{ "_id": "6a1f1826b401979e7341ec75", "Package": "REffectivePred", "Type": "Package", "Title": "Pandemic Prediction Model in an SIRS Framework", "Version": "1.0.1", "Authors@R": "c(person(given = \"Razvan\", \nfamily = \"Romanescu\",\nrole = c(\"aut\", \"cre\"),\nemail = \"razvan_romanescu@hotmail.com\"),\nperson(given = \"Songdi\",\nfamily = \"Hu\",\nrole = \"aut\"),\nperson(given = \"Md Ashiqul\",\nfamily = \"Haque\",\nrole = \"aut\"),\nperson(given = \"Olivier\",\nfamily = \"Tremblay-Savard\",\nrole = \"aut\"))", "Description": "A suite of methods to fit and predict case count data\nusing a compartmental SIRS (Susceptible – Infectious –\nRecovered – Susceptible) model, based on an assumed\nspecification of the effective reproduction number. The\nsignificance of this approach is that it relates epidemic\nprogression to the average number of contacts of infected\nindividuals, which decays as a function of the total\nsusceptible fraction remaining in the population. The main\nfunctions are pred.curve(), which computes the epidemic curve\nfor a set of parameters, and estimate.mle(), which finds the\nbest fitting curve to observed data. The easiest way to pass\narguments to the functions is via a config file, which contains\ninput settings required for prediction, and the package offers\ntwo methods, navigate_to_config() which points the user to the\nconfiguration file, and re_predict() for starting the\nfit-predict process. The main model was published in Razvan G.\nRomanescu et al. .", "License": "GPL (>= 2)", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "Collate": "'prediction_model.v16.R' 'executions.v16.R'", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-17 05:47:16 UTC", "User": "root" }, "Author": "Razvan Romanescu [aut, cre], Songdi Hu [aut], Md Ashiqul Haque\n[aut], Olivier Tremblay-Savard [aut]", "Maintainer": "Razvan Romanescu ", "Repository": "https://rootofunity.r-universe.dev", "Date/Publication": "2024-11-12 09:50:05 UTC", "RemoteUrl": "https://github.com/cran/REffectivePred", "RemoteRef": "HEAD", "RemoteSha": "3fa466aeb3e10e28f28775dbd08f7aacdb5d14b9", "MD5sum": "60f14c91b8faa9cc8c943942a43cfc56", "_user": "rootofunity", "_type": "src", "_file": "REffectivePred_1.0.1.tar.gz", "_fileid": "4d219aa4ce6fbf7b8554956ec6dc81cf7138d14acd54daf900bb5ce9cac144c0", "_filesize": 229228, "_sha256": "4d219aa4ce6fbf7b8554956ec6dc81cf7138d14acd54daf900bb5ce9cac144c0", "_created": 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true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 1, "_contributors": [ { "user": "rootofunity", "count": 1, "uuid": 85967756 } ], "_userbio": { "uuid": 85967756, "type": "user", "name": "rootOfUnity" }, "_downloads": { "count": 568, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/REffectivePred" }, "_searchresults": 6, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/REffectivePred.html", "manual.pdf" ], "_realowner": "rootofunity", "_cranurl": false, "_releases": [ { "version": "1.0.0", "date": "2024-02-02" }, { "version": "1.0.1", "date": "2024-11-14" } ], "_exports": [ "c_helper", "ci.curve", "estimate.mle", "find_ends", "find_starts", "load_config", "log_lklh", "navigate_to_config", "plot_outputs", "pred.curve", "ranges_to_waves", "re_predict", "rt_empirical", "waves_1d_list" ], "_help": [ { "page": "c_helper", "title": "Contact rate function.", 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