The workshops will be held on 2 May 2022 at either the Technical University of Copenhagen (DTU) or the University of Copenhagen (KU).

KU is located centrally in Copenhagen. DTU is located 15 km north of Copenhagen. By public transport, the travelling time is about 30-40 minutes from the city center, from the airport about 1 hour - https://www.dtu.dk/english/about/campuses/dtu-lyngby-campus/getting-there

Please register for the workshop you wish to attend when you register for the conference.

ICAHS4 pre-conference workshop held at Technical University of Denmark (DTU), 2 May 2022

Time: 9.00-16.30 (please arrive at 8.30 to register)
Place: Technical University of Denmark (DTU) - Building 202,(entrance from Henrik Dams Alle), 2800 Kgs. Lyngby, Denmark. The room is LY202-R8003.

Workshop leader: Lucie Collineau (ANSES)
Other teachers: Cécile Aenishaenslin (University of Montreal), Lis Alban (Danish Agriculture & Food Council), Marion Bordier (CIRAD), Sarah Mediouni (University of Montreal), Koen Mintiens (FAO), Madelaine Norström (Norwegian Veterinary Institute), Marianne Sandberg (DTU), Carola Sauter-Louis (FLI), Laura Tomassone (University of Torino) + a MPH student (University of Guelph) to help 

Topics to be covered:
The CoEval-AMR (Convergence of Evaluation Frameworks for Integrated Surveillance of AMR-Antimicrobial Resistance and AMU-Antimicrobial Use) network was created to guide design and evaluation of integrated AMR and AMU surveillance systems. The network was established with the support of JPIAMR funding in 2019 (Phase 1) to harmonize and refine existing methods and tools for assessing AMR and AMU surveillance from a One Health, integrated and systems perspective. Since its inception, the CoEval-AMR network has evaluated and compared 12 different assessment tools in terms of applicability to AMU and AMR with a focus on One Health aspects. The network was renewed in 2021 for Phase 2 to 1) improve tools for evaluation of the impact and socioeconomic value of integrated surveillance systems and the governance of these complex collaborative monitoring systems, 2) engage more social scientists in design and evaluation of integrated AMR and AMU surveillance systems, and 3) to assess new assessment tools by applying them to different case studies. More information about CoEval-AMR is on our network website: coevalamr.fp7-risksur.eu.  

In this workshop, instructors will: 
1) provide a summary of Phase 1 findings and an overview of Phase 2 plans and activities, 
2) present the decision tool developed in Phase 1, summarize the available evaluation tools and review several case studies,
3) lead participants through individual and group activities to formulate an evaluation question, an evaluation plan, and identify an appropriate evaluation tool,
4) facilitate a discussion of challenges and gaps in surveillance system evaluation.

Required prior knowledge:
The workshop is intended for anyone who works in surveillance, is responsible for evaluation of their programs and/or is interested in learning more about the added value of integrated surveillance and how to measure it. The material is particularly relevant to those working in AMR and AMU surveillance in public or animal health with an interest in evaluation.  
Workshop format / Way of teaching: plenary session, individual and group activities and discussions

Own lab top required? Yes (preferred) 

Minimum number of participants required before workshop will be held: 10

ICAHS4 pre-conference workshop held at University of Copenhagen (KU), 2 May 2022

Time: 13:30-17:30 
Place: KU Frederiksberg Campus, building 1-09, Ridebanevej 6, 1. Floor, 1790 Frederiksberg.

Workshop leader: Clazien de Vos (WBVR, NL)
Other teachers: Emma Snary (APHA, UK), Cecilia Hultén (SVA, SE), Helen Roberts (Defra, UK), Rachel Taylor (APHA, UK)

Topics to be covered: This workshop will introduce the participants to the current state of the art of generic risk assessment in the veterinary field. Topics that will be addressed include different modelling approaches ranging from qualitative to quantitative, data needs for generic risk assessment, communication of results of generic risk assessments, and the contribution of generic risk assessment tools to the design of risk-based surveillance. 

Required prior knowledge: None

Workshop format / Way of teaching:
The workshop will start with an introductory lecture on generic risk assessment in which an overview of available tools is provided and data needs of generic risk assessment tools are addressed. Then, participants will be introduced to a quantitative, a semi-quantitative and a qualitative tool that were all developed in recent years. Demonstration of the tools will vary from interactive lectures to group exercises in which participants will get the opportunity to explore the tools themselves. The workshop will be concluded with a comparison over the tools considering issues like ease of use, data needs and communication of results.
 
Own laptop required? Yes

Minimum number of participants required before workshop will be held: Minimum=10; Maximum=30

ICAHS4 pre-conference workshop held at University of Copenhagen (KU), 2 May 2022

Time: 13.00-17.00
Place: KU Frederiksberg Campus, building 1-03, Grønnegårdsvej 8, 1790 Frederiksberg.

Workshop leader: Dr Stefan Widgren, National Veterinary Institute, Sweden (https://orcid.org/0000-0001-5745-2284)
Other teachers: Dr Thomas Rosendal, National Veterinary Institute, Sweden (https://orcid.org/0000-0002-6576-9668)

Topics to be covered:
Mathematical models and computer simulations can be used to study the performance of disease monitoring and surveillance strategies. In this workshop, we will use the R package SimInf (https://CRAN.R-project.org/package=SimInf) and present how to specify a disease spread model and integrate surveillance within the model. The framework can incorporate both within-herd infection dynamics and between-herd transmission from, for example, animal movements or spatial disease transmission. This allows us to efficiently evaluate surveillance in the presence of a complex population structure and disease spread and contrast different design choices. The participants will learn how to use the model specification language in SimInf to define and simulate infectious disease spread models. Additionally, we will introduce some more advanced programming in R to achieve this combination of disease spread and surveillance.

The workshop will consist of the following parts:
1.    Specification of a within- and between-herd transmission model. The participants will be introduced to the model syntax and explore the possible outputs from the model and how to interpret them.
2.    Incorporation of animal- and herd-level testing. This will allow participants to explore and compare various surveillance strategies.
3.    Introduction to debugging techniques. Inevitable, coding mistakes are made that need to be tracked down – we will demonstrate tools to debug a model.

Required prior knowledge:
This is not an introductory course in disease spread modelling, but an advanced introduction to modelling disease surveillance. Therefore, we expect the participants to have a prior experience in disease spread modelling. A basic knowledge of R is assumed and a desire to understand how R can interface compiled languages to enhance performance. We will provide a reading list for those that would like to participate in the workshop but have not previously worked with disease spread modelling.
Workshop format / Way of teaching: The participants will be assigned a reading list prior to the workshop in order to focus on applications of the methods during the workshop. During the workshop, we will complete hands-on exercises and coding in groups to solve problems that are related to surveillance evaluation in veterinary epidemiology.

Own laptop required? The participants are expected to bring a laptop with a recent version of the R-statistical software installed. Prior to the workshop, we will send instructions to the participants.

Minimum number of participants required before workshop will be held: 8.

ICAHS4 pre-conference workshop held at Technical University of Denmark (DTU), 2 May 2022

Time: 10.00-16.00
Place: Technical University of Denmark (DTU) Technical University of Denmark (DTU) - Building 202,(entrance from Henrik Dams Alle), 2800 Kgs. Lyngby, Denmark.. The room is LY202-R1019.

Workshop leader: Pablo Gomez-Vazquez 
Other teachers: Dr. Jerome Baron (co-instructor) and Shadira Gordon (TA)

Topics to be covered:
Network analysis, GIS, dynamic data visualization (https://cadms-ucd.github.io/spatialnetworks_ws/)
Most of infectious diseases are transmitted via direct contacts, therefore, animal trade and other contacts between animals play an essential role in the disease spread.
Social network analysis (SNA) is a powerful tool to explore the interactions between agents in a contact network and obtain additional information regarding the structure and dynamic of a community. The agents or nodes could be defined as the farms that belong to a trade network, wildlife animals tracked by GPS collars, or animals observed in a group. Using SNA methodologies we can identify individuals that could have a bigger role in disease spread when a disease is introduced into the community.

In this workshop we will use data regarding the movement of production animals in a contact network to demonstrate the applications of spatio-temporal network analysis. These methodologies can be applied to other settings such as wildlife monitoring, or to explore hierarchical relationships between animal groups, among others. The first part of the workshop will focus on the description of static networks and the second part will be using dynamic network analysis, which includes temporal dynamics of the movements. Both parts will also include the spatial component.
This workshop is aimed for students, researchers and other people interested in disease transmission and population dynamics.

Objectives 
•    Analyze and describe static and dynamic networks.
•    Advantages and disadvantages of static and dynamic networks and when we can use them.
•    How to incorporate the spatial relationships in the analysis of networks.
•    Visualize and present networks using spatial and non spatial approaches.
•    How to incorporate the transmission and potential spread of diseases in a network.
•    How to incorporate the results from network analysis with other statistical methods.

Required prior knowledge:  Basic knowledge of R language is encouraged, but not required, introduction to R programing is provided as pre-workshop materials

Workshop format / Way of teaching: Lectures/labs

Own lab top required? Yes

Minimum number of participants required before workshop will be held: 6