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Merge pull request #110 from epiforecasts/feature-new-title
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Feature: Update title, description, and citation
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@seabbs
seabbs committed Jul 11, 2022
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20 changes: 11 additions & 9 deletions DESCRIPTION
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Package: epinowcast
Title: Hierarchical Nowcasting of Right Censored Epidemiological Counts
Title: Flexible Hierarchical Nowcasting
Version: 0.1.0.1000
Authors@R:
c(person(given = "Sam Abbott",
Expand All @@ -21,14 +21,16 @@ Authors@R:
email = "me.dewitt.jr@gmail.com",
comment = c(ORCID = "0000-0001-8940-1967")))
Description: Tools to enable flexible and efficient hierarchical nowcasting of
right censored epidemiological counts using a semi-mechanistic Bayesian
method with support for both day of reference and day of report effects.
Nowcasting in this context is the estimation of the total notifications
(for example hospitalisations or deaths) that will be reported for a given
date based on those currently reported and the pattern of reporting for
previous days. This can be useful when tracking the spread of infectious
disease in real-time as otherwise changes in trends can be obfuscated by
partial reporting or their detection may be delayed due to the use of simpler methods like truncation.
right-truncated epidemiological time-series using a semi-mechanistic
Bayesian model with support for a range of reporting and generative
processes. Nowcasting, in this context, is gaining situational awareness
using currently available observations and the reporting patterns of
historical observations. This can be useful when tracking the spread of
infectious disease in real-time: without nowcasting, changes in trends can
be obfuscated by partial reporting or their detection may be delayed due to
the use of simpler methods like truncation. While the package has been
designed with epidemiological applications in mind, it could be applied
to any set of right-truncated time-series count data.
License: MIT + file LICENSE
URL: https://epiforecasts.io/epinowcast/,
https://github.com/epiforecasts/epinowcast/
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1 change: 1 addition & 0 deletions NEWS.md
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Expand Up @@ -8,6 +8,7 @@ This is a major release and contains multiple breaking changes. If needing the o

## Package

* Renamed the package and updated the description to give more clarity about the problem space it focusses on. See [#110](https://github.com/epiforecasts/epinowcast/pull/110) by [@seabbs](https://github.com/seabbs).
* A new helper function `enw_delay_metadata()` has been added. This produces metadata about the delay distribution vector that may be helpful in future modelling. This prepares the way for [#4](https://github.com/epiforecasts/epinowcast/issues/4) where this data frame will be combined with the reference metadata in order to build non-parametric hazard reference and delay based models. In addition to adding this function, it has also been added to the output of `enw_preprocess_data()` in order to make the metadata readily available to end-users. See [#80](https://github.com/epiforecasts/epinowcast/pull/80) by [@seabbs](https://github.com/seabbs).
* Two new helper functions `enw_filter_reference_dates()` and `enw_filter_report_dates()` have been added. These replace `enw_retrospective_data()` but allow users to similarly construct retrospective data. Splitting these functions out into components also allows for additional use cases that were not previously possible. Note that by definition it is assumed that a report date for a given reference date must be the equal or greater (i.e a report cannot happen before the event being reported occurs). See [#82](https://github.com/epiforecasts/epinowcast/pull/82) by [@sbfnk](https://github.com/sbfnk) and [@seabbs](https://github.com/seabbs).
* The internal grouping variables have been refactored to reduce the chance of clashes with columns in the data frames supplied by the user. There will also be an error thrown in case of a variable clash, making preprocessing safer. See [#102](https://github.com/epiforecasts/epinowcast/pull/102) by [@adrian-lison](https://github.com/adrian-lison) and [@seabbs](https://github.com/seabbs), which solves [#99](https://github.com/epiforecasts/epinowcast/issues/99).
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2 changes: 1 addition & 1 deletion R/epinowcast.R
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#' @title Nowcast right censored data
#' @title Nowcast using partially observed data
#'
#' @description Provides a user friendly interface around package functionality
#' to produce a nowcast from observed preprocessed data, a reference model, and
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4 changes: 2 additions & 2 deletions README.Rmd
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Expand Up @@ -15,7 +15,7 @@ knitr::opts_chunk$set(
)
```

# Hierarchical nowcasting of right censored epidemiological counts <a href='https://epiforecasts.io/epinowcast'><img src='man/figures/logo.png' align="right" height="139" /></a>
# Flexible hierarchical nowcasting <a href='https://epiforecasts.io/epinowcast'><img src='man/figures/logo.png' align="right" height="139" /></a>

[![Lifecycle:
experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
Expand All @@ -28,7 +28,7 @@ license](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/

[![DOI](https://zenodo.org/badge/422611952.svg)](https://zenodo.org/badge/latestdoi/422611952)

This package contains tools to enable flexible and efficient hierarchical nowcasting of right censored epidemiological counts using a semi-mechanistic Bayesian method with support for both day of reference and day of report effects. Nowcasting in this context is the estimation of the total notifications (for example hospitalisations or deaths) that will be reported for a given date based on those currently reported and the pattern of reporting for previous days. This can be useful when tracking the spread of infectious disease in real-time as otherwise changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation.
Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.

## Installation

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104 changes: 52 additions & 52 deletions README.md
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<!-- README.md is generated from README.Rmd. Please edit that file -->

# Hierarchical nowcasting of right censored epidemiological counts <a href='https://epiforecasts.io/epinowcast'><img src='man/figures/logo.png' align="right" height="139" /></a>
# Flexible hierarchical nowcasting <a href='https://epiforecasts.io/epinowcast'><img src='man/figures/logo.png' align="right" height="139" /></a>

[![Lifecycle:
experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
Expand All @@ -17,17 +17,17 @@ contributors](https://img.shields.io/github/contributors/epiforecasts/epinowcast

[![DOI](https://zenodo.org/badge/422611952.svg)](https://zenodo.org/badge/latestdoi/422611952)

This package contains tools to enable flexible and efficient
hierarchical nowcasting of right censored epidemiological counts using a
semi-mechanistic Bayesian method with support for both day of reference
and day of report effects. Nowcasting in this context is the estimation
of the total notifications (for example hospitalisations or deaths) that
will be reported for a given date based on those currently reported and
the pattern of reporting for previous days. This can be useful when
tracking the spread of infectious disease in real-time as otherwise
changes in trends can be obfuscated by partial reporting or their
detection may be delayed due to the use of simpler methods like
truncation.
Tools to enable flexible and efficient hierarchical nowcasting of
right-truncated epidemiological time-series using a semi-mechanistic Bayesian
model with support for a range of reporting and generative processes.
Nowcasting, in this context, is gaining situational awareness using
currently available observations and the reporting patterns of
historical observations. This can be useful when tracking the spread of
infectious disease in real-time: without nowcasting, changes in trends can be
obfuscated by partial reporting or their detection may be delayed due to
the use of simpler methods like truncation. While the package has been
designed with epidemiological applications in mind, it could be
applied to any set of right-truncated time-series count data.

## Installation

Expand Down Expand Up @@ -215,12 +215,12 @@ nowcast <- epinowcast(pobs,
)
#> Running MCMC with 2 parallel chains, with 2 thread(s) per chain...
#>
#> Chain 1 finished in 71.8 seconds.
#> Chain 2 finished in 92.8 seconds.
#> Chain 2 finished in 50.2 seconds.
#> Chain 1 finished in 51.8 seconds.
#>
#> Both chains finished successfully.
#> Mean chain execution time: 82.3 seconds.
#> Total execution time: 92.9 seconds.
#> Mean chain execution time: 51.0 seconds.
#> Total execution time: 52.0 seconds.
```

### Results
Expand All @@ -237,11 +237,11 @@ nowcast
#> metadelay time snapshots by groups max_delay max_date
#> 1: <data.table[40x4]> 41 41 1 40 2021-08-22
#> fit data fit_args samples max_rhat
#> 1: <CmdStanMCMC[32]> <list[41]> <list[8]> 1000 1.03
#> 1: <CmdStanMCMC[32]> <list[41]> <list[8]> 1000 1.02
#> divergent_transitions per_divergent_transitions max_treedepth
#> 1: 0 0 8
#> no_at_max_treedepth per_at_max_treedepth run_time
#> 1: 271 0.271 92.9
#> 1: 10 0.01 52
```

Summarise the nowcast for the latest snapshot of data.
Expand All @@ -263,26 +263,26 @@ nowcast |>
#> 10: 2021-07-23 2021-08-22 1 86 DE 00+ 86
#> cum_prop_reported delay prop_reported mean median sd mad q5
#> 1: 1 39 0 72.000 72 0.0000000 0.0000 72
#> 2: 1 38 0 69.044 69 0.2147326 0.0000 69
#> 3: 1 37 0 47.081 47 0.3074631 0.0000 47
#> 4: 1 36 0 65.194 65 0.4388127 0.0000 65
#> 5: 1 35 0 50.272 50 0.5350722 0.0000 50
#> 6: 1 34 0 36.220 36 0.4731002 0.0000 36
#> 7: 1 33 0 94.457 94 0.6990276 0.0000 94
#> 8: 1 32 0 91.705 91 0.9158678 0.0000 91
#> 9: 1 31 0 100.101 100 1.1207386 1.4826 99
#> 10: 1 30 0 87.198 87 1.1866778 1.4826 86
#> q95 rhat ess_bulk ess_tail
#> 1: 72.00 NA NA NA
#> 2: 69.00 1.0001418 975.6787 970.3968
#> 3: 48.00 0.9990071 900.4571 882.7382
#> 4: 66.00 0.9994697 900.4178 758.2049
#> 5: 51.00 1.0017612 707.0578 679.5653
#> 6: 37.00 0.9997234 969.2497 963.5052
#> 7: 96.00 0.9982308 950.4162 859.6649
#> 8: 93.05 1.0002517 1004.3908 1008.6991
#> 9: 102.00 1.0020085 948.5313 936.2672
#> 10: 89.00 1.0000114 1041.1571 858.5731
#> 2: 1 38 0 69.046 69 0.2189336 0.0000 69
#> 3: 1 37 0 47.096 47 0.3144565 0.0000 47
#> 4: 1 36 0 65.176 65 0.4552266 0.0000 65
#> 5: 1 35 0 50.271 50 0.5251998 0.0000 50
#> 6: 1 34 0 36.242 36 0.5096035 0.0000 36
#> 7: 1 33 0 94.457 94 0.6637707 0.0000 94
#> 8: 1 32 0 91.738 92 0.8945145 1.4826 91
#> 9: 1 31 0 100.032 100 1.0545559 1.4826 99
#> 10: 1 30 0 87.159 87 1.1344629 1.4826 86
#> q95 rhat ess_bulk ess_tail
#> 1: 72 NA NA NA
#> 2: 69 1.0007765 1006.9282 1002.6983
#> 3: 48 1.0000955 786.6752 783.7836
#> 4: 66 0.9993755 940.8320 855.6696
#> 5: 51 1.0023047 1000.5282 955.8951
#> 6: 37 1.0006436 989.9089 867.0135
#> 7: 96 0.9982502 1042.2918 882.8528
#> 8: 94 1.0013474 919.6210 759.2589
#> 9: 102 0.9993403 983.8782 930.9138
#> 10: 89 1.0013534 861.8767 886.7324
```

Plot the summarised nowcast against currently observed data (or
Expand Down Expand Up @@ -331,17 +331,17 @@ samples[, (cols) := lapply(.SD, frollsum, n = 7),
#> 33999: 2021-08-22 2021-08-22 1 45 DE 00+ 1093
#> 34000: 2021-08-22 2021-08-22 1 45 DE 00+ 1093
#> cum_prop_reported delay prop_reported .chain .iteration .draw sample
#> 1: 1 33 0 1 1 1 433
#> 2: 1 33 0 1 2 2 433
#> 3: 1 33 0 1 3 3 433
#> 4: 1 33 0 1 4 4 435
#> 5: 1 33 0 1 5 5 437
#> 1: 1 33 0 1 1 1 435
#> 2: 1 33 0 1 2 2 435
#> 3: 1 33 0 1 3 3 438
#> 4: 1 33 0 1 4 4 436
#> 5: 1 33 0 1 5 5 433
#> ---
#> 33996: 1 0 1 2 496 996 2233
#> 33997: 1 0 1 2 497 997 2024
#> 33998: 1 0 1 2 498 998 2283
#> 33999: 1 0 1 2 499 999 2109
#> 34000: 1 0 1 2 500 1000 1806
#> 33996: 1 0 1 2 496 996 2107
#> 33997: 1 0 1 2 497 997 2374
#> 33998: 1 0 1 2 498 998 2089
#> 33999: 1 0 1 2 499 999 1975
#> 34000: 1 0 1 2 500 1000 2044
latest_germany_hosp_7day <- copy(latest_germany_hosp)[
,
confirm := frollsum(confirm, n = 7)
Expand Down Expand Up @@ -372,14 +372,14 @@ following,
#>
#> To cite epinowcast in publications use:
#>
#> Sam Abbott (2021). epinowcast: Hierarchical nowcasting of right
#> censored epidemiological counts, DOI: 10.5281/zenodo.5637165
#> Sam Abbott, Adrian Lison, and Sebastian Funk (2021). epinowcast: Flexible
#> hierarchical nowcasting, DOI: 10.5281/zenodo.5637165
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Article{,
#> title = {epinowcast: Hierarchical nowcasting of right censored epidemiological counts},
#> author = {Sam Abbott},
#> title = {epinowcast: Flexible hierarchical nowcasting},
#> author = {Sam Abbott and Adrian Lison and Sebastian Funk},
#> journal = {Zenodo},
#> year = {2021},
#> doi = {10.5281/zenodo.5637165},
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2 changes: 1 addition & 1 deletion _pkgdown.yml
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Expand Up @@ -10,7 +10,7 @@ template:
opengraph:
image:
src: man/figures/README-nowcast-1.png
alt: An R package for hierarchical nowcasting of right censored epidemiological counts
alt: An R package for flexible hierarchical nowcasting
twitter:
creator: "@seabbs"
card: summary_large_image
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9 changes: 5 additions & 4 deletions inst/CITATION
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citHeader("To cite epinowcast in publications use:")

citEntry(entry = "Article",
title = "epinowcast: Hierarchical nowcasting of right censored epidemiological counts", # nolint
author = personList(as.person("Sam Abbott")),
title = "epinowcast: Flexible hierarchical nowcasting", # nolint
author = personList(as.person("Sam Abbott"), as.person("Adrian Lison"),
as.person("Sebastian Funk")),
journal = "Zenodo",
year = "2021",
volume = "",
Expand All @@ -11,7 +12,7 @@ citEntry(entry = "Article",
doi = "10.5281/zenodo.5637165",

textVersion =
paste("Sam Abbott (2021).",
"epinowcast: Hierarchical nowcasting of right censored epidemiological counts, ", # nolint
paste("Sam Abbott, Adrian Lison, and Sebastian Funk (2021).",
"epinowcast: Flexible hierarchical nowcasting, ", # nolint
"DOI: 10.5281/zenodo.5637165")
)
4 changes: 2 additions & 2 deletions man/epinowcast-package.Rd
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