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FluMoDL - InFluenza-attributable Mortality with Distributed Lag models

This package implements a method to estimate influenza-attributable mortality, and also mortality attributable to ambient temperatures, using distributed lag nonlinear models. These models allow addressing the lag dimension of mortality, and provide for a more detailed adjustment for the confounding effect of temperature in the relationship between influenza and mortality.

To fit a FluMoDL one needs to have:

• a series of daily mean temperatures for the region of interest
• a daily series of deaths
• a weekly series of Influenza-Like Illness (ILI) rates, estimated via sentinel surveillance
• three weekly series of laboratory swab samples Percentage Positives (%) to influenza A(H1N1)pdm09, A(H3N2) and B

These should all cover the same time period.

The package provides functions to facilitate fitting a FluMoDL, summarizing and plotting the results of the analysis, and calculating attributable mortalities (including empirical 95% Confidence Intervals). It also includes the capability to pool analytical results together and calculate attributable mortalities based on BLUP (Best Unbiased Linear Predictor) estimates.

Installation

Packages ‘dlnm’ and ‘mvmeta’, by Antonio Gasparrini are the only dependencies for the FluMoDL package. You need to have those installed from CRAN with install.packages(c("dlnm","mvmeta")). Also install the devtools package if you don’t already have it: install.packages("devtools").

Then to install FluMoDL, open R and give:

  devtools::install_git("https://github.com/thlytras/FluMoDL.git")

Check back here often for new updates of the package!

Usage

See package documentation. One uses the function fitFluMoDL() to fit the model on the available surveillance data, then gives the fitted model object to attrMort() to calculate attributable mortalities (to influenza, temperature and -optionally- RSV). Check the help pages of these two functions for details. In order to try these out, the package also includes some example surveillance data from Greece (see ?greece).

References

• Lytras T, Pantavou K, Mouratidou E, Tsiodras S. Mortality attributable to seasonal influenza in Greece, 2013 to 2017: variation by type/subtype and age, and a possible harvesting effect. Euro Surveill 2019;24(14):pii=1800118
• Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models. Stat Med 2010;29(21):2224–34.
• Gasparrini A, Leone M. Attributable risk from distributed lag models. BMC Med Res Methodol 2014;14:55.
• Gasparrini A, Armstrong B, Kenward MG. Multivariate meta-analysis for non-linear and other multi-parameter associations. Stat Med 2012;31(29):3821–39.

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.