Our research focuses on causes and consequences of diabetes and cardiovascular diseases, identification of predictive biomarkers and lifestyle factors, and novel methods in disease surveillance.
We apply traditional and modern methods for causal inference in large observational datasets, some of which our team have initiated and developed based on high-throughput molecular methods. These data include metabolomics, metagenomics, genomics, proteomics, and imiomics. We have also performed large register linkages, and collected COVID-19 data through an innovative national syndromic surveillance app, and through close collaboration with the county council and other institutions.
We are an international, creative, and collaborative research environment with ambition to work on impactful projects. Our research is projected to lead to important new insights of disease mechanisms, which in turn can facilitate development of new treatments of these diseases, as well as to new biomarkers of disease for improved risk prediction and prognostics. Additionally, in response to the COVID-19 pandemic, the group has been striving to develop novel methods for monitoring the transmission of infectious disease agents and for establishing a systematic approach to vaccination safety in order to safeguard communities from future crisis.
Research group news
Shafqat Ahmad is awarded a post-doc grant from EpiHealth.
A regression discontinuity analysis of the social distancing recommendations for older adults in Sweden during COVID-19.
An online atlas of human plasma metabolite signatures of gut microbiome composition
App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden
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