho; Centro Diagnóstico Pneumológico; Faculdade de Medicina da Universidade do Porto; Centro de Referência para a TBMR da Região Norte; Instituto de Saúde Pública da Universidade do Porto)

Valor de Inscrição:  €30

9:00 Epidemiologia da tuberculose

9:30 Diagnóstico e tratamento

10:30 Abordagem dos efeitos adversos aos fármacos

11:00 - 11:15 intervalo para café

11:15 Rastreios - quem e como rastrear?

12:15 Discussão de casos práticos