The jpinfect package provides tools for acquiring and
processing notifiable infectious disease data in Japan. The package
includes built-in datasets and functions to download, read and
manipulate data from the Japan Institute for Health Security (JIHS). It
also provides functions to merge datasets, transform data formats and
check data sources.
This package is designed to assist researchers, epidemiologists, public health officials and developers in accessing, cleaning, and manipulating data for epidemiological analysis. The package is particularly useful for those working with infectious disease data in Japan, as it provides a streamlined process for obtaining and processing data from the JIHS.
The jpinfect package depends on the following R
packages:
dplyr: for data manipulation
future: for parallel processing
future.apply: for parallel processing
httr: for HTTP requests
magrittr: for piping
readr: for reading CSV files
readxl: for reading Excel files
stats: for statistical functions
stringi: for string manipulation
stringr: for string manipulation
tidyr: for data tidying
tidyselect: for data selection
utils: for utility functions
The jpinfect package can be installed from GitHub using
the remotes package. To
install the package, run the following command in your R console:
# install.packages("jpinfect")
if(!require("remotes")) install.packages("remotes")
remotes::install_github("TomonoriHoshi/jpinfect")Load the package after installation:
The jpinfect package includes three built-in datasets
that can be used to start immediate data analysis. These datasets
are:
sex_prefecture: Confirmed weekly case reports on the
sex distribution of reported cases by prefecture from 1999 to
2022.
place_prefecture: Confirmed weekly case reports
about the place of infection by prefecture between 2001 and
2022.
bullet: Provisional weekly case reported by
prefecture from 2022 to the current latest reports.
These datasets are provided in a tidy format, making them easy to
work with using the dplyr and tidyr
packages.
str(sex_prefecture)
#> tibble [61,920 × 319] (S3: tbl_df/tbl/data.frame)
#> $ prefecture : chr [1:61920] "Total" "Hokkaido" "Aomori" "Iwate" ...
#> $ year : int [1:61920] 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 ...
#> $ week : int [1:61920] 14 14 14 14 14 14 14 14 14 14 ...
#> $ date : Date[1:61920], format: "1999-04-11" "1999-04-11" ...
#> $ Ebola hemorrhagic fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Ebola hemorrhagic fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Ebola hemorrhagic fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (total) : int [1:61920] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (female) : int [1:61920] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (total) : int [1:61920] 21 1 0 0 0 0 0 1 0 0 ...
#> $ Shigellosis (male) : int [1:61920] 9 1 0 0 0 0 0 1 0 0 ...
#> $ Shigellosis (female) : int [1:61920] 12 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (total) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (male) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (total) : int [1:61920] 5 1 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (male) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (female) : int [1:61920] 4 1 0 0 0 0 0 0 0 0 ...
#> $ Acute poliomyelitis (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute poliomyelitis (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute poliomyelitis (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (total) : int [1:61920] 20 0 0 2 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (male) : int [1:61920] 12 0 0 2 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (female) : int [1:61920] 8 0 0 0 0 0 0 0 0 0 ...
#> $ Amebiasis (total) : int [1:61920] 9 1 0 0 0 0 0 0 1 0 ...
#> $ Amebiasis (male) : int [1:61920] 9 1 0 0 0 0 0 0 1 0 ...
#> $ Amebiasis (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (total) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (female) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute viral hepatitis (total) : int [1:61920] 52 1 0 1 2 0 0 0 2 0 ...
#> $ Acute viral hepatitis (male) : int [1:61920] 28 1 0 1 1 0 0 0 1 0 ...
#> $ Acute viral hepatitis (female) : int [1:61920] 24 0 0 0 1 0 0 0 1 0 ...
#> $ Q fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (total) : int [1:61920] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (female) : int [1:61920] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (total) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (male) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ AIDS (total) : int [1:61920] 18 0 0 0 0 0 0 0 0 0 ...
#> $ AIDS (male) : int [1:61920] 15 0 0 0 0 0 0 0 0 0 ...
#> $ AIDS (female) : int [1:61920] 3 0 0 0 0 0 0 0 0 0 ...
#> $ Coccidioidomycosis (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Coccidioidomycosis (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Coccidioidomycosis (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Giardiasis (total) : int [1:61920] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Giardiasis (male) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Giardiasis (female) : int [1:61920] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Hemorrhagic fever with renal syndrome (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hemorrhagic fever with renal syndrome (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hemorrhagic fever with renal syndrome (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Meningococcal meningitis (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Meningococcal meningitis (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Meningococcal meningitis (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Congenital rubella syndrome (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Congenital rubella syndrome (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Congenital rubella syndrome (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Anthrax (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Anthrax (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Anthrax (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Tsutsugamushi disease (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Tsutsugamushi disease (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Tsutsugamushi disease (female) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Dengue fever (total) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Dengue fever (male) : int [1:61920] 0 0 0 0 0 0 0 0 0 0 ...
#> [list output truncated]str(place_prefecture)
#> tibble [57,552 × 420] (S3: tbl_df/tbl/data.frame)
#> $ prefecture : chr [1:57552] "Total" "Hokkaido" "Aomori" "Iwate" ...
#> $ year : int [1:57552] 2001 2001 2001 2001 2001 2001 2001 2001 2001 2001 ...
#> $ week : int [1:57552] 1 1 1 1 1 1 1 1 1 1 ...
#> $ date : Date[1:57552], format: "2001-01-07" "2001-01-07" ...
#> $ Ebola hemorrhagic fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Ebola hemorrhagic fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Ebola hemorrhagic fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Ebola hemorrhagic fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (total) : int [1:57552] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (Others) : int [1:57552] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (total) : int [1:57552] 6 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (Inside Japan) : int [1:57552] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (Others) : int [1:57552] 5 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Poliomyelitis (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Poliomyelitis (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Poliomyelitis (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Poliomyelitis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (total) : int [1:57552] 12 0 1 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (Inside Japan) : int [1:57552] 10 0 0 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic E. coli infection (Unknown) : int [1:57552] 2 0 1 0 0 0 0 0 0 0 ...
#> $ Amebiasis (total) : int [1:57552] 3 0 0 0 0 0 0 0 0 0 ...
#> $ Amebiasis (Inside Japan) : int [1:57552] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Amebiasis (Others) : int [1:57552] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Amebiasis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute viral hepatitis (total) : int [1:57552] 1 0 0 0 1 0 0 0 0 0 ...
#> $ Acute viral hepatitis (Inside Japan) : int [1:57552] 1 0 0 0 1 0 0 0 0 0 ...
#> $ Acute viral hepatitis (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute viral hepatitis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cryptosporidiosis (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Creutzfeldt-Jakob disease (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (total) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (Inside Japan) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (Others) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe invasive streptococcal infections (Unknown) : int [1:57552] 0 0 0 0 0 0 0 0 0 0 ...
#> $ AIDS (total) : int [1:57552] 9 0 0 0 0 0 0 0 1 0 ...
#> $ AIDS (Inside Japan) : int [1:57552] 7 0 0 0 0 0 0 0 1 0 ...
#> $ AIDS (Others) : int [1:57552] 1 0 0 0 0 0 0 0 0 0 ...
#> [list output truncated]str(bullet)
#> tibble [3,408 × 178] (S3: tbl_df/tbl/data.frame)
#> $ prefecture : chr [1:3408] "Total" "Hokkaido" "Aomori" "Iwate" ...
#> $ year : int [1:3408] 2024 2024 2024 2024 2024 2024 2024 2024 2024 2024 ...
#> $ week : int [1:3408] 1 1 1 1 1 1 1 1 1 1 ...
#> $ date : Date[1:3408], format: "2024-01-01" "2024-01-01" ...
#> $ Ebola hemorrhagic fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Ebola hemorrhagic fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Crimean-Congo hemorrhagic fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Smallpox (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Smallpox (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ South American hemorrhagic fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ South American hemorrhagic fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Plague (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Marburg disease (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Lassa fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute poliomyelitis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Acute poliomyelitis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Tuberculosis (weekly) : int [1:3408] 78 2 0 0 6 1 1 0 4 1 ...
#> $ Tuberculosis (cumulative) : int [1:3408] 78 2 0 0 6 1 1 0 4 1 ...
#> $ Diphtheria (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Diphtheria (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe Acute Respiratory Syndrome (SARS) (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe Acute Respiratory Syndrome (SARS) (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Middle East Respiratory Syndrome Coronavirus (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Middle East Respiratory Syndrome Coronavirus (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Avian influenza H5N1 (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Avian influenza H5N1 (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Avian influenza H7N9 (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Avian influenza H7N9 (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Cholera (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (weekly) : int [1:3408] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Shigellosis (cumulative) : int [1:3408] 2 0 0 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic Escherichia coli infection (weekly) : int [1:3408] 9 0 0 0 0 0 0 0 0 0 ...
#> $ Enterohemorrhagic Escherichia coli infection (cumulative) : int [1:3408] 9 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Typhoid fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Paratyphoid fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hepatitis E (weekly) : int [1:3408] 6 0 0 0 1 0 0 0 0 0 ...
#> $ Hepatitis E (cumulative) : int [1:3408] 6 0 0 0 1 0 0 0 0 0 ...
#> $ West Nile fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ West Nile fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hepatitis A (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hepatitis A (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Echinococcosis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Mpox (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Mpox (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Yellow fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Psittacosis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Omsk hemorrhagic fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Omsk hemorrhagic fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Relapsing fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Kyasanur forest disease (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Kyasanur forest disease (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Q fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Rabies (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Coccidioidomycosis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Coccidioidomycosis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Zika virus infection (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Zika virus infection (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe Fever with Thrombocytopenia Syndrome (SFTS) (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Severe Fever with Thrombocytopenia Syndrome (SFTS) (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hemorrhagic fever with renal syndrome (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hemorrhagic fever with renal syndrome (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Western equine encephalitis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Western equine encephalitis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Tick-borne encephalitis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Tick-borne encephalitis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Anthrax (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Anthrax (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Chikungunya fever (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Chikungunya fever (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Scrub typhus (Tsutsugamushi disease) (weekly) : int [1:3408] 5 0 0 0 0 0 0 0 0 0 ...
#> $ Scrub typhus (Tsutsugamushi disease) (cumulative) : int [1:3408] 5 0 0 0 0 0 0 0 0 0 ...
#> $ Dengue fever (weekly) : int [1:3408] 4 0 0 0 0 0 0 0 0 0 ...
#> $ Dengue fever (cumulative) : int [1:3408] 4 0 0 0 0 0 0 0 0 0 ...
#> $ Eastern equine encephalitis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Eastern equine encephalitis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Avian influenza (exclud. Avian influenza both H5N1 and H7N9) (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Avian influenza (exclud. Avian influenza both H5N1 and H7N9) (cumulative): int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Nipah virus infection (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Nipah virus infection (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Japanese spotted fever (weekly) : int [1:3408] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Japanese spotted fever (cumulative) : int [1:3408] 1 0 0 0 0 0 0 0 0 0 ...
#> $ Japanese encephalitis (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Japanese encephalitis (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hantavirus pulmonary syndrome (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Hantavirus pulmonary syndrome (cumulative) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> $ Herpes B virus infection (weekly) : int [1:3408] 0 0 0 0 0 0 0 0 0 0 ...
#> [list output truncated]The jpinfect_merge function helps to merge the datasets
into one dataset if necessary, which enables users to start their data
analysis instantly.
The jpinfect_pivot function enables users to seamlessly
pivot datasets between wide and long formats. This functionality is
particularly useful for reorganising data to suit analysis or
visualisation needs.
# Convert from wide to long format
bullet_long <- jpinfect_pivot(bullet)
# Convert from long to wide format
bullet_wide <- jpinfect_pivot(bullet_long)# Check the structure of long format
head(bullet_long)
#> # A tibble: 6 × 6
#> prefecture year week date disease cases
#> <chr> <int> <int> <date> <chr> <int>
#> 1 Total 2024 1 2024-01-01 Ebola hemorrhagic fever (weekly) 0
#> 2 Total 2024 1 2024-01-01 Ebola hemorrhagic fever (cumulative) 0
#> 3 Total 2024 1 2024-01-01 Crimean-Congo hemorrhagic fever (week… 0
#> 4 Total 2024 1 2024-01-01 Crimean-Congo hemorrhagic fever (cumu… 0
#> 5 Total 2024 1 2024-01-01 Smallpox (weekly) 0
#> 6 Total 2024 1 2024-01-01 Smallpox (cumulative) 0
# Check the structure of wide format
head(bullet_wide)
#> # A tibble: 6 × 178
#> prefecture year week date `Ebola hemorrhagic fever (weekly)`
#> <chr> <int> <int> <date> <int>
#> 1 Total 2024 1 2024-01-01 0
#> 2 Hokkaido 2024 1 2024-01-01 0
#> 3 Aomori 2024 1 2024-01-01 0
#> 4 Iwate 2024 1 2024-01-01 0
#> 5 Miyagi 2024 1 2024-01-01 0
#> 6 Akita 2024 1 2024-01-01 0
#> # ℹ 173 more variables: `Ebola hemorrhagic fever (cumulative)` <int>,
#> # `Crimean-Congo hemorrhagic fever (weekly)` <int>,
#> # `Crimean-Congo hemorrhagic fever (cumulative)` <int>,
#> # `Smallpox (weekly)` <int>, `Smallpox (cumulative)` <int>,
#> # `South American hemorrhagic fever (weekly)` <int>,
#> # `South American hemorrhagic fever (cumulative)` <int>,
#> # `Plague (weekly)` <int>, `Plague (cumulative)` <int>, …Although the build-in datasets are provided in this package, it is
ideal for scientists, epidemiologists and public health officers to
review whole data handling process from the upstream to downstream. For
those who cares the precision of dataset, jpinfect provides
the following functions to build the same datasets or even the latest
bullet datasets sourced from the government-provided raw data.
The sources of these datasets can be checked by using
jpinfect_url_confirmed for confirmed case reports and
jpinfect_url_bullet for provisional case reports,
respectively.
The raw data can be downloaded using
jpinfect_get_confirmed for confirmed case reports and
jpinfect_get_bullet for provisional case reports,
respectively. Confirmed weekly case data is organised into a single
Microsoft Excel file for each year, while provisional data is provided
as separate CSV files for each week. Since this function connect to the
government website, it may take some time to download the data. To avoid
excessive burden on the server, please kindly avoid downloading the
files frequently. The downloaded files are saved under the
raw_data folder or the specified directory.
The acquired raw data into your local computer can be imported into R
using jpinfect_read_confirmed and
jpinfect_read_bullet.
If you encounter any bugs or issues while using the
jpinfect package, please report them on the GitHub Issues
page. When reporting, please include the following information:
A clear description of the problem
Steps to reproduce the issue
Your R version and operating system
Relevant error messages
Example code to reproduce the problem