Surveillance and epidemiology of infectious diseases

• Design and evaluate, in a team, surveillance programmes for infectious diseases, including choice of methodologies and tools
• Assess sensitivity, specificity, and positive predictive values of diagnostic tests and surveillance programmes
• Apply mathematical models to predict the spread of (selected) infectious diseases in defined populations
• Perform trend analysis of infectious disease data
• Analyse and interpret data from existing national and international surveillance programmes of infectious diseases, antimicrobial usage and antimicrobial resistance
• Plan and perform, in a team, investigations og food and water associated disease outbreaks
• Apply genomic data (WGS) from pathogens to elucidate transmission pathways and trace the sources of infections
• Perform epidemiological studies to investigate global, regional, and local drivers as well as risk factors for infectious diseases
• Perform epidemiological studies to investigate the efficacy and safety of vaccines and treatments
• Estimate burden of disease measures for prioritization of interventions (DALY estimations)

History of infectious diseases; viral, bacterial and parasitic diseases; the threat from antimicrobial resistance; zoonoses and species jumps; design and evaluation of surveillance systems; design and interpretation of epidemiological studies; causality versus association; modelling the spread of infectious diseases using differential and stochastic models (e.g. SIR and agent-based models); understanding global, regional and local drivers of infectious diseases including impact of climate change and increasing urbanisation; One Health: understanding the interaction between animal, human and environmental health; methods for identifying drivers and risk factors of infectious diseases using regression and Bayesian modelling techniques; methods for investigating efficacy and safety of vaccines and treatments; ecological studies; using whole genome sequencing data (WGS) for prediction; big data and digital epidemiology.

23256/23205

Lectures, exercises, group work