diff --git a/DESCRIPTION b/DESCRIPTION index 47208556..b1b7e060 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: AMR -Version: 1.4.0.9026 -Date: 2020-11-24 +Version: 1.4.0.9027 +Date: 2020-11-25 Title: Antimicrobial Resistance Analysis Authors@R: c( person(role = c("aut", "cre"), diff --git a/NEWS.md b/NEWS.md index cee74a51..d9f573d5 100755 --- a/NEWS.md +++ b/NEWS.md @@ -1,9 +1,9 @@ -# AMR 1.4.0.9026 -## Last updated: 24 November 2020 +# AMR 1.4.0.9027 +## Last updated: 25 November 2020 ### New * Function `is_new_episode()` to determine patient episodes which are not necessarily based on microorganisms. It also supports grouped variables with e.g. `mutate()`, `filter()` and `summarise()` of the `dplyr` package: - ```r + ```r example_isolates %>% group_by(patient_id, hospital_id) %>% filter(is_new_episode(date, episode_days = 60)) diff --git a/docs/404.html b/docs/404.html index 97432560..c506dc45 100644 --- a/docs/404.html +++ b/docs/404.html @@ -81,7 +81,7 @@ AMR (for R) - 1.4.0.9026 + 1.4.0.9027 diff --git a/docs/LICENSE-text.html b/docs/LICENSE-text.html index 53c1f42f..2166c262 100644 --- a/docs/LICENSE-text.html +++ b/docs/LICENSE-text.html @@ -81,7 +81,7 @@ AMR (for R) - 1.4.0.9026 + 1.4.0.9027 diff --git a/docs/articles/index.html b/docs/articles/index.html index 890970c7..2593fa72 100644 --- a/docs/articles/index.html +++ b/docs/articles/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.4.0.9026 + 1.4.0.9027 diff --git a/docs/authors.html b/docs/authors.html index 374c7cf9..71cacece 100644 --- a/docs/authors.html +++ b/docs/authors.html @@ -81,7 +81,7 @@ AMR (for R) - 1.4.0.9026 + 1.4.0.9027 diff --git a/docs/countries.png b/docs/countries.png index 1f925df6..5b995680 100644 Binary files a/docs/countries.png and b/docs/countries.png differ diff --git a/docs/countries_large.png b/docs/countries_large.png index 4528252e..5b77adb7 100644 Binary files a/docs/countries_large.png and b/docs/countries_large.png differ diff --git a/docs/index.html b/docs/index.html index b19c85a3..81b1b4d9 100644 --- a/docs/index.html +++ b/docs/index.html @@ -43,7 +43,7 @@ AMR (for R) - 1.4.0.9026 + 1.4.0.9027 @@ -210,7 +210,7 @@ Since you are one of our users, we would like to know how you use the package an

This package is fully independent of any other R package and works on Windows, macOS and Linux with all versions of R since R-3.0.0 (April 2013). It was designed to work in any setting, including those with very limited resources. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the University of Groningen, in collaboration with non-profit organisations Certe Medical Diagnostics and Advice and University Medical Center Groningen. This R package is actively maintained and is free software (see Copyright).

- Used in more than 120 countries
Since its first public release in early 2018, this package has been downloaded from more than 120 countries. Click the map to enlarge and to also see the names of the countries. + Used in 135 countries
Since its first public release in early 2018, this package has been downloaded from 135 countries. Click the map to enlarge and to also see the names of the countries.



diff --git a/docs/news/index.html b/docs/news/index.html index 3c294c93..a7e2efae 100644 --- a/docs/news/index.html +++ b/docs/news/index.html @@ -81,7 +81,7 @@ AMR (for R) - 1.4.0.9026 + 1.4.0.9027 @@ -236,31 +236,37 @@ Source: NEWS.md -
-

-AMR 1.4.0.9026 Unreleased +
+

+AMR 1.4.0.9027 Unreleased

-
+

-Last updated: 24 November 2020 +Last updated: 25 November 2020

New

    -

  • Function is_new_episode() to determine patient episodes which are not necessarily based on microorganisms. It also supports grouped variables with e.g. mutate(), filter() and summarise() of the dplyr package: r example_isolates %>% group_by(patient_id, hospital_id) %>% filter(is_new_episode(date, episode_days = 60))

  • -

    Functions mo_is_gram_negative() and mo_is_gram_positive() as wrappers around mo_gramstain(). They always return TRUE or FALSE (except when the input is NA or the MO code is UNKNOWN), thus always return FALSE for species outside the taxonomic kingdom of Bacteria. If you have the dplyr package installed, they can even determine the column with microorganisms themselves when used inside dplyr verbs:

    +

    Function is_new_episode() to determine patient episodes which are not necessarily based on microorganisms. It also supports grouped variables with e.g. mutate(), filter() and summarise() of the dplyr package:

     example_isolates %>%
-  filter(mo_is_gram_positive())
+  group_by(patient_id, hospital_id) %>%
+  filter(is_new_episode(date, episode_days = 60))
    +
    • +
  • +

    Functions mo_is_gram_negative() and mo_is_gram_positive() as wrappers around mo_gramstain(). They always return TRUE or FALSE (except when the input is NA or the MO code is UNKNOWN), thus always return FALSE for species outside the taxonomic kingdom of Bacteria. If you have the dplyr package installed, they can even determine the column with microorganisms themselves when used inside dplyr verbs:

    +
    +example_isolates %>%
+  filter(mo_is_gram_positive())
 #> NOTE: Using column `mo` as input for mo_is_gram_positive()

  • Function mo_is_intrinsic_resistant() to test for intrinsic resistance, based on EUCAST Intrinsic Resistance and Unusual Phenotypes v3.2 from 2020. As with the new mo_is_gram_*() functions, if you have the dplyr package installed the column with microorganisms will be automatically determined when used inside dplyr verbs:

    -
    +
     example_isolates %>%
-  filter(mo_is_intrinsic_resistant(ab = "Vancomycin"))
+  filter(mo_is_intrinsic_resistant(ab = "Vancomycin"))
 #> NOTE: Using column `mo` as input for mo_is_intrinsic_resistant()
@@ -304,7 +310,7 @@

  • Data set intrinsic_resistant. This data set contains all bug-drug combinations where the ‘bug’ is intrinsic resistant to the ‘drug’ according to the latest EUCAST insights. It contains just two columns: microorganism and antibiotic.

    Curious about which enterococci are actually intrinsic resistant to vancomycin?

    -
    +
     library(AMR)
 library(dplyr)
 intrinsic_resistant %>%
@@ -326,7 +332,7 @@
 
      
 
    • 
 
      Support for using dplyr’s across() to interpret MIC values or disk zone diameters, which also automatically determines the column with microorganism names or codes.
      
-
      +
       # until dplyr 1.0.0
 your_data %>% mutate_if(is.mic, as.rsi)
 your_data %>% mutate_if(is.disk, as.rsi)
@@ -343,7 +349,7 @@
 
      • 
 
    • 
 
      Added intelligent data cleaning to as.disk(), so numbers can also be extracted from text and decimal numbers will always be rounded up:
      
-
      +
       as.disk(c("disk zone: 23.4 mm", 23.4))
 #> Class <disk>
 #> [1] 24 24
      
@@ -403,7 +409,7 @@
 
    • Function ab_from_text() to retrieve antimicrobial drug names, doses and forms of administration from clinical texts in e.g. health care records, which also corrects for misspelling since it uses as.ab() internally
      • 
 
    • 
 
      Tidyverse selection helpers for antibiotic classes, that help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations. They can be used in any function that allows selection helpers, like dplyr::select() and tidyr::pivot_longer():
      
-
      +
       library(dplyr)
 
 # Columns 'IPM' and 'MEM' are in the example_isolates data set
@@ -591,7 +597,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
    • Fixed important floating point error for some MIC comparisons in EUCAST 2020 guideline
      • 
 
    • 
 
      Interpretation from MIC values (and disk zones) to R/SI can now be used with mutate_at() of the dplyr package:
      
-
      +
       yourdata %>% 
   mutate_at(vars(antibiotic1:antibiotic25), as.rsi, mo = "E. coli")
 
@@ -619,7 +625,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
        
 
      • 
 
        Support for LOINC codes in the antibiotics data set. Use ab_loinc() to retrieve LOINC codes, or use a LOINC code for input in any ab_* function:
        
-
        +
         ab_loinc("ampicillin")
 #> [1] "21066-6" "3355-5"  "33562-0" "33919-2" "43883-8" "43884-6" "87604-5"
 ab_name("21066-6")
@@ -629,7 +635,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
        • 
 
      • 
 
        Support for SNOMED CT codes in the microorganisms data set. Use mo_snomed() to retrieve SNOMED codes, or use a SNOMED code for input in any mo_* function:
        
-
        +
         mo_snomed("S. aureus")
 #> [1] 115329001   3092008 113961008
 mo_name(115329001)
@@ -693,10 +699,10 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
          
 
        • 
 
          If you were dependent on the old Enterobacteriaceae family e.g. by using in your code:
          
-
          +
           if (mo_family(somebugs) == "Enterobacteriaceae") ...
          
 
          then please adjust this to:
          
-
          +
           if (mo_order(somebugs) == "Enterobacterales") ...
          
 
          • 
 
        
@@ -709,7 +715,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
          
 
        • 
 
          Functions susceptibility() and resistance() as aliases of proportion_SI() and proportion_R(), respectively. These functions were added to make it more clear that “I” should be considered susceptible and not resistant.
          
-
          +
           library(dplyr)
 example_isolates %>%
   group_by(bug = mo_name(mo)) %>% 
@@ -737,7 +743,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
        • More intelligent way of coping with some consonants like “l” and “r”
          • 
 
        • 
 
          Added a score (a certainty percentage) to mo_uncertainties(), that is calculated using the Levenshtein distance:
          
-
          +
           as.mo(c("Stafylococcus aureus",
         "staphylokok aureuz"))
 #> Warning: 
@@ -795,13 +801,13 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            
 
          • 
 
            Determination of first isolates now excludes all ‘unknown’ microorganisms at default, i.e. microbial code "UNKNOWN". They can be included with the new parameter include_unknown:
            
-
            +
             first_isolate(..., include_unknown = TRUE)
            
 
            For WHONET users, this means that all records/isolates with organism code "con" (contamination) will be excluded at default, since as.mo("con") = "UNKNOWN". The function always shows a note with the number of ‘unknown’ microorganisms that were included or excluded.
            
 
            • 
 
          • 
 
            For code consistency, classes ab and mo will now be preserved in any subsetting or assignment. For the sake of data integrity, this means that invalid assignments will now result in NA:
            
-
            +
             # how it works in base R:
 x <- factor("A")
 x[1] <- "B"
@@ -825,7 +831,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              
 
            • 
 
              Function bug_drug_combinations() to quickly get a data.frame with the results of all bug-drug combinations in a data set. The column containing microorganism codes is guessed automatically and its input is transformed with mo_shortname() at default:
              
-
              +
               x <- bug_drug_combinations(example_isolates)
 #> NOTE: Using column `mo` as input for `col_mo`.
 x[1:4, ]
@@ -847,12 +853,12 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 #> 4 Gram-negative AMX 227  0 405   632
 #> NOTE: Use 'format()' on this result to get a publicable/printable format.
              
 
              You can format this to a printable format, ready for reporting or exporting to e.g. Excel with the base R format() function:
              
-
              +
               format(x, combine_IR = FALSE)
              
 
              • 
 
            • 
 
              Additional way to calculate co-resistance, i.e. when using multiple antimicrobials as input for portion_* functions or count_* functions. This can be used to determine the empiric susceptibility of a combination therapy. A new parameter only_all_tested (which defaults to FALSE) replaces the old also_single_tested and can be used to select one of the two methods to count isolates and calculate portions. The difference can be seen in this example table (which is also on the portion and count help pages), where the %SI is being determined:
              
-
              +
               # --------------------------------------------------------------------
 #                     only_all_tested = FALSE  only_all_tested = TRUE
 #                     -----------------------  -----------------------
@@ -873,7 +879,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • 
 
            • 
 
              tibble printing support for classes rsi, mic, disk, ab mo. When using tibbles containing antimicrobial columns, values S will print in green, values I will print in yellow and values R will print in red. Microbial IDs (class mo) will emphasise on the genus and species, not on the kingdom.
              
-
              +
               # (run this on your own console, as this page does not support colour printing)
 library(dplyr)
 example_isolates %>%
@@ -955,7 +961,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                
 
              • 
 
                Function rsi_df() to transform a data.frame to a data set containing only the microbial interpretation (S, I, R), the antibiotic, the percentage of S/I/R and the number of available isolates. This is a convenient combination of the existing functions count_df() and portion_df() to immediately show resistance percentages and number of available isolates:
                
-
                +
                 septic_patients %>%
   select(AMX, CIP) %>%
   rsi_df()
@@ -981,7 +987,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • UPEC (Uropathogenic E. coli)
                • 
 
              
 
              All these lead to the microbial ID of E. coli:
              
-
              +
               as.mo("UPEC")
 # B_ESCHR_COL
 mo_name("UPEC")
@@ -1085,7 +1091,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            • when all values are unique it now shows a message instead of a warning
              • 
 
            • 
 
              support for boxplots:
              
-
              +
               septic_patients %>% 
   freq(age) %>% 
   boxplot()
@@ -1179,7 +1185,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • 
 
            • 
 
              New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:
              
-
              +
               filter_aminoglycosides()
 filter_carbapenems()
 filter_cephalosporins()
@@ -1192,7 +1198,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 filter_macrolides()
 filter_tetracyclines()
              
 
              The antibiotics data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the antibiotics data set. For example:
              
-
              +
               septic_patients %>% filter_glycopeptides(result = "R")
 # Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
 septic_patients %>% filter_glycopeptides(result = "R", scope = "all")
@@ -1200,7 +1206,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • 
 
            • 
 
              All ab_* functions are deprecated and replaced by atc_* functions:
              
-
              +
               ab_property -> atc_property()
 ab_name -> atc_name()
 ab_official -> atc_official()
@@ -1220,19 +1226,19 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
            • New function age_groups() to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.
              • 
 
            • 
 
              New function ggplot_rsi_predict() as well as the base R plot() function can now be used for resistance prediction calculated with resistance_predict():
              
-
              +
               x <- resistance_predict(septic_patients, col_ab = "amox")
 plot(x)
 ggplot_rsi_predict(x)
              
 
              • 
 
            • 
 
              Functions filter_first_isolate() and filter_first_weighted_isolate() to shorten and fasten filtering on data sets with antimicrobial results, e.g.:
              
-
              +
               septic_patients %>% filter_first_isolate(...)
 # or
 filter_first_isolate(septic_patients, ...)
              
 
              is equal to:
              
-
              +
               septic_patients %>%
   mutate(only_firsts = first_isolate(septic_patients, ...)) %>%
   filter(only_firsts == TRUE) %>%
@@ -1264,7 +1270,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                
 
              • 
 
                Now handles incorrect spelling, like i instead of y and f instead of ph:
                
-
                +
                 # mo_fullname() uses as.mo() internally
 
 mo_fullname("Sthafilokockus aaureuz")
@@ -1275,7 +1281,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                • 
 
              • 
 
                Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default allow_uncertain = TRUE is equal to uncertainty level 2. Run ?as.mo for more info about these levels.
                
-
                +
                 # equal:
 as.mo(..., allow_uncertain = TRUE)
 as.mo(..., allow_uncertain = 2)
@@ -1289,7 +1295,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
              • All microbial IDs that found are now saved to a local file ~/.Rhistory_mo. Use the new function clean_mo_history() to delete this file, which resets the algorithms.
                • 
 
              • 
 
                Incoercible results will now be considered ‘unknown’, MO code UNKNOWN. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:
                
-
                +
                 mo_genus("qwerty", language = "es")
 # Warning: 
 # one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
@@ -1338,7 +1344,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                  
 
                • 
 
                  Support for tidyverse quasiquotation! Now you can create frequency tables of function outcomes:
                  
-
                  +
                   # Determine genus of microorganisms (mo) in `septic_patients` data set:
 # OLD WAY
 septic_patients %>%
@@ -1421,7 +1427,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                • Fewer than 3 characters as input for as.mo will return NA
                  • 
 
                • 
 
                  Function as.mo (and all mo_* wrappers) now supports genus abbreviations with “species” attached
                  
-
                  +
                   as.mo("E. species")        # B_ESCHR
 mo_fullname("E. spp.")     # "Escherichia species"
 as.mo("S. spp")            # B_STPHY
@@ -1437,14 +1443,14 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                    
 
                  • 
 
                    Support for grouping variables, test with:
                    
-
                    +
                     septic_patients %>% 
   group_by(hospital_id) %>% 
   freq(gender)
                    
 
                    • 
 
                  • 
 
                    Support for (un)selecting columns:
                    
-
                    +
                     septic_patients %>% 
   freq(hospital_id) %>% 
   select(-count, -cum_count) # only get item, percent, cum_percent
                    
@@ -1523,7 +1529,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                    • 
 
                  
 
                  They also come with support for German, Dutch, French, Italian, Spanish and Portuguese:
                  
-
                  +
                   mo_gramstain("E. coli")
 # [1] "Gram negative"
 mo_gramstain("E. coli", language = "de") # German
@@ -1533,7 +1539,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 mo_fullname("S. group A", language = "pt") # Portuguese
 # [1] "Streptococcus grupo A"
                  
 
                  Furthermore, former taxonomic names will give a note about the current taxonomic name:
                  
-
                  +
                   mo_gramstain("Esc blattae")
 # Note: 'Escherichia blattae' (Burgess et al., 1973) was renamed 'Shimwellia blattae' (Priest and Barker, 2010)
 # [1] "Gram negative"
                  
@@ -1547,7 +1553,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                • Function is.rsi.eligible to check for columns that have valid antimicrobial results, but do not have the rsi class yet. Transform the columns of your raw data with: data %>% mutate_if(is.rsi.eligible, as.rsi)
                  • 
 
                • 
 
                  Functions as.mo and is.mo as replacements for as.bactid and is.bactid (since the microoganisms data set not only contains bacteria). These last two functions are deprecated and will be removed in a future release. The as.mo function determines microbial IDs using intelligent rules:
                  
-
                  +
                   as.mo("E. coli")
 # [1] B_ESCHR_COL
 as.mo("MRSA")
@@ -1555,7 +1561,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 as.mo("S group A")
 # [1] B_STRPTC_GRA
                  
 
                  And with great speed too - on a quite regular Linux server from 2007 it takes us less than 0.02 seconds to transform 25,000 items:
                  
-
                  +
                   thousands_of_E_colis <- rep("E. coli", 25000)
 microbenchmark::microbenchmark(as.mo(thousands_of_E_colis), unit = "s")
 # Unit: seconds
@@ -1588,7 +1594,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                • Added three antimicrobial agents to the antibiotics data set: Terbinafine (D01BA02), Rifaximin (A07AA11) and Isoconazole (D01AC05)
                  • 
 
                • 
 
                  Added 163 trade names to the antibiotics data set, it now contains 298 different trade names in total, e.g.:
                  
-
                  +
                   ab_official("Bactroban")
 # [1] "Mupirocin"
 ab_name(c("Bactroban", "Amoxil", "Zithromax", "Floxapen"))
@@ -1604,7 +1610,7 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                • Added parameters minimum and as_percent to portion_df
                  • 
 
                • 
 
                  Support for quasiquotation in the functions series count_* and portions_*, and n_rsi. This allows to check for more than 2 vectors or columns.
                  
-
                  +
                   septic_patients %>% select(amox, cipr) %>% count_IR()
 # which is the same as:
 septic_patients %>% count_IR(amox, cipr)
@@ -1623,11 +1629,11 @@ This works for all drug combinations, such as ampicillin/sulbactam, ceftazidime/
 
                • Added longest en shortest character length in the frequency table (freq) header of class character
                  • 
 
                • 
 
                  Support for types (classes) list and matrix for freq
                  
-
                  +
                   my_matrix = with(septic_patients, matrix(c(age, gender), ncol = 2))
 freq(my_matrix)
                  
 
                  For lists, subsetting is possible:
                  
-
                  +
                   my_list = list(age = septic_patients$age, gender = septic_patients$gender)
 my_list %>% freq(age)
 my_list %>% freq(gender)
                  
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 71f68e16..f2df8e12 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -12,7 +12,7 @@ articles:
   datasets: datasets.html
   resistance_predict: resistance_predict.html
   welcome_to_AMR: welcome_to_AMR.html
-last_built: 2020-11-24T10:47Z
+last_built: 2020-11-25T11:09Z
 urls:
   reference: https://msberends.github.io/AMR//reference
   article: https://msberends.github.io/AMR//articles
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 9dd0c294..ef39a782 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -81,7 +81,7 @@
       
       
         AMR (for R)
-        1.4.0.9026
+        1.4.0.9027
       
     
                  
 
diff --git a/docs/survey.html b/docs/survey.html
index 10481d5c..344ae117 100644
--- a/docs/survey.html
+++ b/docs/survey.html
@@ -81,7 +81,7 @@
       
       
         AMR (for R)
-        1.4.0.9026
+        1.4.0.9027
       
     
                  
 
diff --git a/index.md b/index.md
index 94ed66eb..1a23ed61 100644
--- a/index.md
+++ b/index.md
@@ -18,8 +18,8 @@ This package is [fully independent of any other R package](https://en.wikipedia.
 
                  
   
                  
     
-    Used in more than 120 countries
                  
-    Since its first public release in early 2018, this package has been downloaded from more than 120 countries. Click the map to enlarge and to also see the names of the countries.


                  
+    Used in 135 countries
                  
+    Since its first public release in early 2018, this package has been downloaded from 135 countries. Click the map to enlarge and to also see the names of the countries.


                  
 
                  
 
 
                  
diff --git a/pkgdown/logos/countries.png b/pkgdown/logos/countries.png
index 1f925df6..5b995680 100644
Binary files a/pkgdown/logos/countries.png and b/pkgdown/logos/countries.png differ
diff --git a/pkgdown/logos/countries_large.png b/pkgdown/logos/countries_large.png
index 4528252e..5b77adb7 100644
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