The overarching aim of the project will be to develop analytical approaches to more rapidly and accurately identify, monitor, and manage health risks in society, such as a pandemic disease. Through a collaboration with the SWECOV research program at Stockholm University, www.swecov.se, we can apply for access to an internationally unique data infrastructure comprising of individual-level syndromic surveillance data from the Swedish health advisory hotline linked with other register data covering the entire Swedish population. In addition, novel data sources on domestic and international mobility patterns can be exploited.

Your main tasks will be:

• Evaluate the utility of individual-level health hotline data linked with comprehensive register data infrastructure to forecast disease transmission trends and associated health care demands under different policy scenarios using mathematical modelling approaches.
• Modelling the likely introduction and future transmission of a pandemic disease using real-world domestic and cross-border mobility data based on mobile phone usage and credit card transactions using traditional epidemiological modelling techniques as well as by exploring data-driven methods.
• Engage in the dissemination and discussion of the research findings within our network (at Lund University, SWECOV, national epidemiological modelling network), public agencies (e.g., Swedish Public Health Agency) and within the wider scientific community (publications, conferences).