{ "_id": "6a49737cf408bf5a1e5fdc88", "Package": "serosv", "Type": "Package", "Title": "Model Infectious Disease Parameters from Serosurveys", "Version": "1.2.0.9000", "Authors@R": "c(\nperson(\"Anh\", \"Phan Truong Quynh\", email = \"anhptq@oucru.org\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0009-0000-2129-435X\")),\nperson(\"Nguyen\", \"Pham Nguyen The\", email = \"nguyenpnt@oucru.org\", role = c(\"aut\"), comment = c(ORCID = \"0000-0002-0356-2776\")),\nperson(\"Long\", \"Bui Thanh\", role = \"aut\"),\nperson(\"Tuyen\", \"Huynh\", email = \"tuyenhn@oucru.org\", role = \"aut\"),\nperson(\"Thinh\", \"Ong\", email = \"thinhop@oucru.org\", role = \"aut\", comment = c(ORCID = \"0000-0001-6772-9291\")),\nperson(\"Marc\", \"Choisy\", email = \"mchoisy@oucru.org\", role = \"aut\", comment = c(ORCID = \"0000-0002-5187-6390\"))\n)", "Description": "An easy-to-use and efficient tool to estimate infectious\ndiseases parameters using serological data. Implemented models\ninclude SIR models (basic_sir_model(), static_sir_model(),\nmseir_model(), sir_subpops_model()), parametric models\n(polynomial_model(), fp_model()), nonparametric models\n(lp_model()), semiparametric models\n(penalized_splines_model()), hierarchical models\n(hierarchical_bayesian_model()). The package is based on the\nbook \"Modeling Infectious Disease Parameters Based on\nSerological and Social Contact Data: A Modern Statistical\nPerspective\" (Hens, Niel & Shkedy, Ziv & Aerts, Marc & Faes,\nChristel & Damme, Pierre & Beutels, Philippe., 2013)\n.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "Collate": "'data.R' 'fractional_polynomial_models.R'\n'polynomial_models.R' 'utils.R' 'compare_models.R'\n'correct_prevalence.R' 'weibull_model.R' 'farrington_model.R'\n'nonparametric.R' 'semiparametric_models.R' 'mixture_model.R'\n'hierarchical_bayesian_model.R' 'to_titer.R' 'serosv.R'\n'stanmodels.R' 'plots.R' 'compute_ci.R' 'age_time_model.R'\n'predict.R' 'print.R'", "Config/testthat/edition": "3", "URL": "https://oucru-modelling.github.io/serosv/,\nhttps://github.com/OUCRU-Modelling/serosv", "VignetteBuilder": "knitr", "Biarch": "true", "SystemRequirements": "GNU make", "BugReports": 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"add_thresholds" ] }, { "page": "age_time_model", "title": "Age-time varying seroprevalence", "topics": [ "age_time_model" ] }, { "page": "compare_models", "title": "Generate table of metrics for model comparison", "topics": [ "compare_models" ] }, { "page": "compute_ci.age_time_model", "title": "Compute confidence interval for time age model", "topics": [ "compute_ci.age_time_model" ] }, { "page": "compute_ci.default", "title": "Compute confidence interval for a model of serosv", "topics": [ "compute_ci.default" ] }, { "page": "compute_ci.fp_model", "title": "Compute confidence interval for fractional polynomial model", "topics": [ "compute_ci.fp_model" ] }, { "page": "compute_ci.hierarchical_bayesian_model", "title": "Compute 95% credible interval for hierarchical Bayesian model", "topics": [ "compute_ci.hierarchical_bayesian_model" ] }, { "page": "compute_ci.lp_model", "title": "Compute confidence interval for local polynomial model", "topics": [ "compute_ci.lp_model" ] }, { "page": "compute_ci.mixture_model", "title": "Compute confidence interval for mixture model", "topics": [ "compute_ci.mixture_model" ] }, { "page": "compute_ci.penalized_spline_model", "title": "Compute confidence interval for penalized_spline_model", "topics": [ "compute_ci.penalized_spline_model" ] }, { "page": "compute_ci.weibull_model", "title": "Compute confidence interval for Weibull model", "topics": [ "compute_ci.weibull_model" ] }, { "page": "correct_prevalence", "title": "Estimate the true sero prevalence using Frequentist/Bayesian estimation", "topics": [ "correct_prevalence" ] }, { "page": "est_foi", "title": "Estimate force of infection", "topics": [ "est_foi" ] }, { "page": "estimate_from_mixture", "title": "Estimate seroprevalence and FOI from a fixed mixture model", "topics": [ "estimate_from_mixture" ] }, { "page": "farrington_model", "title": "The Farrington (1990) model.", "topics": [ "farrington_model" ] }, { "page": "find_best_fp_powers", "title": "Returns the powers of the fractional polynomial model which has the lowest deviance score.", "topics": [ "find_best_fp_powers" ] }, { "page": "fp_model", "title": "A fractional polynomial model.", "topics": [ "fp_model" ] }, { "page": "hav_be_1993_1994", "title": "Hepatitis A serological data from Belgium in 1993 and 1994 (aggregated)", "topics": [ "hav_be_1993_1994" ] }, { "page": "hav_be_2002", "title": "Hepatitis A serological data from Belgium in 2002 (line listing)", "topics": [ "hav_be_2002" ] }, { "page": "hav_bg_1964", "title": "Hepatitis A serological data from Bulgaria in 1964 (aggregated)", "topics": [ "hav_bg_1964" ] }, { "page": "hbv_ru_1999", "title": "Hepatitis B serological data from Russia in 1999 (aggregated)", "topics": [ "hbv_ru_1999" ] }, { "page": "hcv_be_2006", "title": "Hepatitis C serological data from Belgium in 2006 (line listing)", "topics": [ "hcv_be_2006" ] }, { "page": "hierarchical_bayesian_model", "title": "Hierarchical Bayesian Model", "topics": [ "hierarchical_bayesian_model" ] }, { "page": "lp_model", "title": "A local polynomial model.", "topics": [ "lp_model" ] }, { "page": "mixture_model", "title": "Fit a mixture model to classify serostatus", "topics": [ "mixture_model" ] }, { "page": "mumps_uk_1986_1987", "title": "Mumps serological data from the UK in 1986 and 1987 (aggregated)", "topics": [ "mumps_uk_1986_1987" ] }, { "page": "parvob19_be_2001_2003", "title": "Parvo B19 serological data from Belgium from 2001-2003 (line listing)", "topics": [ "parvob19_be_2001_2003" ] }, { "page": "parvob19_ew_1996", "title": "Parvo B19 serological data from England and Wales in 1996 (line listing)", "topics": [ "parvob19_ew_1996" ] }, { "page": "parvob19_fi_1997_1998", "title": "Parvo B19 serological data from Finland from 1997-1998 (line listing)", "topics": [ "parvob19_fi_1997_1998" ] }, { "page": "parvob19_it_2003_2004", "title": "Parvo B19 serological data from Italy from 2003-2004 (line listing)", "topics": [ "parvob19_it_2003_2004" ] }, { "page": "parvob19_pl_1995_2004", "title": "Parvo B19 serological data from Poland from 1995-2004 (line listing)", "topics": [ "parvob19_pl_1995_2004" ] }, { "page": "pava", "title": "Monotonize seroprevalence", "topics": [ "pava" ] }, { "page": "penalized_spline_model", "title": "Penalized Spline model", "topics": [ "penalized_spline_model" ] }, { "page": "plot_corrected_prev", "title": "Plot output for corrected_prevalence", "topics": [ "plot_corrected_prev" ] }, { "page": "plot_gcv", "title": "Plotting GCV values with respect to different nn-s and h-s parameters.", "topics": [ "plot_gcv" ] }, { "page": "plot_standard_curve", "title": "Visualize standard curves for each plate", "topics": [ "plot_standard_curve" ] }, { "page": "plot_titer_qc", "title": "Quality control plot", "topics": [ "plot_titer_qc" ] }, { "page": "plot.age_time_model", "title": "Plot output for age_time_model", "topics": [ "plot.age_time_model" ] }, { "page": "plot.estimate_from_mixture", "title": "plot() overloading for result of estimate_from_mixture", "topics": [ "plot.estimate_from_mixture" ] }, { "page": "plot.farrington_model", "title": "plot() overloading for Farrington model", "topics": [ "plot.farrington_model" ] }, { "page": "plot.fp_model", "title": "plot() overloading for fractional polynomial model", "topics": [ "plot.fp_model" ] }, { "page": "plot.hierarchical_bayesian_model", "title": "plot() overloading for hierarchical_bayesian_model", "topics": [ "plot.hierarchical_bayesian_model" ] }, { "page": "plot.lp_model", "title": "plot() overloading for local polynomial model", "topics": [ "plot.lp_model" ] }, { "page": "plot.mixture_model", "title": "plot() overloading for mixture model", "topics": [ "plot.mixture_model" ] }, { "page": "plot.penalized_spline_model", "title": "plot() overloading for penalized spline", "topics": [ "plot.penalized_spline_model" ] }, { "page": "plot.polynomial_model", "title": "plot() overloading for 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