EPIPOI: A user-friendly analytical tool for the extraction and visualization of temporal parameters from epidemiological time series
Open Access
- 15 November 2012
- journal article
- Published by Springer Nature in BMC Public Health
- Vol. 12 (1), 982
- https://doi.org/10.1186/1471-2458-12-982
Abstract
There is an increasing need for processing and understanding relevant information generated by the systematic collection of public health data over time. However, the analysis of those time series usually requires advanced modeling techniques, which are not necessarily mastered by staff, technicians and researchers working on public health and epidemiology. Here a user-friendly tool, EPIPOI, is presented that facilitates the exploration and extraction of parameters describing trends, seasonality and anomalies that characterize epidemiological processes. It also enables the inspection of those parameters across geographic regions. Although the visual exploration and extraction of relevant parameters from time series data is crucial in epidemiological research, until now it had been largely restricted to specialists.Keywords
This publication has 27 references indexed in Scilit:
- Were Equatorial Regions Less Affected by the 2009 Influenza Pandemic? The Brazilian ExperiencePLOS ONE, 2012
- Public Health Surveillance and Knowing About Health in the Context of Growing Sources of Health DataAmerican Journal of Preventive Medicine, 2011
- Mortality burden of the 1918–1919 influenza pandemic in EuropeInfluenza and Other Respiratory Viruses, 2009
- Online detection and quantification of epidemicsBMC Medical Informatics and Decision Making, 2007
- Incriminating bluetongue virus vectors with climate envelope modelsJournal of Applied Ecology, 2007
- Seasonality of Influenza in Brazil: A Traveling Wave from the Amazon to the SubtropicsAmerican Journal of Epidemiology, 2007
- Synchrony, Waves, and Spatial Hierarchies in the Spread of InfluenzaScience, 2006
- Travelling waves in the occurrence of dengue haemorrhagic fever in ThailandNature, 2004
- Satellite imagery in the study and forecast of malariaNature, 2002
- Fourier Series for analysis of temporal sequences of satellite sensor imageryInternational Journal of Remote Sensing, 1994