`incidence.Rd`

This function computes incidence based on dates of events provided in various formats. A fixed interval, provided as numbers of days, is used to define time intervals. Counts within an interval always include the first date, after which they are labeled, and exclude the second. For instance, intervals labeled as 0, 3, 6, ... mean that the first bin includes days 0, 1 and 2, the second interval includes 3, 4 and 5 etc.

incidence(dates, interval = 1L, ...) # S3 method for default incidence(dates, interval = 1L, ...) # S3 method for Date incidence(dates, interval = 1L, standard = TRUE, groups = NULL, na_as_group = TRUE, first_date = NULL, last_date = NULL, ...) # S3 method for character incidence(dates, interval = 1L, standard = TRUE, groups = NULL, na_as_group = TRUE, first_date = NULL, last_date = NULL, ...) # S3 method for integer incidence(dates, interval = 1L, groups = NULL, na_as_group = TRUE, first_date = NULL, last_date = NULL, ...) # S3 method for numeric incidence(dates, interval = 1L, groups = NULL, na_as_group = TRUE, first_date = NULL, last_date = NULL, ...) # S3 method for POSIXt incidence(dates, interval = 1L, standard = TRUE, groups = NULL, na_as_group = TRUE, first_date = NULL, last_date = NULL, ...) # S3 method for incidence print(x, ...)

dates | A vector of dates, which can be provided as objects of the
class: integer, numeric, Date, POSIXct, POSIXlt, and character. (See Note
about |
---|---|

interval | An integer or character indicating the (fixed) size of the time interval used for computing the incidence; defaults to 1 day. This can also be a text string that corresponds to a valid date interval: day, week, month, quarter, or year. (See Note). |

... | Additional arguments passed to other methods (none are used). |

standard | (Only applicable to Date objects) When |

groups | An optional factor defining groups of observations for which incidence should be computed separately. |

na_as_group | A logical value indicating if missing group (NA) should be treated as a separate group. |

first_date, last_date | optional first/last dates to be used in the
epicurve. When these are |

x | An 'incidence' object. |

An list with the class `incidence`

, which contains the
following items:

**dates**: The dates marking the left side of the bins used for counting events. When`standard = TRUE`

and the interval represents weeks, months, quarters, or years, the first date will represent the first standard date (See Interval specification, below).**counts**: A matrix of incidence counts, which one column per group (and a single column if no groups were used).**timespan**: The length of the period for which incidence is computed, in days.**interval**: The bin size. If it's an integer, it represents the number of days between each bin. It can also be a character, e.g. "2 weeks" or "6 months".**n**: The total number of cases.**weeks**: Dates in week format (YYYY-Www), where YYYY corresponds to the year of the given week and ww represents the numeric week of the year. This will be a produced from the function`aweek::date2week()`

. Note that these will have a special`"week_start"`

attribute indicating which day of the ISO week the week starts on (see Weeks, below).**isoweeks**: ISO 8601 week format YYYY-Www, which is returned only when ISO week-based weekly incidence is computed.

For details about the `incidence class`

, see the dedicated
vignette:

`vignette("incidence_class", package = "incidence")`

`dates`

)**Decimal (numeric) dates**: will be truncated with a warning**Character dates**should be in the unambiguous`yyyy-mm-dd`

(ISO 8601) format. Any other format will trigger an error.

`interval`

)`interval`

is a valid character (e.g. "week" or "1 month"), then
the bin will start at the beginning of the interval just before the first
observation by default. For example, if the first case was recorded on
Wednesday, 2018-05-09:
"week" : first day of the week (i.e. Monday, 2018-05-07) (defaults to ISO weeks, see "Week intervals", below)

"month" : first day of the month (i.e. 2018-05-01)

"quarter" : first day of the quarter (i.e. 2018-04-01)

"year" : first day of the calendar year (i.e. 2018-01-01)

`standard = FALSE`

, which
sets the interval to begin at the first observed case.
`aweek::date2week()`

function from the aweek package. The default
state is to use ISO 8601 definition of weeks, which start on Monday. You can
specify the day of the week an incidence object should be standardised to by
using the pattern "n W weeks" where "W" represents the weekday in an
English or current locale and "n" represents the duration, but this can be
ommitted. Below are examples of specifying weeks starting on different days
assuming we had data that started on 2016-09-05, which is ISO week 36 of
2016:
interval = "2 monday weeks" (Monday 2016-09-05)

interval = "1 tue week" (Tuesday 2016-08-30)

interval = "1 Wed week" (Wednesday 2016-08-31)

interval = "1 Thursday week" (Thursday 2016-09-01)

interval = "1 F week" (Friday 2016-09-02)

interval = "1 Saturday week" (Saturday 2016-09-03)

interval = "Sunday week" (Sunday 2016-09-04)

interval = "week", standard = TRUE (Default, Monday)

interval = "ISOweek" (Monday)

interval = "EPIweek" (Sunday)

interval = "MMWRweek" (Sunday)

`first_date`

argument`first_date`

argument override
`standard = TRUE`

. It has been changed as of `first_date = NULL`

. This, however
may be a change in behaviour, so a warning is now issued once and only once
if `first_date`

is specified, but `standard`

is not. To never see this
warning, use `options(incidence.warn.first_date = FALSE)`

.
The intervals for "month", "quarter", and "year" will necessarily vary in the number of days they encompass and warnings will be generated when the first date falls outside of a calendar date that is easily represented across the interval.

The main other functions of the package include:

`incidence::plot.incidence()`

: Plot epicurves from an incidence object.`incidence::fit()`

: Fit log-linear model to computed incidence.`incidence::fit_optim_split()`

: Find the optimal peak of the epidemic and fits log-linear models on either side of the peak.`incidence::subset()`

: Handling of`incidence`

objects.`incidence::pool()`

: Sum incidence over groups.`incidence::as.data.frame.incidence()`

: Convert an`incidence`

object to a`data.frame`

.

The following vignettes are also available:

`overview`

: Provides an overview of the package's features.`customize_plot`

: Provides some tips on finer plot customization.`incidence_class`

: Details the content of the`incidence`

class.

#> <incidence object> #> [10 cases from days 1 to 9] #> #> $counts: matrix with 9 rows and 1 columns #> $n: 10 cases in total #> $dates: 9 dates marking the left-side of bins #> $interval: 1 day #> $timespan: 9 days #> $cumulative: FALSE #>#> <incidence object> #> [10 cases from days 1 to 9] #> #> $counts: matrix with 5 rows and 1 columns #> $n: 10 cases in total #> $dates: 5 dates marking the left-side of bins #> $interval: 2 days #> $timespan: 9 days #> $cumulative: FALSE #>## example using simulated dataset if(require(outbreaks)) { withAutoprint({ onset <- outbreaks::ebola_sim$linelist$date_of_onset ## daily incidence inc <- incidence(onset) inc plot(inc) ## weekly incidence inc.week <- incidence(onset, interval = 7, standard = FALSE) inc.week plot(inc.week) plot(inc.week, border = "white") # with visible border # Starting on Monday inc.isoweek <- incidence(onset, interval = "isoweek") inc.isoweek # Starting on Sunday inc.epiweek <- incidence(onset, interval = "epiweek") inc.epiweek # Starting on Saturday inc.epiweek <- incidence(onset, interval = "saturday epiweek") inc.epiweek ## use group information sex <- outbreaks::ebola_sim$linelist$gender inc.week.gender <- incidence(onset, interval = 7, groups = sex, standard = FALSE) inc.week.gender head(inc.week.gender$counts) plot(inc.week.gender, border = "grey90") inc.satweek.gender <- incidence(onset, interval = "2 epiweeks: saturday", groups = sex) inc.satweek.gender plot(inc.satweek.gender, border = "grey90") })}#> > onset <- outbreaks::ebola_sim$linelist$date_of_onset #> > inc <- incidence(onset) #> > inc #> <incidence object> #> [5888 cases from days 2014-04-07 to 2015-04-30] #> #> $counts: matrix with 389 rows and 1 columns #> $n: 5888 cases in total #> $dates: 389 dates marking the left-side of bins #> $interval: 1 day #> $timespan: 389 days #> $cumulative: FALSE #> #> > plot(inc)#> > inc.week <- incidence(onset, interval = 7, standard = FALSE) #> > inc.week #> <incidence object> #> [5888 cases from days 2014-04-07 to 2015-04-27] #> #> $counts: matrix with 56 rows and 1 columns #> $n: 5888 cases in total #> $dates: 56 dates marking the left-side of bins #> $interval: 7 days #> $timespan: 386 days #> $cumulative: FALSE #> #> > plot(inc.week)#> > plot(inc.week, border = "white")#> > inc.isoweek <- incidence(onset, interval = "isoweek") #> > inc.isoweek #> <incidence object> #> [5888 cases from days 2014-04-07 to 2015-04-27] #> [5888 cases from ISO weeks 2014-W15 to 2015-W18] #> #> $counts: matrix with 56 rows and 1 columns #> $n: 5888 cases in total #> $dates: 56 dates marking the left-side of bins #> $interval: 1 week #> $timespan: 386 days #> $cumulative: FALSE #> #> > inc.epiweek <- incidence(onset, interval = "epiweek") #> > inc.epiweek #> <incidence object> #> [5888 cases from days 2014-04-06 to 2015-04-26] #> [5888 cases from MMWR weeks 2014-W15 to 2015-W17] #> #> $counts: matrix with 56 rows and 1 columns #> $n: 5888 cases in total #> $dates: 56 dates marking the left-side of bins #> $interval: 1 week #> $timespan: 386 days #> $cumulative: FALSE #> #> > inc.epiweek <- incidence(onset, interval = "saturday epiweek") #> > inc.epiweek #> <incidence object> #> [5888 cases from days 2014-04-05 to 2015-04-25] #> [5888 cases from (Saturday) weeks 2014-W14 to 2015-W17] #> #> $counts: matrix with 56 rows and 1 columns #> $n: 5888 cases in total #> $dates: 56 dates marking the left-side of bins #> $interval: 1 week #> $timespan: 386 days #> $cumulative: FALSE #> #> > sex <- outbreaks::ebola_sim$linelist$gender #> > inc.week.gender <- incidence(onset, interval = 7, groups = sex, standard = FALSE) #> > inc.week.gender #> <incidence object> #> [5888 cases from days 2014-04-07 to 2015-04-27] #> [2 groups: f, m] #> #> $counts: matrix with 56 rows and 2 columns #> $n: 5888 cases in total #> $dates: 56 dates marking the left-side of bins #> $interval: 7 days #> $timespan: 386 days #> $cumulative: FALSE #> #> > head(inc.week.gender$counts) #> f m #> [1,] 1 0 #> [2,] 0 1 #> [3,] 4 1 #> [4,] 4 0 #> [5,] 9 3 #> [6,] 8 10 #> > plot(inc.week.gender, border = "grey90")#> > inc.satweek.gender <- incidence(onset, interval = "2 epiweeks: saturday", #> + groups = sex) #> > inc.satweek.gender #> <incidence object> #> [5888 cases from days 2014-04-05 to 2015-04-18] #> [5888 cases from (Saturday) weeks 2014-W14 to 2015-W16] #> [2 groups: f, m] #> #> $counts: matrix with 28 rows and 2 columns #> $n: 5888 cases in total #> $dates: 28 dates marking the left-side of bins #> $interval: 2 weeks #> $timespan: 379 days #> $cumulative: FALSE #> #> > plot(inc.satweek.gender, border = "grey90")# Use of first_date d <- Sys.Date() + sample(-3:10, 10, replace = TRUE) # `standard` specified, no warning di <- incidence(d, interval = "week", first_date = Sys.Date() - 10, standard = TRUE) # warning issued if `standard` not specified di <- incidence(d, interval = "week", first_date = Sys.Date() - 10)#> Warning: #> #> As of incidence version 1.6.0, the default behavior has been modified so that `first_date` no longer overrides `standard`. This means that the first date will be either on or before 2019-03-04. #> If you want to use Sys.Date() - 10 as the precise `first_date`, set `standard = FALSE`. #> #> To remove this warning in the future, explicitly set the `standard` argument OR use `options(incidence.warn.first_date = FALSE)`# second instance: no warning issued di <- incidence(d, interval = "week", first_date = Sys.Date() - 10)