This function fits a FluMoDL object. This is a distributed lag nonlinear model (DLNM), of quasipoisson family and with log link, which estimates the association between mortality (as outcome) and daily mean temperatures and type-specific influenza incidence proxies (as exposures), adjusted for covariates.
A vector of daily deaths, of equal length to argument
A vector of daily mean temperatures, of equal length to argument
A vector of dates (of class
A vector of weekly influenza A(H1N1)pdm09 incidence proxies, of equal
length to argument
A vector of weekly influenza A(H3N2) incidence proxies, of equal
length to argument
A vector of weekly influenza B incidence proxies, of equal
length to argument
An integer vector of weeks, in yyyyww format
An optional vector of weekly RSV incidence proxies, of equal
length to argument
Should a periodic B-spline term be included in the model?
Objects of class 'FluMoDL' contain the model, the associated data, estimates of the predicted
associations and other information.
These objects can be further used as input for function
attrMort, to calculate
influenza-attributable and temperature-attributable mortalities for any period in the data
(and any temperature range). Methods
been defined for objects of class 'FluMoDL' (see below),
FluMoDL uses a DLNM with the daily number of deaths as the outcome. Covariates include the following:
cross-basis matrix for temperature. The exposure-response
relationship is modelled with a quadratic B-spline with internal knots placed at the
10th, 75th and 90th percentile of the temperatures distribution. The lag-response
relationship is modelled with a natural cubic spline with three internal knots
equidistant in the log scale.
cross-basis matrices for influenza incidence proxies for
each type/subtype: A(H1N1)pdm09, A(H3N2) and B. These normally are equal to a
sentinel Influenza-Like Illness (ILI) rate, times the laboratory swab samples Percentage
implying an approximately constant case fatality ratio for each influenza type. The
lag-response relationship is specified as above (for temperature).
A periodic B-spline term to model seasonality, with three equidistant internal
knots according to day of the year. Can optionally be suppressed by setting argument
A linear trend, and a factor variable for day of the week.
cross-basis matrix for an RSV
incidence proxy, with specification identical to those for influenza. If given,
it will be included in the model and output, and it will be possible to calculate
mortality attributable to RSV with
attrMort. This is an experimental feature;
it might be removed in the future.
An object of class 'FluMoDL'. This is a list containing the following elements:
data.frame with the data used to fit the model. Rows correspond to
days in argument
dates. The columns are named:
temp, (for temperature),
t (linear trend, with values
doy (day of year,
use to calculate the periodic B-spline term to model seasonality) and
dow (day of
the week). Also column
proxyRSV if the relevant argument is provided.
The fitted model; an object of class
glm and of 'quasipoisson' family
with log link.
A list with names 'temp', 'proxyH1', 'proxyH3' and 'proxyB' (and proxyRSV,
if provided in the function arguments), containing the
cross-basis matrices that are used as exposures in the model. See
The Minimum Mortality Point, i.e. the temperature where mortality is lowest.
A list with names 'temp', 'proxyH1', 'proxyH3' and 'proxyB' (and 'proxyRSV'
if provided in the function arguments), containing
predictions (in the form of
crosspred objects) for each exposure.
These can be plotted in both the exposure-response and lag-response dimensions, see
plot.crosspred and the examples below.
This element is NULL when creating the object, but can receive a
summary.FluMoDL object that contains Best Linear Unbiased Predictor
(BLUP) coefficients, to be used when estimating attributable mortality. Can be
retrieved or set with the
Objects of class 'FluMoDL' have methods
coef() returns a list of numeric vectors, with names 'proxyH1', 'proxyH3'
and 'proxyB' (and 'proxyRSV' if provided in the function arguments), containing the model
coefficients for these cross-basis terms. Similarly
vcov() returns a list
of variance-covariance matrices for the same terms.
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 (PubMed)
Gasparrini A, Armstrong B, Kenward MG. Distributed lag non-linear models. Stat Med 2010;29(21):2224–34.
Gasparrini A, et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet 2015 Jul 25;386(9991):369–75.
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data(greece) # Use example surveillance data from Greece m <- with(greece, fitFluMoDL(deaths = daily$deaths, temp = daily$temp, dates = daily$date, proxyH1 = weekly$ILI * weekly$ppH1, proxyH3 = weekly$ILI * weekly$ppH3, proxyB = weekly$ILI * weekly$ppB, yearweek = weekly$yearweek)) m # Plot the association between A(H1N1)pdm09 activity and mortality # and the overall temperature-mortality association: plot(m$pred$proxyH1, "overall") plot(m$pred$temp, "overall") # Add the Minimum Mortality Point to the plot: abline(v=m$MMP) # Check the lag-response dimension for the A(H1N1)pdm09 - mortality # association, for all proxy values, and for an indicative value of 30. plot(m$pred$proxyH1) # Produces a 3D plot, see ?plot.crosspred plot(m$pred$proxyH1, var=30) # Have a look at the data associated with this FluMoDL: str(m$data) tail(m$data)
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