README.md

In UBC-MDS/rbccovideda: EDA Analysis for BC COVID19 data

rbccovideda

Authors: Lianna Hovhannisyan, John Lee, Vadim Taskaev, Vanessa Yuen

The British Columbia Center for Disease Control (BCCDC) manages a range of provincial programs and clinics that contribute to public health and help control the spread of disease in BC. It administers and distributes the latest daily data on COVID-19 in British Columbia, which it provides in csv format along case-, lab- and regional-specific features as well as in comprehensive ArcGIS format via the COVID-19 webpage (under “Download the data”).

rbccovideeda leverages daily case-specific COVID-19 data, allowing users to conveniently download the latest case data, and - per specified date range interval - compute several key statistics, visualize time series progression along age-related and regional parameters, and generate exploratory data analysis in the form of histogram figures supporting on-demand analysis. COVID-19 case detail parameters extracted using this package:

• Reported_Date (in YYYY-MM-DD format)
• HA (provincial health region, e.g., “Vancouver Coast Health”)
• Sex (M or F)
• Age_Group (reported along 10-yr age group bins, e.g., “60-69”)
• Classification_Reported (diagnosis origin, e.g., “Lab-diagnosed”)

Installation

You can install the development version of rbccovideda from GitHub with:

# install.packages("devtools")
devtools::install_github("UBC-MDS/rbccovideda")

Package Functions

• get_data()

  • This function downloads the latest detailed daily case-specific COVID-19 from BCCDC’s dedicated COVID-19 homepage. It returns a dataframe containing the extracted raw data.

• show_summary_stat()

  • This function computes summary statistics from the available case-specific parameters, such as age-related and regional aggregate metrics. It returns a dataframe listing key identified summary statistics specified per the time interval queried.

• plot_line_by_date()

  • This function returns a line chart plot of daily case counts, based on parameters and grouping selected by the user, per the time interval queried.

• plot_hist_by_cond()

  • This function returns a histogram plot based on parameters and grouping selected by the user, per the time interval queried, allowing for on-demand exploratory data analysis.

Usage

Details documentation can be found on our Github page: https://ubc-mds.github.io/rbccovideda/

rbccovideda can be used to download and compute summary statistics, generate exploratory data analysis histogram plots, and plot time series chart data as follows:

## load library
library(rbccovideda)
library(dplyr, warn.conflicts = FALSE)

To download and save data from BCCDC, use get_data()

all_data <- get_data()
head(all_data)
#> # A tibble: 6 x 5
#>   Reported_Date HA                Sex   Age_Group Classification_Reported
#>   <date>        <chr>             <chr> <chr>     <chr>                  
#> 1 2020-01-29    Out of Canada     M     40-49     Lab-diagnosed          
#> 2 2020-02-06    Vancouver Coastal F     50-59     Lab-diagnosed          
#> 3 2020-02-10    Out of Canada     F     20-29     Lab-diagnosed          
#> 4 2020-02-10    Out of Canada     M     30-39     Lab-diagnosed          
#> 5 2020-02-18    Interior          F     30-39     Lab-diagnosed          
#> 6 2020-02-24    Fraser            M     40-49     Lab-diagnosed

To generate summary statistics, call show_summary_stat(startDate, endDate)

summary <- show_summary_stat("2022-01-01", "2022-01-31")
# to show the 15-columns tibble in a nice way
glimpse(summary)
#> Rows: 1
#> Columns: 15
#> $ total_cases_count        <int> 327625
#> $ latest_date              <date> 2022-02-01
#> $ latest_daily_cases_count <int> 1695
#> $ max_date                 <date> 2021-12-31
#> $ max_daily_cases_count    <int> 4078
#> $ min_date                 <date> 2020-01-29
#> $ min_daily_cases_count    <int> 1
#> $ max_age_group            <chr> "20-29"
#> $ max_age_group_count      <int> 67347
#> $ min_age_group            <chr> "Unknown"
#> $ min_age_group_count      <int> 90
#> $ max_region               <chr> "Fraser"
#> $ max_region_count         <int> 152269
#> $ min_region               <chr> "Out of Canada"
#> $ min_region_count         <int> 353

To plot a histogram by Age, use plot_hist_by_cond("2021-01-01", "2021-12-31", "Age")

plot_hist_by_cond("2021-01-01", "2021-01-30", "Age")

To plot a time-series line chart, use plot_line_by_date(startDate, endDate)

plot_line_by_date("2021-01-01", "2021-01-30")

Role within R Ecosystem

Given the relatively adequate accessibility of latest aggregate COVID-19 data combined with its persistent impact on socio-economics since early 2020, there are some 40 related packages found in CRAN at time as of January 2022. Examples of API wrapper packages that retrieve COVID-19 data include canadacovid and covidregionaldata, while others provide functions to retrieve data, display summary statistics and generate plots, such as nCov2019 and covid19.analytic. In contrast to these existing packages, rbccovideda provides a simple user interface that focuses on the localized provincial context of British Columbia, utilizing features specific to BCCDC’s data administration conventions for generating a quick overview and on-demand analysis of trends and statistics pertaining to age-related and regional case characteristics.

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

Contributors

Group 25 Contributors:

• Lianna Hovhannisyan: @liannah
• John Lee: @johnwslee
• Vadim Taskaev: @vtaskaev1
• Vanessa Yuen: @imtvwy

License

The rbccovideda project was created by DSCI 524 (Collaborative Software Development) Group 25 within the Master of Data Science program at the University of British Columbia (2021-2022). It is licensed under the terms of the MIT license.

Credits

R Packages, DSCI 524 Course Material (UBC MDS)

UBC-MDS/rbccovideda documentation built on Feb. 5, 2022, 8:13 a.m.