{"id":28702909,"url":"https://github.com/epiforecasts/epinow2","last_synced_at":"2025-06-14T13:05:52.955Z","repository":{"id":40484931,"uuid":"272995211","full_name":"epiforecasts/EpiNow2","owner":"epiforecasts","description":"Estimate Realtime Case Counts and Time-varying Epidemiological Parameters","archived":false,"fork":false,"pushed_at":"2025-06-04T16:50:22.000Z","size":101601,"stargazers_count":129,"open_issues_count":63,"forks_count":36,"subscribers_count":9,"default_branch":"main","last_synced_at":"2025-06-04T17:07:42.753Z","etag":null,"topics":["backcalculation","covid-19","gaussian-processes","open-source","reproduction-number","rstats","stan"],"latest_commit_sha":null,"homepage":"https://epiforecasts.io/EpiNow2/dev/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/epiforecasts.png","metadata":{"files":{"readme":"README.Rmd","changelog":"NEWS.md","contributing":".github/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2020-06-17T14:25:50.000Z","updated_at":"2025-06-04T13:17:22.000Z","dependencies_parsed_at":"2023-09-21T19:52:10.771Z","dependency_job_id":"20e6e1a9-659b-49ed-abe4-5cc084541a55","html_url":"https://github.com/epiforecasts/EpiNow2","commit_stats":{"total_commits":1183,"total_committers":22,"mean_commits":53.77272727272727,"dds":"0.35333896872358406","last_synced_commit":"2cc568ee3511795a1124202cffe5bb87a28d8d80"},"previous_names":[],"tags_count":19,"template":false,"template_full_name":null,"purl":"pkg:github/epiforecasts/EpiNow2","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/epiforecasts%2FEpiNow2","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/epiforecasts%2FEpiNow2/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/epiforecasts%2FEpiNow2/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/epiforecasts%2FEpiNow2/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/epiforecasts","download_url":"https://codeload.github.com/epiforecasts/EpiNow2/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/epiforecasts%2FEpiNow2/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259820812,"owners_count":22916548,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["backcalculation","covid-19","gaussian-processes","open-source","reproduction-number","rstats","stan"],"created_at":"2025-06-14T13:05:51.791Z","updated_at":"2025-06-14T13:05:52.942Z","avatar_url":"https://github.com/epiforecasts.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n```{r, echo = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/\", # nolint\n  eval = TRUE\n)\n```\n\n# EpiNow2: Estimate real-time case counts and time-varying epidemiological parameters \u003ca href=\"https://epiforecasts.io/EpiNow2/\"\u003e\u003cimg src=\"man/figures/logo.png\" align=\"right\" height=\"139\" alt=\"EpiNow2 website\" /\u003e\u003c/a\u003e\n\n[![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html#maturing) [![R-CMD-check](https://github.com/epiforecasts/EpiNow2/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/epiforecasts/EpiNow2/actions/workflows/R-CMD-check.yaml) [![codecov](https://codecov.io/gh/epiforecasts/EpiNow2/branch/main/graph/badge.svg?token=FZWwEMdpq6)](https://app.codecov.io/gh/epiforecasts/EpiNow2) [![](https://cranlogs.r-pkg.org/badges/grand-total/EpiNow2)](https://cran.r-project.org/package=EpiNow2)\n\n[![MIT license](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/epiforecasts/EpiNow2/blob/main/LICENSE.md/)   [![GitHub contributors](https://img.shields.io/github/contributors/epiforecasts/EpiNow2)](https://github.com/epiforecasts/EpiNow2/graphs/contributors)  [![universe](https://epiforecasts.r-universe.dev/badges/EpiNow2)](http://epiforecasts.r-universe.dev/#package:EpiNow2) [![GitHub commits](https://img.shields.io/github/commits-since/epiforecasts/EpiNow2/v1.7.1.svg?color=orange)](https://GitHub.com/epiforecasts/EpiNow2/commit/main/) [![DOI](https://zenodo.org/badge/272995211.svg)](https://zenodo.org/badge/latestdoi/272995211)\n\n## Summary\n\n`{EpiNow2}` estimates the time-varying reproduction number, growth rate, and doubling time using a range of open-source tools ([Abbott et al.](https://doi.org/10.12688/wellcomeopenres.16006.1)), and current best practices ([Gostic et al.](https://doi.org/10.1371/journal.pcbi.1008409)). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is actively supported.\n\nForecasting is also supported for the time-varying reproduction number, infections, and reported cases using the same generative process approach as used for estimation.\n\n\u003cdetails\u003e \u003csummary\u003e More details \u003c/summary\u003e\n\n`{EpiNow2}` estimates the time-varying reproduction number on cases by date of infection (using a similar approach to that implemented in [`{EpiEstim}`](https://github.com/mrc-ide/EpiEstim)). True infections, treated as latent and unobserved, are estimated and then mapped to observed data (for example cases by date of report) via one or more delay distributions (in the examples in the package documentation these are an incubation period and a reporting delay) and a reporting model that can include weekly periodicity. \n\nUncertainty is propagated from all inputs into the final parameter estimates, helping to mitigate spurious findings. This is handled internally. The time-varying reproduction estimates and the uncertain generation time also give time-varying estimates of the rate of growth.\n\n\u003c/details\u003e\n\n\u003cdetails\u003e \u003csummary\u003e Models provided \u003c/summary\u003e\n\n`{EpiNow2}` provides three models:\n\n* `estimate_infections()`: Reconstruct cases by date of infection from reported cases.\n\n* `estimate_secondary()`: Estimate the relationship between primary and secondary observations, for example, deaths (secondary) based on hospital admissions (primary), or bed occupancy (secondary) based on hospital admissions (primary).\n\n* `estimate_truncation()`: Estimate a truncation distribution from multiple snapshots of the same data source over time. For more flexibility, check out the [`{epinowcast}`](https://package.epinowcast.org/) package.\n\n\nThe default model in `estimate_infections()` uses a non-stationary Gaussian process to estimate the time-varying reproduction number and infer infections. Other options, which generally reduce runtimes at the cost of the granularity of estimates or real-time performance, include:\n\n* A stationary Gaussian process (faster to estimate but currently gives reduced performance for real time estimates).\n* User specified breakpoints.\n* A fixed reproduction number.\n* A piecewise constant, combining a fixed reproduction number with breakpoints.\n* A random walk, combining a fixed reproduction number with regularly spaced breakpoints (i.e weekly).\n* A deconvolution/back-calculation method for inferring infections, followed with calculating the time-varying reproduction number.\n* Adjustment for the remaining susceptible population beyond the forecast horizon.\n\nBy default, all these models are fit with [MCMC sampling](https://mc-stan.org/docs/reference-manual/mcmc.html) using the [`rstan`](https://mc-stan.org/users/interfaces/rstan) R package as the backend. Users can, however, switch to use approximate algorithms like [variational inference](https://en.wikipedia.org/wiki/Variational_Bayesian_methods), the [pathfinder](https://mc-stan.org/docs/reference-manual/pathfinder.html) algorithm, or [Laplace approximation](https://mc-stan.org/docs/reference-manual/laplace.html) especially for quick prototyping. The latter two methods are provided through the [`cmdstanr`](https://mc-stan.org/cmdstanr/) R package, so users will have to install that separately.\n\nThe documentation for `estimate_infections` provides examples of the implementation of the different options available. \n\n`{EpiNow2}` is designed to be used via a single function call to two functions:\n\n* `epinow()`: Estimate Rt and cases by date of infection and forecast these infections into the future.\n\n* `regional_epinow()`: Efficiently run `epinow()` across multiple regions in an efficient manner.\n\nThese two functions call `estimate_infections()`, which works to reconstruct cases by date of infection from reported cases.\n\nFor more details on using each function corresponding function documentation.\n\n\u003c/details\u003e\n\n## Installation\n\nInstall the released version of the package:\n\n```{r, eval = FALSE}\ninstall.packages(\"EpiNow2\")\n```\n\nInstall the development version of the package with:\n\n```{r, eval = FALSE}\ninstall.packages(\"EpiNow2\", repos = c(\"https://epiforecasts.r-universe.dev\", getOption(\"repos\")))\n```\n\nAlternatively, install the development version of the package with [pak](https://pak.r-lib.org/)\nas follows (few users should need to do this):\n\n```{r, eval = FALSE}\n# check whether {pak} is installed\nif (!require(\"pak\")) {\n  install.packages(\"pak\")\n}\npak::pkg_install(\"epiforecasts/EpiNow2\")\n```\n\nIf using `pak` fails, try:\n```{r, eval = FALSE}\n# check whether {remotes} is installed\nif (!require(\"remotes\")) {\n  install.packages(\"remotes\")\n}\nremotes::install_github(\"epiforecasts/EpiNow2\")\n```\n\nTo build `{EpiNow2}` from source, users will need to configure their C toolchain. This is because `{EpiNow2}` implements the underlying models in Stan (a statistical modelling programming language), which is built on C++.\n\nEach operating system has a different set up procedure. Windows users need to install an appropriate version of [RTools](https://github.com/stan-dev/rstan/wiki/Configuring-C---Toolchain-for-Windows). Mac users can [follow these steps](https://github.com/stan-dev/rstan/wiki/Configuring-C---Toolchain-for-Mac), and Linux users can use [this guide](https://github.com/stan-dev/rstan/wiki/Configuring-C-Toolchain-for-Linux).\n\n## Resources\n\n\u003cdetails\u003e \u003csummary\u003e Getting Started \u003c/summary\u003e\n\nThe Getting Started vignette (see `vignette(\"EpiNow2\")`)\nis your quickest entry point to the package. It provides a quick run through of\nthe two main functions in the package and how to set up them up. It also\ndiscusses how to summarise and visualise the results after running the models.\n\nMore broadly, users can also learn the details of estimating delay distributions, nowcasting, and forecasting in a structured way through the free and open short-course, [\"Nowcasting and forecasting infectious disease dynamics\"](https://nfidd.github.io/nfidd/), developed by some authors of this package.\n\n\u003c/details\u003e\n\n\u003cdetails\u003e \u003csummary\u003e Package website \u003c/summary\u003e\n\nThe package has two websites: one for\n[the stable release version on CRAN](https://epiforecasts.io/EpiNow2/), and\nanother for [the version in development](https://epiforecasts.io/EpiNow2/dev/).\nThese two provide various resources for learning about the package, including\nthe function reference, details about each model (model definition), workflows\nfor each model (usage), and case studies or literature of applications of\nthe package. However, the development website may contain experimental features\nand information not yet available in the stable release.\n\n\u003c/details\u003e\n\n\u003cdetails\u003e \u003csummary\u003e End-to-end workflows \u003c/summary\u003e\n\nThe workflow vignette (see `vignette(\"estimate_infections_workflow\")`)\nprovides guidance on the end-to-end process of estimating reproduction\nnumbers and performing short-term forecasts for a disease spreading in a\n\n\u003c/details\u003e\n\n\u003cdetails\u003e \u003csummary\u003e Model definitions \u003c/summary\u003e\n\nIn different vignettes we provide the mathematical definition of each model.\nFor example, the model definition vignette for `estimate_infections()` can be\nfound in `vignette(\"estimate_infections\")`.\n\n\u003c/details\u003e\n\n\u003cdetails\u003e \u003csummary\u003e Example implementations \u003c/summary\u003e\n\nA simple example of using the package to estimate a national Rt for Covid-19 can be found [here](https://gist.github.com/seabbs/163d0f195892cde685c70473e1f5e867).\n\n\u003c/details\u003e\n\n## Contributing\n\nWe welcome all contributions. If you have identified an issue with the package,\nyou can file an issue [here](https://github.com/epiforecasts/EpiNow2/issues). We also welcome additions and extensions to the underlying model either in the form of options or improvements. If you wish to contribute in any form, please follow the\n[package contributing guide](https://github.com/epiforecasts/EpiNow2/blob/main/.github/CONTRIBUTING.md).\n\n## Contributors\n\n\n\n\n\n\n\n\n\u003c!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --\u003e\n\u003c!-- prettier-ignore-start --\u003e\n\u003c!-- markdownlint-disable --\u003e\n\nAll contributions to this project are gratefully acknowledged using the [`allcontributors` package](https://github.com/ropensci/allcontributors) following the [allcontributors](https://allcontributors.org) specification. Contributions of any kind are welcome!\n\n### Code\n\n\n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=seabbs\"\u003eseabbs\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=sbfnk\"\u003esbfnk\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=jamesmbaazam\"\u003ejamesmbaazam\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=joeHickson\"\u003ejoeHickson\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=hsbadr\"\u003ehsbadr\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=pitmonticone\"\u003epitmonticone\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=actions-user\"\u003eactions-user\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=ellisp\"\u003eellisp\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=kaitejohnson\"\u003ekaitejohnson\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=jdmunday\"\u003ejdmunday\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=pearsonca\"\u003epearsonca\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=Bisaloo\"\u003eBisaloo\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=JAllen42\"\u003eJAllen42\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=adamkucharski\"\u003eadamkucharski\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=avehtari\"\u003eavehtari\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=andrjohns\"\u003eandrjohns\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=LloydChapman\"\u003eLloydChapman\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=medewitt\"\u003emedewitt\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=nikosbosse\"\u003enikosbosse\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=sophiemeakin\"\u003esophiemeakin\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/commits?author=zsusswein\"\u003ezsusswein\u003c/a\u003e\n\n\n\n### Issue Authors\n\n\n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Araulfernandezn\"\u003eraulfernandezn\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Apcarbo\"\u003epcarbo\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Ajohnaponte\"\u003ejohnaponte\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Asophie-schiller\"\u003esophie-schiller\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Amunozedg\"\u003emunozedg\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Akathsherratt\"\u003ekathsherratt\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Ayungwai\"\u003eyungwai\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Akgostic\"\u003ekgostic\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Afkrauer\"\u003efkrauer\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aphilturk\"\u003ephilturk\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Akrageth\"\u003ekrageth\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Atony352\"\u003etony352\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Ausername-rp\"\u003eusername-rp\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3AHAKGH\"\u003eHAKGH\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3AAndrewRiceMGW\"\u003eAndrewRiceMGW\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Abrynhayder\"\u003ebrynhayder\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3ARichardMN\"\u003eRichardMN\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aandrybicio\"\u003eandrybicio\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Arhamoonga\"\u003erhamoonga\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Afurqan915\"\u003efurqan915\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3AMFZaini1984\"\u003eMFZaini1984\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Afabsig\"\u003efabsig\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aaffans\"\u003eaffans\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3AGauriSaran\"\u003eGauriSaran\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Adavidvilanova\"\u003edavidvilanova\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Ajrcpulliam\"\u003ejrcpulliam\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Adajmcdon\"\u003edajmcdon\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Ajoshwlambert\"\u003ejoshwlambert\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aavallecam\"\u003eavallecam\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aathowes\"\u003eathowes\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Alorenzwalthert\"\u003elorenzwalthert\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Anlinton\"\u003enlinton\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Amartinamcm\"\u003emartinamcm\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aadrian-lison\"\u003eadrian-lison\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Ajonathonmellor\"\u003ejonathonmellor\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3ATimTaylor\"\u003eTimTaylor\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+author%3Aciaramccarthy1\"\u003eciaramccarthy1\u003c/a\u003e\n\n\n\n### Issue Contributors\n\n\n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+commenter%3Ajhellewell14\"\u003ejhellewell14\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+commenter%3Athlytras\"\u003ethlytras\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+commenter%3ALizaHadley\"\u003eLizaHadley\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+commenter%3Antorresd\"\u003entorresd\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+commenter%3ASamuelBrand1\"\u003eSamuelBrand1\u003c/a\u003e, \n\u003ca href=\"https://github.com/epiforecasts/EpiNow2/issues?q=is%3Aissue+commenter%3Amicahwiesner67\"\u003emicahwiesner67\u003c/a\u003e\n\n\n\u003c!-- markdownlint-enable --\u003e\n\u003c!-- prettier-ignore-end --\u003e\n\u003c!-- ALL-CONTRIBUTORS-LIST:END --\u003e\n\n\n\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fepiforecasts%2Fepinow2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fepiforecasts%2Fepinow2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fepiforecasts%2Fepinow2/lists"}