Accumulate setting in EpiNow2 #886

nlinton · 2024-12-10T20:02:45Z

nlinton
Dec 10, 2024

Hello, I noticed there have been a lot of updates around the accumulate setting in EpiNow2, which is very exciting to see. We've tried to run a version of the code using fill_missing(missing_dates="accumulate", initial_accumulate=7) (pulled from github, since it was not showing up in the CRAN install of EpiNow2 1.6.1) to set up the data, which then look like this:

However, trying to use this as the data for EpiNow2::epinow() results in the following error, which seems to tell me I cannot have the accumulate column in the input dataset.

Error in data.table::rbindlist(list(data.table::data.table(date = seq(min(reported_cases$date) - : Item 2 has 4 columns, inconsistent with item 1 which has 3 columns. To fill missing columns use fill=TRUE. Error in data.table::rbindlist(list(data.table::data.table(date = seq(min(reported_cases$date) - : Item 2 has 4 columns, inconsistent with item 1 which has 3 columns. To fill missing columns use fill=TRUE.

Any guidance on how to get the accumulate setting to accurately work in EpiNow2 1.6.1?

Answered by jamesmbaazam

Dec 11, 2024

The current functionality is not yet on CRAN, so you will need to install the development version from GitHub with

# Remove current installation
remove.packages("EpiNow2")
# Install dev version from GitHub
if (!require("pak")) {
  install.packages("pak")
}
pak::pkg_install("epiforecasts/EpiNow2")

View full answer

jamesmbaazam · 2024-12-10T23:22:25Z

jamesmbaazam
Dec 10, 2024
Collaborator

Hi @nlinton It's great to see that you are already trying out the new accumulate feature. I tried to reconstruct your data and reproduce your error but I didn't get that (below). Could you provide a reprex to help us diagnose your issue?

library(EpiNow2)
#> 
#> Attaching package: 'EpiNow2'
#> The following object is masked from 'package:stats':
#> 
#>     Gamma
library(data.table)

packageVersion("EpiNow2")
#> [1] '1.6.1.9000'

data <- data.table::data.table(
  date = as.Date(c("2024-08-24", "2024-08-31")),
  confirm = c(2531, 2306)
)
# View the data
data
#>          date confirm
#>        <Date>   <num>
#> 1: 2024-08-24    2531
#> 2: 2024-08-31    2306

data <- fill_missing(
  data,
  missing_dates = "accumulate",
  initial_accumulate = 7
)

# View the data
data
#> Key: <date>
#>           date confirm accumulate
#>         <Date>   <num>     <lgcl>
#>  1: 2024-08-18      NA       TRUE
#>  2: 2024-08-19      NA       TRUE
#>  3: 2024-08-20      NA       TRUE
#>  4: 2024-08-21      NA       TRUE
#>  5: 2024-08-22      NA       TRUE
#>  6: 2024-08-23      NA       TRUE
#>  7: 2024-08-24    2531      FALSE
#>  8: 2024-08-25      NA       TRUE
#>  9: 2024-08-26      NA       TRUE
#> 10: 2024-08-27      NA       TRUE
#> 11: 2024-08-28      NA       TRUE
#> 12: 2024-08-29      NA       TRUE
#> 13: 2024-08-30      NA       TRUE
#> 14: 2024-08-31    2306      FALSE

# Specify other inputs
generation_time <- Gamma(
  shape = Normal(1.3, 0.3),
  rate = Normal(0.37, 0.09),
  max = 14
)

incubation_period <- LogNormal(
  meanlog = Normal(1.6, 0.06),
  sdlog = Normal(0.4, 0.07),
  max = 14
)
# set an example reporting delay. In practice this should use an estimate
# from the literature or be estimated from data
reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10)

# estimate Rt and nowcast/forecast cases by date of infection
out <- estimate_infections(
  data = data,
  generation_time = gt_opts(generation_time),
  rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.1)),
  delays = delay_opts(incubation_period + reporting_delay)
)
#> ℹ As of version 1.5.0 missing dates or dates with `NA` cases are treated as
#>   missing. This is in contrast to previous versions where these were
#>   interpreted as dates with zero cases.
#> ℹ In order to treat missing or `NA` cases as zeroes, see solutions in
#>   <https://github.com/epiforecasts/EpiNow2/issues/767#issuecomment-2348805272>
#> ℹ If the data is reported at non-daily intervals (for example weekly), consider
#>   using `obs_opts(na="accumulate")`.
#> ℹ For more information on these options, see `?obs_opts`.
#> This message is displayed once every 8 hours.
#> Warning: There were 16 divergent transitions after warmup. See
#> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
#> to find out why this is a problem and how to eliminate them.
#> Warning: Examine the pairs() plot to diagnose sampling problems
#> Warning: Tail Effective Samples Size (ESS) is too low, indicating posterior variances and tail quantiles may be unreliable.
#> Running the chains for more iterations may help. See
#> https://mc-stan.org/misc/warnings.html#tail-ess

out$summarised
#>            date                 variable  strat                           type
#>          <Date>                   <char> <char>                         <char>
#>   1: 2024-08-18                        R   <NA> estimate based on partial data
#>   2: 2024-08-19                        R   <NA> estimate based on partial data
#>   3: 2024-08-20                        R   <NA> estimate based on partial data
#>   4: 2024-08-21                        R   <NA> estimate based on partial data
#>   5: 2024-08-22                        R   <NA> estimate based on partial data
#>  ---                                                                          
#> 126: 2024-09-04           reported_cases   <NA>                       forecast
#> 127: 2024-09-05           reported_cases   <NA>                       forecast
#> 128: 2024-09-06           reported_cases   <NA>                       forecast
#> 129: 2024-09-07           reported_cases   <NA>                       forecast
#> 130:       <NA> reporting_overdispersion   <NA>                           <NA>
#>            median        mean           sd    lower_90   lower_50     lower_20
#>             <num>       <num>        <num>       <num>      <num>        <num>
#>   1:    1.9531002    1.957395 9.860917e-02   1.8060208   1.888709    1.9279919
#>   2:    1.9511507    1.956226 9.875206e-02   1.8054405   1.888070    1.9270143
#>   3:    1.9515471    1.954867 9.958806e-02   1.8015232   1.885639    1.9260132
#>   4:    1.9513628    1.953424 1.013485e-01   1.7962150   1.883408    1.9256043
#>   5:    1.9500809    1.951989 1.041336e-01   1.7857012   1.881186    1.9241806
#>  ---                                                                          
#> 126: 1507.0000000 2710.223500 4.015238e+03 102.9000000 595.750000 1086.2000000
#> 127: 1618.5000000 2972.081500 4.510027e+03 108.9000000 656.500000 1196.6000000
#> 128: 1801.0000000 3532.740000 6.239869e+03 123.8500000 679.750000 1312.2000000
#> 129: 2176.5000000 4148.669500 6.060557e+03 120.9500000 893.000000 1546.2000000
#> 130:    0.3560215    0.371260 1.453547e-01   0.1602343   0.266294    0.3187301
#>          upper_20     upper_50     upper_90
#>             <num>        <num>        <num>
#>   1:    1.9798608    2.0259564     2.118147
#>   2:    1.9804259    2.0254079     2.119610
#>   3:    1.9794639    2.0248136     2.118680
#>   4:    1.9793869    2.0238450     2.119698
#>   5:    1.9800565    2.0222187     2.123985
#>  ---                                       
#> 126: 2069.4000000 3311.2500000  9155.900000
#> 127: 2139.6000000 3511.2500000  9734.850000
#> 128: 2470.4000000 4082.2500000 11683.200000
#> 129: 2917.4000000 5071.7500000 14354.700000
#> 130:    0.3955891    0.4640018     0.632445

^{Created on 2024-12-10 with reprex v2.1.1}

3 replies

seabbs Dec 11, 2024
Maintainer

@jamesmbaazam the difference I see between what you have and what @nlinton is reporting is that they are reporting having used epinow() and you have used estimate_infections(). I can imagine that there is an integration test missing here and that the data ingestion in epinow is the problem (if this is the case it suggests that there is a DRY problem here as if epinow() is passing to estimate_infections() they should have the same check.

jamesmbaazam Dec 11, 2024
Collaborator

Sorry, that's actually an artifact of me checking if there was a difference between estimate_infections() and epinow(). The epinow() version has no issue as well

library(EpiNow2)
#> 
#> Attaching package: 'EpiNow2'
#> The following object is masked from 'package:stats':
#> 
#>     Gamma
library(data.table)

packageVersion("EpiNow2")
#> [1] '1.6.1.9000'

data <- data.table::data.table(
  date = as.Date(c("2024-08-24", "2024-08-31")),
  confirm = c(2531, 2306)
)
# View the data
data
#>          date confirm
#>        <Date>   <num>
#> 1: 2024-08-24    2531
#> 2: 2024-08-31    2306

data <- fill_missing(
  data,
  missing_dates = "accumulate",
  initial_accumulate = 7
)

# View the data
data
#> Key: <date>
#>           date confirm accumulate
#>         <Date>   <num>     <lgcl>
#>  1: 2024-08-18      NA       TRUE
#>  2: 2024-08-19      NA       TRUE
#>  3: 2024-08-20      NA       TRUE
#>  4: 2024-08-21      NA       TRUE
#>  5: 2024-08-22      NA       TRUE
#>  6: 2024-08-23      NA       TRUE
#>  7: 2024-08-24    2531      FALSE
#>  8: 2024-08-25      NA       TRUE
#>  9: 2024-08-26      NA       TRUE
#> 10: 2024-08-27      NA       TRUE
#> 11: 2024-08-28      NA       TRUE
#> 12: 2024-08-29      NA       TRUE
#> 13: 2024-08-30      NA       TRUE
#> 14: 2024-08-31    2306      FALSE

# Specify other inputs
generation_time <- Gamma(
  shape = Normal(1.3, 0.3),
  rate = Normal(0.37, 0.09),
  max = 14
)

incubation_period <- LogNormal(
  meanlog = Normal(1.6, 0.06),
  sdlog = Normal(0.4, 0.07),
  max = 14
)
# set an example reporting delay. In practice this should use an estimate
# from the literature or be estimated from data
reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10)

# estimate Rt and nowcast/forecast cases by date of infection
out <- epinow(
  data = data,
  generation_time = gt_opts(generation_time),
  rt = rt_opts(prior = LogNormal(mean = 2, sd = 0.1)),
  delays = delay_opts(incubation_period + reporting_delay)
)
#> Logging threshold set at INFO for the name logger
#> Writing EpiNow2 logs to the console and:
#> '/var/folders/vr/dn4r1_zj417drd1zr9301trw0000gp/T//RtmpqTcVBG/regional-epinow/2024-08-31.log'.
#> Logging threshold set at INFO for the name logger
#> Writing EpiNow2.epinow logs to the console and:
#> '/var/folders/vr/dn4r1_zj417drd1zr9301trw0000gp/T//RtmpqTcVBG/epinow/2024-08-31.log'.
#> WARN [2024-12-11 10:56:39] epinow: The `filter_leading_zeros` argument of `estimate_infections()` is deprecated as of EpiNow2 1.7.0. - 
#> WARN [2024-12-11 10:56:39] epinow: The `zero_threshold` argument of `estimate_infections()` is deprecated as of EpiNow2 1.7.0. -
#> ℹ As of version 1.5.0 missing dates or dates with `NA` cases are treated as
#>   missing. This is in contrast to previous versions where these were
#>   interpreted as dates with zero cases.
#> ℹ In order to treat missing or `NA` cases as zeroes, see solutions in
#>   <https://github.com/epiforecasts/EpiNow2/issues/767#issuecomment-2348805272>
#> ℹ If the data is reported at non-daily intervals (for example weekly), consider
#>   using `obs_opts(na="accumulate")`.
#> ℹ For more information on these options, see `?obs_opts`.
#> This message is displayed once every 8 hours.
#> WARN [2024-12-11 10:56:45] epinow: There were 8 divergent transitions after warmup. See
#> https://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
#> to find out why this is a problem and how to eliminate them. - 
#> WARN [2024-12-11 10:56:45] epinow: Examine the pairs() plot to diagnose sampling problems
#>  -

out$plots$summary

^{Created on 2024-12-11 with reprex v2.1.1}

seabbs Dec 11, 2024
Maintainer

Ah nice - no worries. Good idea to check that and good it isn't the issue!

nlinton · 2024-12-11T19:27:06Z

nlinton
Dec 11, 2024
Author

My suspicion is perhaps it's a package version issue? I tried running the same code as @jamesmbaazam with packageVersion("EpiNow2") printing ‘1.6.1’ from CRAN, (code below, but not reprex).

`print(packageVersion("EpiNow2"))

data <- data.table::data.table(
date = as.Date(c("2024-08-24", "2024-08-31")),
confirm = c(2531, 2306)
)

data <- fill_missing(
data,
missing_dates = "accumulate",
initial_accumulate = 7
)

generation_time <- Gamma(
shape = Normal(1.3, 0.3),
rate = Normal(0.37, 0.09),
max = 14
)

incubation_period <- LogNormal(
meanlog = Normal(1.6, 0.06),
sdlog = Normal(0.4, 0.07),
max = 14
)

reporting_delay <- LogNormal(mean = 2, sd = 1, max = 10)

out <- estimate_infections(
data = data,
generation_time = gt_opts(generation_time),
rt = rt_opts(prior = list(mean = 2, sd = 0.1)),
delays = delay_opts(incubation_period + reporting_delay)
)

out$summarised`

I received the error
Error in data.table::rbindlist(list(data.table::data.table(date = seq(min(reported_cases$date) - : Item 2 has 4 columns, inconsistent with item 1 which has 3 columns. To fill missing columns use fill=TRUE. Error in data.table::rbindlist(list(data.table::data.table(date = seq(min(reported_cases$date) - : Item 2 has 4 columns, inconsistent with item 1 which has 3 columns. To fill missing columns use fill=TRUE.

It seems from the posts by @jamesmbaazam this is succeeding on '1.6.1.9000' but not for ‘1.6.1’ on CRAN. Is there a way to get '1.6.1.9000' from GitHub? devtools::install_github("epiforecasts/[email protected]") does not work.

10 replies

jamesmbaazam Dec 11, 2024
Collaborator

The current functionality is not yet on CRAN, so you will need to install the development version from GitHub with

# Remove current installation
remove.packages("EpiNow2")
# Install dev version from GitHub
if (!require("pak")) {
  install.packages("pak")
}
pak::pkg_install("epiforecasts/EpiNow2")

Answer selected by nlinton

seabbs Dec 12, 2024
Maintainer

Ah interesting. We should have a new CRAN release soon with this functionality but in the meantime if you need a pinned release you can use devtools::install_github("epiforecasts/EpiNow2@<commit-hash>").

nlinton Dec 12, 2024
Author

Works great with the Github development version! Thanks for developing this functionality. Unfortunately, we can't operationalize it for our current workflow until it is on CRAN. What is the eta on the CRAN release?

nlinton Dec 12, 2024
Author

Also, just FYI, the pak code was "installing" for two hours before I gave up on it. devtools::install_github("epiforecasts/[email protected]") also did not work for whatever reason.

A simple remotes::install_github("epiforecasts/EpiNow2") got me to '1.6.1.9000' though.

seabbs Dec 13, 2024
Maintainer

the pak code was "installing" for two hours before I gave up on it.

Super weird.

also did not work for whatever reason.

So this is because there isn't a fixed release for the development version (as its evolving) so nothing exists at v1..6.1.9000. If you did need a fixed version though the thing to do is use the git commit hash vs a tag (but this is quite an edge case use).

I can't really speak as to the planned release schedule but I would think soon. @sbfnk?

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Accumulate setting in EpiNow2 #886

{{title}}

{{editor}}'s edit

{{editor}}'s edit

Replies: 2 comments 13 replies

{{title}}

{{title}}

{{title}}

{{editor}}'s edit

{{editor}}'s edit

{{title}}

{{title}}

{{editor}}'s edit

{{editor}}'s edit

{{title}}

{{editor}}'s edit

{{editor}}'s edit

{{title}}

{{title}}

{{editor}}'s edit

{{editor}}'s edit

{{title}}

{{editor}}'s edit

{{editor}}'s edit

{{title}}

Select a reply

Accumulate setting in EpiNow2 #886

nlinton Dec 10, 2024

Replies: 2 comments · 13 replies

jamesmbaazam Dec 10, 2024 Collaborator

seabbs Dec 11, 2024 Maintainer

jamesmbaazam Dec 11, 2024 Collaborator

seabbs Dec 11, 2024 Maintainer

nlinton Dec 11, 2024 Author

jamesmbaazam Dec 11, 2024 Collaborator

seabbs Dec 12, 2024 Maintainer

nlinton Dec 12, 2024 Author

nlinton Dec 12, 2024 Author

seabbs Dec 13, 2024 Maintainer

nlinton
Dec 10, 2024

Replies: 2 comments 13 replies

jamesmbaazam
Dec 10, 2024
Collaborator

seabbs Dec 11, 2024
Maintainer

jamesmbaazam Dec 11, 2024
Collaborator

seabbs Dec 11, 2024
Maintainer

nlinton
Dec 11, 2024
Author

jamesmbaazam Dec 11, 2024
Collaborator

seabbs Dec 12, 2024
Maintainer

nlinton Dec 12, 2024
Author

nlinton Dec 12, 2024
Author

seabbs Dec 13, 2024
Maintainer