Report

Teaser, summary, work performed and final results

Periodic Reporting for period 2 - TransMID (Translational and Transdisciplinary research in Modeling Infectious Diseases)

Teaser

TransMID focuses on the development of novel methods to estimate key epidemiological parameters from both serological and social contact data, with the aim to significantly expand the range of public health questions that can be adequately addressed using such data. The...

Summary

TransMID focuses on the development of novel methods to estimate key epidemiological parameters from both serological and social contact data, with the aim to significantly expand the range of public health questions that can be adequately addressed using such data. The overall goal is to advance public health and epidemiology by:
- Developing innovative methodology in mathematical epidemiology (Modelling Infectious Diseases).
- (In)validating epidemiological hypotheses based on existing and new data collections.
- Conducting basic and general research applicable to many different pathogens (Translational).
- Applying the proposed methodology to better understand and predict the dynamics of important
pathogens such as cytomegalovirus, hepatitis A, pertussis, measles-mumps-rubella, …
- Using both biomedical knowledge and mathematical tools (Transdisciplinary).
To maximize TransMID’s impact on public health in Europe and beyond, the toolbox and accompanying software will allow easy and effective application of the fundamentally improved techniques on many infectious diseases and in different geographic contexts.

Work performed

TransMID focuses on the on the development of novel methods to estimate key epidemiological parameters from social contact data (the MIXING work packages) and serological data (the SERO work packages). The TransMID team has made progress on both parts of the project and has produced new insights, methods, software, an online data sharing platform that enables researchers to better estimate the value of serological and social contact data in studying disease transmission and efficiently use these datasets in modelling efforts.
The main achievements so far, regarding research on the use of social contact data to inform infectious disease transmission models are:
• Two manuscripts on the social contact survey in Flanders in 2011 (in preparation), one of which focuses on the comparison with the social contact survey in 2006.
• A successful workshop and hackathon meeting as well as a research visit to London School of Hygiene and Tropical Medicine to continue working on the R-package `socialmixr’.
• Several manuscripts on the analysis of social contact data and their impact on disease transmission.
• A systematic review on the use of social contact data to inform disease transmission models.
• A contribution to the R package ‘socialmixr’ (statistical software to use social contact data in disease transmission models)
• A highly successful data sharing platform that allows researchers from all over the world to share and download social contact data for reuse (www.socialcontactdata.org; >45.000 downloads)
• New funding to set up a social contact survey in Belgium, focused on elderly and frail populations.

The main achievements so far, regarding research on the use of serological data to inform infectious disease transmission models are:
• Three manuscripts on using frailty models in infectious disease models informed by serological data, of which one focuses on a deterministic approach.
• A book on frailty models in collaboration with colleagues Steven Abrams, Andreas Wienke and Steffen Unkel (in preparation).
• A systematic review on the design of serosurveys.
• A manuscript on a Bayesian analysis of social contact data and serological data (in preparation)
• A manuscript on the seroepidemiology of CMV and Hepatitis A.
• A manuscript on co-infections and the impact of behavioural change on their dynamics.

Principal Investigator (PI) Niel Hens has been co-editing a book entitled`The handbook of infectious disease data analysis’ with a specific section on the analysis of seroprevalence data. The book is expected to appear in Aug-Sep 2019.

The ERC funding for TransMID has opened doors for new or intensified collaborations with public health organisations like WHO, ECDC and pharmaceutical companies who were interested in joint research or statistical consultancy services. As further recognition of the societal relevance of the TransMID research, Niel Hens obtained ERC Proof of Concept (POC) funding to develop a data science tool for epidemic forecasting (DEFOG) which will integrate classical surveillance data, pharmacy sales data, out-of-hours general practitioners’ data, social contact data and possibly other data sets in a novel real-time forecasting tool that will yield better and more rapid warning signals of the number of infected cases. The results will be of value for various stakeholders in the healthcare sector.

Final results

All output described above can be considered novel as they provide new insights and solutions for important issues related to the use of social contact and serological data in mathematical models for disease transmission. We highlight our paper published in Proceedings of the Royal Society Series B as unconventional in the sense that it refuted one of the key assumptions made in mathematical epidemiology namely the random mixing assumption and as such received a lot of attention. We also highlight our paper on the impact of behavioural change on the dynamics of co-infections which reveals that the interplay between behaviour and infections transmitted via the respiratory route is non-trivial.

Website & more info

More info: http://www.socialcontactdata.org.