Contact Network
An instrument to map networks of social contacts between individuals.
Within the Contact Network measurement module we employ ultra-wideband (UWB) technology to measure the physical distances between individuals. To measure the physical distances between individuals, participants are equipped with a wearable tag that uses ultra-wideband technology that measures the distances between individuals who are within line-of-sight with an accuracy of 10cm at a frequency of 1Hz. The measured distances form the basis for the construction of Contact Networks.
Contact networks of two different physical distancing interventions based on data from the Smart Distance Lab.
Initial Applications
The Contact Network measurement module was initially developed as a response to the Covid-19 pandemic. At the beginning of the pandemic, conventional measures of virus spread were based on population statistics such as hospital admissions and country-level interventions, which are delayed indicators of behavioral interventions. Therefore, we developed the BECON framework which makes use of contact networks in which physical distances between individuals are encoded. This allows for a direct behavioral assessment of interventions that are targeted at physical distances between individuals as was the case during the Covid-19 pandemic. The direct assessment of physical distances formed the basis of the experiments we did with the Smart Distance Lab. In these experiments we measured the physical distances between individuals under various behavioral interventions, such as wearing face masks, walking directions, buzzers, or shopping carts. You can read more on the Smart Distance Lab here.
To build a contact network from experimental data collected during the Smart Distance Lab, the frequency of physical contacts below a 1,5 m threshold was assessed.
Further Applications
The measurement of Contact Networks has applications beyond Covid-19. It allows us to assess the physical distances between individuals in various situations: interactions between children in a classroom, mingling of attendants at a conference, and so forth. We have developed a pipeline to collect the data, construct the Contact Networks, describe, and test the networks using BECON indicators, see BECON for more details. In case contacts need to be promoted (e.g., in the case of stimulating interactions across disciplines) or broken down (e.g., in the case of Covid-19), the pipeline allows to set up an experimental design and evaluate the effectiveness of a manipulation on the contact network using BECON indicators and B2 models.