Author: Cherrie, Mark P. C.; Nichols, Gordon; Iacono, Gianni Lo; Sarran, Christophe; Hajat, Shakoor; Fleming, Lora E.
Title: Pathogen seasonality and links with weather in England and Wales: a big data time series analysis Document date: 2018_8_28
ID: 0x4zrfw3_3
Snippet: A systematic approach to the analysis of the potential seasonality of common pathogen serotypes and their associations with multiple weather variables is required to help narrow the focus on candidate pathogens in addition to those that have been studied in depth previously. The current analysis is well placed to address this gap given the rich data now available on a broad number of pathogens and meteorological factors. The aim of the analysis w.....
Document: A systematic approach to the analysis of the potential seasonality of common pathogen serotypes and their associations with multiple weather variables is required to help narrow the focus on candidate pathogens in addition to those that have been studied in depth previously. The current analysis is well placed to address this gap given the rich data now available on a broad number of pathogens and meteorological factors. The aim of the analysis was to use several data mining techniques to identify pathogens that display a seasonal component, and describe their associations with meteorological factors as an aid to future analytical work (including forecasting) and public health planning.
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