Understanding the interplay between physiological, mental and socio-economic factors that have an impact on health is crucial to find effective responses to major public health challenges. At the IAS we aim to develop predictive models for various health related questions, examining all aspects from the molecular level all the way up to the healthcare system.
Health and illness have causes beyond biology and behaviour. However, a systemic and systematic approach is still largely missing. To predict or evaluate the effect of health intervention, many interrelated factors (and the multi-scale and dynamic interplay between them) should be taken into account: from an individual’s genes, biology and behaviour, to the social and physical environment and medical care.
Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity
- World Health Organization
This research programme adopts a system dynamics approach in order to develop data-driven, predictive models that can run what/if explorations for various health and wellbeing related questions, on individual and population level. We validate these models using real-time data from healthcare and population health studies. Our overall objective is to support the identification, implementation, and evaluation of effective responses to major public health challenges.
To increase our understanding of the causal relations between all determinants that have an impact on health, this work requires integration of knowledge, data, concepts and theories from many disciplines, ranging from biology and medical sciences to psychology, sociology and economics. Therefore, we use a complex systems approach as our common framework.
Professsor of Anthropology of Care and Health, University of Amsterdam
In my research work on global health issues, I combine social sciences and medicine. I am interested in a broad range of subjects, from reproductive health in women, HIV/AIDS, and the social impact of pharmaceuticals on vulnerable youths to the relationship between health and global sustainable development and the role of chemical substances in the lives of young people.
Will be studying synergistic interactions between stochastic and deterministic processes underlying the dynamics of infectious diseases close to the point of elimination.
Will be studying how complexity modelling tools can be used to understand the onset and maintenance of common mental health disorders (like depression) in order to explore new targets for prevention and treatment.
Will team up with other researchers to address several immunity-related questions, using an interdisciplinary approach combining in-vitro, in-vivo and in-silico experiments.
Will work on improving the performance of specific individual-based computation techniques (AMC-SMC) to be used to predict and optimise the impact of public health programmes against neglected tropical infectious diseases.
Will be studying how to assert control on psychological complexity (e.g., treatment), specifically by exploring the utility of information theory applied to network psychometrics.
Programme developer Health Systems Complexity, and post-doc researcher Computational Immunology.
To find out more about this research theme, or discuss getting involved, contact Anita Hardon.