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The Moving Epidemics Method MEM is a tool developed in the Health Sentinel Network of Castilla y León (Spain) to help in the routine influenza surveillance in health systems. It gives a better understanding of the annual influenza epidemics and allows the weekly assessment of the epidemic status and intensity.
Although in its conception it was originally created to be used with influenza data and health sentinel networks, MEM has been tested with different respiratory infectious diseases and surveillance systems so nowadays it could be used with any parameter which present a seasonal accumulation of cases that can be considered an epidemic.
MEM development started in 2001 and the first record appeared in 2003 in the Options for the Control of Influenza V. It was presented to the baselines working group of the European Influenza Surveillance Scheme (EISS) in the 12th EISS Annual Meeting (Malaga, Spain, 2007), with whom started a collaboration that continued when, in 2008, was established the European Influenza Surveillance Network.
In 2009 MEM is referenced in an official European document: the Who European guidance for influenza surveillance in humans. A year later MEM was implemented in The European Surveillance System (TESSy), of the European Centre for Disease Prevention and Control (ECDC), and in 2012, after a year piloting, in the EuroFlu regional influenza surveillance platform, of the World Health Organization Regional Office for Europe (WHO-E).
As a result of the collaboration with ECDC and WHO-E, two papers have been published, one related to the establishment of epidemic thresholds and other to the comparison of intensity levels in Europe.
The stable package can be installed from the official R repositories (CRAN) using the built-in install function (or from the package manager in some GUIs for R):
# install the memapp CRAN version
install.packages("mem")Or from the official repository:
if(!require("devtools")) install.packages("devtools")
library("devtools")
# install the mem stable version from GitHub
install_github("lozalojo/mem", ref = "master")To install the development version of mem use the devtools package.
if(!require("devtools")) install.packages("devtools")
library("devtools")
# install the memapp development version from GitHub
install_github("lozalojo/mem", ref = "development")There is a package that acts as a Graphical User Interface (GUI) for mem. The package is called memapp, you can find more information on the official repository:
# load the library
library("mem")
# run the help
help("mem")Vega T, Lozano JE, Ortiz de Lejarazu R, Gutierrez Perez M. Modelling influenza epidemic—can we detect the beginning and predict the intensity and duration? Int Congr Ser. 2004 Jun;1263:281–3.
Vega T, Lozano JE, Meerhoff T, Snacken R, Mott J, Ortiz de Lejarazu R, et al. Influenza surveillance in Europe: establishing epidemic thresholds by the moving epidemic method. Influenza Other Respir Viruses. 2013 Jul;7(4):546–58. DOI:10.1111/j.1750-2659.2012.00422.x.
Vega T, Lozano JE, Meerhoff T, Snacken R, Beaute J, Jorgensen P, et al. Influenza surveillance in Europe: comparing intensity levels calculated using the moving epidemic method. Influenza Other Respir Viruses. 2015 Sep;9(5):234–46. DOI:10.1111/irv.12330.
Lozano JE. lozalojo/mem: Second release of the MEM R library. Zenodo
[Internet]. [cited 2017 Feb 1]; Available from:
https://zenodo.org/record/165983.
Lozano JE. lozalojo/memapp: Second release of the MEM Shiny Web
Application R package. Zenodo [Internet]. [cited 2018 Feb 15]; Available
from: https://zenodo.org/record/1173518. 
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.