Retrospective space-time cluster analysis of whooping cough, re-emergence in Barcelona, Spain, 2000-2011

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012)

BACKGROUND

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution.

METHODS

We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics.

RESULTS

Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk.

CONCLUSIONS

We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Evaluation of reported cases of pertussis: epidemiological study in a large city in Spain

We retrospectively analysed the incidence rate of reported cases of pertussis in Barcelona during 2009–2012 according to age, sex, type of medical centre and vaccination status. We included 748 confirmed or suspected cases, 613 (82.0 %) of which were confirmed by laboratory testing and the remaining 135 (18.0 %) by epidemiological evidence. The highest reported incidence of pertussis was amongst <1 year olds [96.1 per 100 000 person-years, 95 % confidence interval (CI): 84.3–109.1]. The majority of confirmed and suspected cases were reported in 2011 and 2012, and the total incidence (confirmed or suspected) was 6.3 (95 % CI: 5.6–6.9) and 4.2 (95 % CI: 3.6–4.7) per 100 000 person-years, respectively. Incidence increased significantly (P = 0.001) in 2011–2012 compared with 2009. Most confirmed cases occurred in children <1 year old (87.9 %). Cases were confirmed by real-time (RT)-PCR (87.5 %; 95 % CI: 81.3–87.6) and bacterial culture (13.7 %; 95 % CI: 11.0–17.1). We recommend performing RT-PCR in suspected cases with no epidemiological link to a confirmed case.