Publications

 

Research papers that have used EPIPOI for data analysis include (see other ones at this link):

• Alonso et al (2015) A global map of hemispheric influenza vaccine recommendations based on local patterns of viral circulation. Nature Scien. Rep. 5: 17214
• Geoghegan et al (2014) Seasonal Drivers of the Epidemiology of Arthropod-Borne Viruses in Australia. PLoS Negl Trop Dis 8(11): e3325. doi:10.1371/journal.pntd.0003325
• Yu et al (2013) Characterization of Regional Influenza Seasonality Patterns in China and Implications for Vaccination Strategies: Spatio-Temporal Modeling of Surveillance Data. PLoS Med 10(11): e1001552. doi:10.1371/journal.pmed.1001552
• Patel et al (2013) Global seasonality of rotavirus disease The Pediatric Infectious Disease Journal 32(4):e134-47
• Schuck-Paim et al (2012) Were Equatorial Regions Less Affected by the 2009 Influenza Pandemic? The Brazilian Experience. PLoS ONE 7(8): e41918. doi:10.1371/journal.pone.0041918
• McCormick et al (2011) An exploration of spatial patterns of seasonal diarrhoeal morbidity in Thailand. Epidemiology and Infection 19:1–8 [epub].
• Alonso et al (2012) Spatio-temporal patterns of diarrhoeal mortality in Mexico. Epidemiology and Infection 140(1):91–9.
• Alonso et al (2007) Seasonality of influenza in Brazil: a traveling wave from the Amazon to the subtropics. American Journal of Epidemiology 165:1434-42.

 

The scientific paper that describes EPIPOI is:

Alonso  &  McCormick (2012) A user friendly analytical tool for extraction of temporal and spatial parameters from epidemiological time-series.  BMC Public Health 12:982

 

The slides presentation explaining some of the analyses that epipoi can perform can be downloaded here