Epidemiology course

Course duration: 8 double lessons

Anyone who plans, organizes, or analyzes epidemiological studies must also make use of quantitative statistical methods. But even those who want or need to understand and evaluate such studies firsthand cannot do so without statistical knowledge. Many public controversies surrounding epidemiological studies result from either the use of inadequate statistical methods or the misinterpretation of statistical findings.

The goal of this course is therefore to teach the methodological knowledge necessary for epidemiological studies from the basics and to illustrate it with examples.
 

Speakers

Prof. Dr. Wolfgang Ahrens: Professor of Epidemiological Methods in the Department of Mathematics and Computer Science at the University of Bremen (since 2003)

Prof. Dr. Lothar Kreienbrock: Former Director of the Institute for Biometry, Epidemiology, and Information Processing at the University of Veterinary Medicine Hannover

PD Dr. Jürgen Wellmann: Research Assistant at the Institute for Epidemiology and Social Medicine, University Hospital Münster

Topic Overview

Part I

• Measures of Disease Frequency (Prevalence, Cumulative Incidence, Risk Years, Incidence Density)
• Standardization of mortality rates
• Fundamentals of probability theory and statistics
• Measures of association between diseases and risk factors (relative risk, odds ratio, attributable risks)
• Types of epidemiological studies (cohort, case-control, and cross-sectional studies)
   

Course duration: 8 double lessons

Anyone who plans, organizes, or analyzes epidemiological studies must also make use of quantitative statistical methods. But even those who want or need to understand and evaluate such studies firsthand cannot do so without statistical knowledge. Many public controversies surrounding epidemiological studies result from either the use of inadequate statistical methods or the misinterpretation of statistical findings.

The goal of this course is therefore to teach the methodological knowledge necessary for epidemiological studies from the basics and to illustrate it using examples.

Speakers

PD Dr. Amely Campe: Research Associate at the Institute for Biometry, Epidemiology and Information Processing at the University of Veterinary Medicine Hannover

Prof. Dr. Lothar Kreienbrock: Former Director of the Institute for Biometry, Epidemiology and Information Processing at the University of Veterinary Medicine Hannover

Dr. Hermann Pohlabeln: Research Associate in the Department of Biometrics and Computer Science at the Leibniz Institute for Prevention Research and Epidemiology – BIPS GmbH, Bremen

PD Dr. Jürgen Wellmann: Research Assistant at the Institute of Epidemiology and Social Medicine, University Hospital Münster

Topic Overview

Part II

• Simple epidemiological analysis methods
• Case number calculations for epidemiological studies
• Bias in epidemiological studies (selection, misclassification and confounding)
• Stratified analysis methods
• Risk modeling using logistic regression

Course duration: 8 double lessons

Risk assessments are used, among other things, to estimate the potential harm associated with the importation of live animals or animal products, to evaluate possible protective measures in a comparative manner, and thereby to provide management with an objective basis for decision-making. In the field of food hygiene, similar principles are used to assess health risks to consumers. Animal welfare aspects can also be examined using risk assessment methodology.

In addition to risk assessment, risk analysis also encompasses the communication and management of risks. Risk assessment provides an objective basis for decision-making in risk management. Risk assessment considers both the probability of harm occurring and the severity of the consequences. As part of risk analysis, it is often possible to identify ways to mitigate or avoid risks and to compare various risk reduction strategies.

In particular, the fields of microbiology, toxicology, food hygiene, veterinary epidemiology, and epidemiology contribute to science-based health risk assessments by providing data, information, and expert knowledge. Depending on the nature of the issue, the results of risk assessments are implemented by national or supranational authorities, as well as by producers (risk management). The entire risk analysis process—from planning to the implementation of the results—should be conducted through dialogue among all stakeholders, particularly with the involvement of consumer and producer associations.

The course is aimed in particular at anyone who, either currently or potentially, contributes to risk analyses in the areas of food safety, animal health, or animal welfare as part of interdisciplinary collaboration. Furthermore, the course is also intended for individuals with a professional interest in the results of risk analyses and those with a general interest in risk analysis.

Speakers

PD Dr. Amely Campe: Research Associate at the Institute for Biometry, Epidemiology and Information Processing at the University of Veterinary Medicine Hannover

Prof. Dr. Matthias Greiner: Head of Department at the Federal Institute for Risk Assessment (BfR), Berlin, and Professor at the University of Veterinary Medicine Hannover (TiHo)

PD Dr. Christine Müller-Graf: Head of the Epidemiology, Biometrics, and Mathematical Modeling Section at the Federal Institute for Risk Assessment (BfR), Berlin

Course Modules

Terminology of risk analysis (standards according to the OIE, Codex Alimentarius)

Basic concepts of risk modeling (deterministic, stochastic models, simulation)

Modeling tools

Qualitative risk assessment and quantitative risk assessments with application examples

Course duration: 8 double lessons

Disease events in individual hosts, herds, and entire host populations are now increasingly understood as changing dynamic systems and managed accordingly. The resulting abundance of decision-relevant mechanisms and processes quickly complicates the consistent interpretation of observations or the comprehensive testing of causal hypotheses. Evidence-based decisions, e.g., in the control context, appear difficult. Increasingly, dynamic epidemiological models are being developed to represent the complex interplay of mechanisms and processes involved in the spread of disease in host populations. Such models can be used to recreate possible consequences of decisions and to weigh alternatives. For example, what impact would a change in a biological assumption have on the expected success of a control measure? This immediate function of models as a deduction and decision support tool is the focus of the course.

During the seminar, background knowledge and practical experience in the development and use of models will be provided. It will be demonstrated that it can be useful to use models, regardless of the mathematical background of the person seeking an answer. In addition, it will be shown how very sophisticated models can be created through many years of experience and thanks to modern information technology.

Models are jointly developed that reproduce the transmission dynamics of diseases in the computer, and their statements are interpreted. No previous knowledge is required. Guided experimentation and freedom for own creative ideas are taken into account in the conception as well as the exchange among each other. The background knowledge to be imparted will be illustrated by examples from the 20 years of modeling activity of the lecturers in the environment of science and politics of animal welfare.

The course is aimed at non-modelers who deal with diseases in populations in the course of their work and who (might) be confronted with the statements of epidemiological models. The seminar is equally suitable for scientists and practitioners in health and animal health agencies and research institutions, as well as for students of human and veterinary medicine and natural sciences.

Speakers

Hans-Hermann Thulke & Martin Lange: Scientists at the Department of Ecological Systems Analysis of the Helmholtz Centre for Environmental Research (UFZ) in Leipzig. The Leipzig Project Group Ecological Epidemiology (EcoEpi - www.ecoepi.eu) has a proven track record in providing model-based advice to national and international decision-making bodies on various problems in animal health policy, disease management and epidemiology.

Course Units

The course is conducted over four half-day sessions of two double hours each. The parts cannot be taken individually. The course includes illustrative lectures and practical exercises. Exercises are done on provided computers or, optionally, on the student's own laptop (program installation required).

Content

•  Classical approach to disease description
• Early models of infectious diseases in host groups
• Guided NetLogo-based experimentation with different model concepts
• The step from the deterministic compartmental view to the reflection of biological diversity of host-pathogen interactions
• Guided NetLogo-based development of an individual-based infection spread model
• Guided independent model application to reproduce model-based answers to selected problems in animal disease control
• Example-oriented outlook on modern applied disease modeling to solve real-world decision problems
• Translating model-based insights into recommendations for action on an actual disease situation

Course duration: 8 double lessons

Course content and learning objectives

Animal experiments play an essential role in the process of scientific discovery in biology and (veterinary) medicine. The requirements for an experimental project are laid down in the Animal Welfare Act (TierSchG) and explained in more detail in the general administrative regulations for the implementation of the Animal Welfare Act (AVV), which are intended to ensure uniform application of the law throughout Germany. The current version of the written application for animal experiments requiring approval includes, among other things, information on the planned number of animals, including biometric planning (biometric section).

The course covers these biometric aspects and explains them using practical examples of specific animal experiment plans. This should enable participants to perform simple calculations independently and prepare the groundwork for planning more complex issues.

Speakers

Prof. Dr. Frank Konietschke, Charité – Universitätsmedizin Berlin: Head of the Working Group on Statistical Methods for Translational and Early-Phase Clinical Trials at the Institute of Biometry and Clinical Epidemiology

Prof. Dr. Lothar Kreienbrock, University of Veterinary Medicine Hannover: Former director of the Institute for Biometry, Epidemiology, and Information Processing and the WHO Collaborating Center for Research and Training for Health at the Human-Animal-Environment Interface

Course units

The course is held over four half-days, each consisting of two double periods. The sections cannot be taken individually. The course includes illustrative lectures, practical exercises, and discussion forums and is conducted in person (if there is very high interest, online participation may be made available). The exercises are completed on the participants’ own laptops. This requires the installation of certain software, which must be done independently before the course begins.

Course content

• Introduction
  o    General concept for determining sample size in animal experiments 
  o    Legal framework
  o    Issues surrounding exploratory and confirmatory animal experiments

   

• Statistical aspects of animal experiments
  o    What are alpha, beta, sigma, delta, and (Cohen's) effect sizes?
  o    Standard deviation as an essential measure for planning

   

• Parallel-group trials (two or more groups) for testing scientific hypotheses
  o    Sample size calculation for basic statistical tests (t-test, chi-square test, Fisher’s exact test, nonparametric test procedures)
  o    Sample size calculation for one-way analysis of variance and dose-response studies
  o    Sample size calculation for multifactor analysis of variance
  o    Sample size calculation for multiple testing procedures
  o    Sample size calculation to demonstrate equivalence between groups
  o    Fundamentals of adaptive animal experiments

• Notes on the use of software
• Supplementary literature
• General discussion