Returns a data.frame
summarizing a Covidestim model run. Note that if
runOptimizer.covidestim
is used, all *.(lo|hi)
variables will be NA
-valued, because BFGS does not generate
confidence intervals.
# S3 method for covidestim_result
summary(ccr, include.before = TRUE, index = FALSE)
A covidestim_result
object
A logical scalar. Include estimations that fall in the
period before the first day of input data? (This period is of length
ndays_before
as passed to covidestim
). If TRUE
, any
elements of variables which do not have values for this "before" period
will be represented as NA
.
A logical scalar. If TRUE
, will include a variable
index
in the output, with range 1:(ndays_before + ndays)
.
A data.frame
with the following variables:
date
Date as a Date
vector.
Rt
, Rt.lo
, Rt.hi
Estimate of the effective reproductive number (\(R_t\)). Median and 95% interval, ℝ.
infections
, infections.lo
, infections.hi
The number of modeled infections that occurred on date date
.
This includes infections that may never cause symptoms, as well as
infections which will never show up in case reports (will never be
diagnosed). Being indexed by date-of-occurrence, reporting lag is
absent from this outcome. Median and 95% interval, ℝ.
cum.incidence
, cum.incidence.lo
,
cum.incidence.hi
The number of modeled cumulative infections (not cases, or diagnoses)
that have occurred by the end of date date
. Median and
95% interval, ℝ.
diagnoses
, diagnoses.lo
, diagnoses.hi
The number of modeled diagnoses that occurred on date date
.
This is the sum of:
New asmptomatic diagnoses on date date
, plus:
New diagnoses of symptomatic, non-severe individuals on date
date
, plus:
New diagnoses of severe individuals on date date
.
Median and 95% interval, ℝ.
cases.fitted
, cases.fitted.lo
,
cases.fitted.hi
The number of modeled case reports for date date
. This will
always differ from the number of observed cases: it is the
model's approximation of how many case reports should have been filed
that day. This outcome reflects underascertainment, and the full delay
structure downstream of infection events. Note: infection events are
tabulated by the infections[.lo/.hi]
outcomes. Median
and 95% interval, ℝ.
symptomatic
, symptomatic.lo
, symptomatic.hi
The number of modeled transitions of infected individuals into the
infected, symptomatic health state on date date
. This takes
into account the probability of becoming symptomatic and the delay
between infection and presentation of symptoms. Median and 95%
interval, ℝ.
symptomatic.diagnosed
, symptomatic.diagnosed.lo
,
symptomatic.diagnosed.hi
The number of modeled diagnoses of symptomatic individuals occurring
on date date
. The difference between this outcome and
the diagnoses
outcome is that diagnoses
includes
modeled diagnoses of asymptomatic individuals. Median and 95%
interval, ℝ.
severe
, severe.lo
, severe.hi
The number of transitions into the "severe" health state on date
date
. The "severe" state is defined as disease that would merit
hospitalization. This outcome is not intended to model observational
data detailing the number of COVID-positive hospital admissions or
COVID-primary-cause hospital admissions. Median and 95%
interval, ℝ.
deaths
, deaths.lo
, deaths.hi
The number of modeled deaths for date date
. The number of
deaths estimated to have occurred on date date
and does not
account for reporting delays. Median and 95% interval, ℝ.
deaths.fitted
, deaths.fitted.lo
,
deaths.fitted.hi
The number of modeled death reports for a date date
. This
will always differ from the number of observed deaths for that same
date, because deaths.fitted
is approximating how many death
reports should exist for that date. Median and 95% interval,
ℝ.
data.available
Was there input data available for date date
? This should be
TRUE
, except for the first month of estimates. logical.
sero.positive
, sero.positive.lo
,
sero.positive.hi
The number of individuals in the population who are modeled as being seropositive. This is an unreliable outcome that we don't recommend using. Median and 95% interval, ℝ.
pop.infectiousness
, pop.infectiousness.lo
,
pop.infectiousness.hi
Meant to be an estimate of infectiousness of the population for comparison with wastewater data. This is an unreliable outcome that we don't recommend using. Median and 95% interval, ℝ.