Connection project: Control of Infectious Diseases: modelling decisions and behaviour in Social Networks

Risk perception and health related decisions, connections in social networks, and how they are influencing epidemic dynamics are very relevant for the effectiveness of non-pharmaceutical interventions during a pandemic, but there are not yet good modelling tools to include these aspects into infectious disease transmission models. For policy makers in a future pandemic, it is important to assess not only the epidemiological impact of non-pharmaceutical interventions such as physical distancing measures, but also how adherence to measures is influenced by risk perception and social networks. Policy makers would like to make informed decisions that balance epidemiological impact of interventions and possibly negative effects on behaviour and social networks. Knowledge is lacking on how to integrate information on individual decisions regarding health protective behaviours, and how they are influenced in social networks, in transmission models for infectious diseases. The projects objectives are:

1. To systematically review the literature and extract information on choice based studies regarding health related behaviour in infectious disease context, in particular in outbreak situations; extract information on how individual preferences for decision making are influenced by social networks.
2. To quantify measures as degree distribution and clustering in social networks and assess diversity of social contacts in real social networks from literature and by analysing existing cohort data sets.
3. To develop novel modelling tools based on individual preferences for health related behaviour and utility functions with the aim of including decision making and social network influence in infectious disease transmission models.
4. To formulate guidance for modellers on how to include the above aspects of behaviour and social networks into various types of infectious disease models.
5. To perform a case study including specific scenarios that will be shared with modellers and stakeholders to develop guidance for the practical application of our modelling tools

Our approach is to extract information and data from existing literature regarding choice based studies (e.g. discrete choice experiments) in infectious diseases. We search in particular for results regarding the influence of social networks on these decisions, if available in the literature. Similarly, for quantification of measures for social networks and their diversity we review published literature, and existing observational data sets. We develop mathematical tools based on the concepts preferences and utility functions from health economics as elements that can be integrated into infectious disease models. We test the approach in a case study using different types of models (compartmental model and individual based model). We then formulate a general framework on how to integrate and use these utility functions in any infectious disease model. We organize a symposium for modellers and stakeholders, in which we present and discuss the suggested approach and results from scenarios.

The study population is the general population of community-dwelling adults. We will focus mainly on non-pharmaceutical interventions, but will also consider vaccination in a pandemic situation. The results will be modelling tools for including risk perception, health related behaviour, and social networks in infectious disease models for epidemic/pandemic preparedness. We aim for impact, that is improvement of ability to assess the (social) costs and benefits of non-pharmaceutical interventions during a pandemic, by delivering novel modelling tools that can be integrated into various types of infectious disease models.

Researchers on the project Senne Wijnen (PhD candidate), Florian van Daalen and Lisanne Steijvers (postdocs), Nicole Dukers and Rik Crutzen ([associate] profs) from Health promotion, Maastricht University.

Other team members: Nannan Li and Mickaël Hiligsmann (Health Services Research, Maastricht University), Baharak Rambod, Lilian Kojan and Leonard Stellbrink (Institute of Multimedia and Interactive Systems, University of Lübeck, Germany), Joshua M Chevalier (Department of Epidemiology & Health Economics, University Medical Center Utrecht, Utrecht University), Beate Jahn and Uwe Siebert (UMIT TIROL-University for Health Sciences and Health Technology, Hall in Tirol, Austria), Mirjam Kretzschmar (Department of Epidemiology and Health Economics, University Medical Center Utrecht, Utrecht University, Utrecht).

Funded by ZonMW

Started 2024 (ongoing)