Package index • epireview

All functions

append_new_entry_to_table(): Append new entry to article, outbreak, model, or parameter table

article_column_type(): Define the column types for the article data frame

assign_qa_score(): Assign quality assessment score to each article

check_column_types(): Checks that the column types of the input csv matches the column types expected by epireview.

check_df_for_meta(): Sanity checks before meta-analysis

check_ulim(): Check upper limit of parameter values

color_palette(): Define a consistent color palette for use in figures. Palettes are currently defined for parameters and countries. Any other variable will return NULL

country_palette(): country_palette Function

create_new_article_entry(): Create new article entry

create_new_model_entry(): Create new model entry

create_new_outbreak_entry(): Create new outbreak entry

create_new_parameter_entry(): Create new parameter entry

custom_palette(): Create a custom color palette.

data_outbreak_table(): Process data for outbreak table

data_param_table(): Process data for delay table

date_start(): create a date

delay_table(): Create table for human delay parameters

delays_to_days(): This function converts delays in different units (hours, weeks, months) to days. It checks if all delays are in days and warns the user if not. It then converts hours to days by dividing by 24, weeks to days by multiplying by 7, and months to days by multiplying by 30.

filter_cols(): Filter columns of a data frame based on specified conditions.

filter_df_for_metamean(): Prepare parameter dataframe for meta analysis of means

filter_df_for_metaprop(): Prepare parameter dataframe for meta analysis of proportions

forest_plot(): Basic forest plot

forest_plot_delay_int(): Create forest plot for human delays

forest_plot_doubling_time(): Forest plot for doubling time

forest_plot_incubation_period(): Create forest plot for incubation period

forest_plot_infectious_period(): Create forest plot for infectious period

forest_plot_r0(): forest_plot_r0 function

forest_plot_rt(): Generate a forest plot for effective reproduction number (Rt)

forest_plot_serial_interval(): Create forest plot for serial interval

get_key_columns(): Subset the epidemiological parameter columns by parameter type

get_parameter(): retrieve all parameters of specified type or class

get_incubation_period() get_serial_interval() get_generation_time() get_delays() get_cfr() get_risk_factors() get_genomic() get_reproduction_number() get_seroprevalence() get_doubling_time() get_attack_rate() get_growth_rate() get_overdispersion() get_relative_contribution(): Retrieve all incubation period parameters for a given pathogen

get_table_field_options(): Utility to obtain available fields in a specified table

invert_inverse_params()

Inverts the values of selected parameters in a data frame. Sometimes parameters are reported in inverse form (e.g., a delay might be reported as per day instead of days). Here we carry out a very simple transformation to convert these to the correct form by inverting the parameter value and the uncertainty bounds. This may not be appropriate in all cases, and must be checked on a case-by-case basis. This function takes a data frame as input and inverts the values of selected parameters. The selected parameters are identified by the column 'inverse_param'. The function performs the following operations:

Inverts the parameter values of the selected parameters.
Swaps the upper and lower bounds of the selected parameters.
Inverts the uncertainty values of the selected parameters.
Updates the logical vector to indicate that the parameters are no longer inverted.
Does not change the unit of the parameters, as it remains the same as the original parameter.

load_epidata(): Retrieve pathogen-specific data

load_epidata_raw(): Loads raw data for a particular pathogen

make_unique_id(): Ensure that each article gets a unique id across all tables

marburg_article: Data on the articles identified and included in the systematic review of articles related to Marburg virus disease.

marburg_dropdown_models: Dropdown menu options for model extractions in the systematic review of articles related to Marburg virus disease (MVD).

marburg_dropdown_outbreaks: Dropdown menu options for outbreak extractions in the systematic review of articles related to Marburg virus disease (MVD).

marburg_dropdown_parameters: Dropdown menu options for parameter extractions in the systematic review of articles related to Marburg virus disease (MVD).

marburg_model: Data on the models identified in the systematic review of articles related to Marburg virus disease.

marburg_outbreak: Data on the outbreaks identified in the systematic review of articles related to Marburg virus disease.

marburg_parameter: Data on the parameters identified in the systematic review of articles related to Marburg virus disease.

mark_multiple_estimates(): Distinguish multiple estimates from the same study

model_column_type(): model_column_type

outbreak_column_type(): outbreak_column_type

outbreak_table(): Create table with all outbreak data for a particular pathogen

param_pm_uncertainty(): Update parameter uncertainty columns in a data frame

parameter_column_type(): parameter_column_type

parameter_palette(): Define a consistent color palette for use in figures

pretty_article_label(): Make pretty labels for articles

priority_pathogens(): priority_pathogens

qa_questions(): Quality assessment questionnaire This function returns the list of 7 questions used to assess quality of articles.

quality_assessment_plots(): Plots for the quality assessment (QA) of the included studies

reorder_studies(): Reorder articles based on parameter value

reparam_gamma(): Reparameterize Gamma Distribution

risk_table(): Create risk table

sero_table(): Create seroprevalence table

shape_palette(): shape_palette function

short_parameter_type(): Short labels parameters for use in figures

theme_epireview(): Plotting theme for epireview A standard theme for figures in epireview.

update_article_info(): Include key article information when DOI is missing

value_type_palette(): Define a consistent shape palette for use in forest plots