Visualization of data from longitudinal studies concerning multi-variant diseases
The Center for Infectious Disease Control is the national knowledge center and coordinator in the in-fectious disease domain. One way of reducing health problems related to infectious diseases is byvaccination. For some infectious diseases, such as the Human papilloma virus ( HPV ) infection andpneumococcal disease, persons can get infected by multiple variants at the same time. Because vaccin-ation only works against some variants of these diseases, the effect of vaccination on these diseases arestill unclear. Studies are being conducted to investigate this. The information in those studies is quitecomplex.Therefore we designed an interactive exploratory visualization tool, ComboVis. ComboVis can helpepidemiologist answer questions about the data from longitudinal studies concerning multi-variantdiseases. Multiple visualization techniques that are being used for data in a similar format have beendiscussed with multiple epidemiologists. Based on the feedback, we combined different visualizationtechniques. During the design phase, an early user evaluation was conducted. The feedback from theearly user evaluation is processed in the next version of ComboVis. Finally, another user evaluation withanother group of epidemiologists was conducted, which resulted in enthusiastic and positive reactionsand the final version of ComboVis.
RIVM Centre for Infectious Disease Control (CIb) performs diagnostics, surveillance and scientific research in the field of infectious diseases. This knowledge is important to gain insight in the prevalence and spread of these diseases, to set up control measures and to get information concerning the response on the measures taken.
One of the tasks of the CIb is to monitor and inform the government about potential national health threats with regard to antimicrobial resistance. Antimicrobial resistance happens when microorganisms (such as bacteria, fungi, viruses, and parasites) change when they are exposed to antimicrobial drugs (such as antibiotics, antifungals, antivirals, antimalarials, and antihelmintics). As a result, the medicines become ineffective and infections persist in the body, increasing the risk of spread to others. Based on the Dutch national antimicrobial resistance surveillance system (ISIS-AR), occurrence of and trends in antimicrobial resistance are monitored using routine antibiotic susceptibility testing data from microbiology laboratories in the Netherlands. In 2015, more than 637,000 isolates were analyzed, comprising isolates of 151 different species of pathogens. For each isolate, susceptibility to on average 19 different antibiotics is tested. The combination of all susceptibility test results for one isolate is called an antibiogram.
As a service to the participating laboratories, the laboratories can query the ISIS-AR database and request a report with a summary of the data of their own laboratory via an interactive web system (ISISweb). However, currently we only provide resistance data for each combination of pathogen and antibiotic separately. The information regarding (changes in) antibiograms is limited, since as of yet we have not found a solution for visualizing these multi-dimensional data.
We think visualization can help us to communicate these complex data. The task for the student is to design, implement, and evaluate an interactive visualization prototype system, which enables epidemiologists and laboratories to obtain insight in the data. The main challenges are to deal with the combination of many different types of data (multivariate, temporal, and hierarchical) and to enable domain experts to explore these data efficiently.