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Basic malariaAtlas usage.

Dan Pfeffer, Tim Lucas

2024-08-26

Overview

This package allows you to download parasite rate data (Plasmodium falciparum and P. vivax) and modelled raster outputs from the Malaria Atlas Project.

Available Data

The data can be interactively explored at https://data.malariaatlas.org/maps. This is also useful for finding information on the raster data available and checking the extents of different rasters (some are Africa only for example).

List Versions Functions

The list version functions are used to list the available versions of different datasets, and all return a data.frame with a single column for version. These versions can be passed to functions such as listShp, listSpecies, listPRPointCountries, listVecOccPointCountries, getPR, getVecOcc and getShp.

Use:

listPRPointVerions() to see the available versions for PR point data, which can then be used in listPRPointCountries and getPR.
listVecOccPointVersions() to see the available versions for vector occurrence data, which can then be used in listSpecies, listVecOccPointCountries and getVecOcc.
listShpVersions() to see the available versions for admin unit shape data, which can then be used in listShp and getShp.

listPRPointVersions()

listVecOccPointVersions()

listShpVersions()

List Countries and Species Functions

To list the countries where there is available data for PR points or vector occurrence points, use:

listPRPointCountries() for PR points
listVecOccPointCountries() for vector occurrence points

To list the species available for vector point data use listSpecies()

All three of these functions can optionally take a version parameter (which can be found with the list versions functions). If you choose not to provide a version, the most recent version of the relevant dataset will be selected by default.

listPRPointCountries(version = "202206")

listVecOccPointCountries(version = "201201")

listSpecies(version = "201201")

List Administrative Units

To list administrative units for which shapefiles are stored on the MAP geoserver, use listShp(). Similar to the list countries and species functions, this function can optionally take a version.

listShp(version = "202206")

List Raster Function

listRaster() gets minimal information on all available rasters. It returns a data.frame with several columns for each raster such as dataset_id, title, abstract, min_raster_year and max_raster_year. The dataset_id can then be used in getRaster and extractRaster.

listRaster()

Is Available Functions

isAvailable_pr confirms whether or not PR survey point data is available to download for a specified country, ISO3 code or continent.

Check whether PR data is available for Madagascar:

isAvailable_pr(country = "Madagascar")

Check whether PR data is available for the United States of America by ISO code:

isAvailable_pr(ISO = "USA")

Check whether PR data is available for Asia:

isAvailable_pr(continent = "Asia")

isAvailable_vec confirms whether or not vector survey point data is available to download for a specified country, ISO3 code or continent.

Check whether vector data is available for Myanmar:

isAvailable_vec(country = "Myanmar")

Check whether vector data is available for multiple countries:

isAvailable_vec(country = c("Nigeria", "Ethiopia"))

You can also pass these functions a dataset version. If you don’t they will default to using the most recent version.

isAvailable_pr(country = "Madagascar", version = "202206")

Downloading & Visualising Data:

get* functions & autoplot methods

Parasite Rate Survey Points

getPR() downloads all publicly available PR data points for a specified location (country, ISO, continent or extent) and plasmodium species (Pf, Pv or BOTH) and returns this as a dataframe with the following format:

MDG_pr_data <- getPR(country = "Madagascar", species = "both")

## Rows: 1,651
## Columns: 28
## $ dhs_id                    <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ site_id                   <int> 8689, 6221, 18093, 6021, 15070, 15795, 7374,…
## $ site_name                 <chr> "Vodivohitra", "Andranomasina", "Ankazobe", …
## $ latitude                  <dbl> -16.21700, -18.71700, -18.31600, -19.83400, …
## $ longitude                 <dbl> 49.68300, 47.46600, 47.11800, 47.85000, 47.2…
## $ rural_urban               <chr> "RURAL", "UNKNOWN", "RURAL", "UNKNOWN", "UNK…
## $ country                   <chr> "Madagascar", "Madagascar", "Madagascar", "M…
## $ country_id                <chr> "MDG", "MDG", "MDG", "MDG", "MDG", "MDG", "M…
## $ continent_id              <chr> "Africa", "Africa", "Africa", "Africa", "Afr…
## $ month_start               <int> 11, 1, 11, 3, 1, 7, 4, 1, 1, 2, 7, 11, 4, 7,…
## $ year_start                <int> 1989, 1987, 1989, 1987, 1987, 1995, 1986, 19…
## $ month_end                 <int> 11, 1, 12, 3, 1, 8, 6, 1, 1, 2, 8, 12, 4, 8,…
## $ year_end                  <int> 1989, 1987, 1989, 1987, 1987, 1995, 1986, 19…
## $ lower_age                 <dbl> 5, 0, 5, 0, 0, 2, 7, 0, 0, 0, 2, 5, 6, 2, 2,…
## $ upper_age                 <int> 15, 99, 15, 99, 99, 9, 22, 99, 99, 99, 9, 15…
## $ examined                  <int> 165, 50, 258, 246, 50, 50, 119, 50, 50, 210,…
## $ positive                  <dbl> 144.0, 7.5, 139.0, 126.0, 2.5, 6.0, 37.0, 13…
## $ pr                        <dbl> 0.87272727, 0.15000000, 0.53875969, 0.512195…
## $ species                   <chr> "P. falciparum", "P. falciparum", "P. falcip…
## $ method                    <chr> "Microscopy", "Microscopy", "Microscopy", "M…
## $ rdt_type                  <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ pcr_type                  <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ malaria_metrics_available <lgl> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TR…
## $ location_available        <lgl> TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TR…
## $ permissions_info          <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ citation1                 <chr> "Lepers, J.P. (1989). <i>Rapport sur la situ…
## $ citation2                 <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ citation3                 <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …

Africa_pvpr_data <- getPR(continent = "Africa", species = "Pv")

Extent_pfpr_data <- getPR(extent = rbind(c(-2.460181, 13.581921), c(-3.867188, 34.277344)), species = "Pf")

You can also pass this function a dataset version. If you don’t it will default to using the most recent version.

MDG_pr_data_202206 <- getPR(country = "Madagascar", species = "both", version = "202206")

autoplot.pr.points configures autoplot method to enable quick mapping of the locations of downloaded PR points.

autoplot(MDG_pr_data)

A version without facetting is also available.

autoplot(MDG_pr_data,
         facet = FALSE)

Vector Survey Points

getVecOcc() downloads all publicly available Vector survey points for a specified location (country, ISO, continent or extent) and species (options for which can be found with listSpecies) and returns this as a dataframe with the following format:

MMR_vec_data <- getVecOcc(country = "Myanmar")

## Rows: 2,866
## Columns: 25
## $ id             <int> 1945, 1946, 1951, 1952, 790, 781, 772, 791, 773, 783, 7…
## $ site_id        <int> 30243, 30243, 30243, 30243, 1000000072, 1000000071, 100…
## $ latitude       <dbl> 16.257, 16.257, 16.257, 16.257, 17.350, 17.380, 17.380,…
## $ longitude      <dbl> 97.725, 97.725, 97.725, 97.725, 96.041, 96.037, 96.037,…
## $ country        <chr> "Myanmar", "Myanmar", "Myanmar", "Myanmar", "Myanmar", …
## $ country_id     <chr> "MMR", "MMR", "MMR", "MMR", "MMR", "MMR", "MMR", "MMR",…
## $ continent_id   <chr> "Asia", "Asia", "Asia", "Asia", "Asia", "Asia", "Asia",…
## $ month_start    <int> 2, 3, 8, 9, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 10, …
## $ year_start     <int> 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1…
## $ month_end      <int> 2, 3, 8, 9, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 10, …
## $ year_end       <int> 1998, 1998, 1998, 1998, 2000, 2000, 2000, 2000, 2000, 2…
## $ anopheline_id  <int> 17, 17, 17, 17, 50, 49, 17, 51, 11, 4, 15, 1, 35, 30, 5…
## $ species        <chr> "Anopheles dirus species complex", "Anopheles dirus spe…
## $ species_plain  <chr> "Anopheles dirus", "Anopheles dirus", "Anopheles dirus"…
## $ id_method1     <chr> "unknown", "unknown", "unknown", "unknown", "morphology…
## $ id_method2     <chr> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ sample_method1 <chr> "man biting", "man biting", "man biting", "man biting",…
## $ sample_method2 <chr> "animal baited net trap", "animal baited net trap", "an…
## $ sample_method3 <chr> NA, NA, NA, NA, "animal baited net trap", "animal baite…
## $ sample_method4 <chr> NA, NA, NA, NA, "house resting inside", "house resting …
## $ assi           <chr> "", "", "", "", "", "", "", "", "", "", "", "", "", "",…
## $ citation       <chr> "Oo, T.T., Storch, V. and Becker, N. (2003).  <b><i>Ano…
## $ time_start     <date> 1998-02-01, 1998-03-01, 1998-08-01, 1998-09-01, 1998-0…
## $ time_end       <date> 1998-02-01, 1998-03-01, 1998-08-01, 1998-09-01, 2000-0…
## $ geometry       <POINT [°]> POINT (97.725 16.257), POINT (97.725 16.257), POI…

You can also pass this function a dataset version. If you don’t it will default to using the most recent version.

MMR_vec_data_201201 <- getVecOcc(country = "Myanmar", version = "201201")

autoplot.vector.points configures autoplot method to enable quick mapping of the locations of downloaded vector points.

autoplot(MMR_vec_data)

N.B. Facet-wrapped option is also available for species stratification.

autoplot(MMR_vec_data,
         facet = TRUE)

Shapefiles

getShp() downloads a shapefile for a specified country (or countries) and returns this as a simple feature object.

MDG_shp <- getShp(ISO = "MDG", admin_level = c("admin0", "admin1"))

## Rows: 23
## Columns: 17
## $ iso           <chr> "MDG", "MDG", "MDG", "MDG", "MDG", "MDG", "MDG", "MDG", …
## $ admn_level    <int> 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ name_0        <chr> "Madagascar", "Madagascar", "Madagascar", "Madagascar", …
## $ id_0          <int> 10000910, 10000910, 10000910, 10000910, 10000910, 100009…
## $ type_0        <chr> "Country", "Country", "Country", "Country", "Country", "…
## $ name_1        <chr> NA, "Menabe", "Alaotra Mangoro", "Amoron I Mania", "Anal…
## $ id_1          <int> NA, 10023004, 10022998, 10022989, 10022983, 10022999, 10…
## $ type_1        <chr> NA, "Region", "Region", "Region", "Region", "Region", "R…
## $ name_2        <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ id_2          <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ type_2        <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ name_3        <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ id_3          <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ type_3        <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, …
## $ source        <chr> "Madagascar NMCP 2016", "Madagascar NMCP 2016", "Madagas…
## $ country_level <chr> "MDG_0", "MDG_1", "MDG_1", "MDG_1", "MDG_1", "MDG_1", "M…
## $ geometry      <MULTIPOLYGON [°]> MULTIPOLYGON (((44.2278 -25..., MULTIPOLYGO…

autoplot.sf configures autoplot method to enable quick mapping of downloaded shapefiles.

autoplot(MDG_shp)

N.B. Facet-wrapped option is also available for species stratification.

autoplot(MDG_shp,
         facet = TRUE,
         map_title = "Example of facetted shapefiles.")

Modelled Rasters

getRaster()downloads publicly available MAP rasters for a specific dataset_id & year, clipped to a given bounding box or shapefile

MDG_shp <- getShp(ISO = "MDG", admin_level = "admin0")
MDG_PfPR2_10 <- getRaster(dataset_id = "Explorer__2020_Global_PfPR", shp = MDG_shp, year = 2013)

autoplot.SpatRaster & autoplot.SpatRasterCollection configures autoplot method to enable quick mapping of downloaded rasters.

p <- autoplot(MDG_PfPR2_10, shp_df = MDG_shp)

Combined visualisation

By using the above tools along with ggplot, simple comparison figures can be easily produced.

MDG_shp <- getShp(ISO = "MDG", admin_level = "admin0")
MDG_PfPR2_10 <- getRaster(dataset_id = "Explorer__2020_Global_PfPR", shp = MDG_shp, year = 2013)

p <- autoplot(MDG_PfPR2_10, shp_df = MDG_shp, printed = FALSE)

pr <- getPR(country = c("Madagascar"), species = "Pf")
p[[1]] +
geom_point(data = pr[pr$year_start==2013,], aes(longitude, latitude, fill = positive / examined, size = examined), shape = 21)+
scale_size_continuous(name = "Survey Size")+
 scale_fill_distiller(name = "PfPR", palette = "RdYlBu")

Similarly for vector survey data

MMR_shp <- getShp(ISO = "MMR", admin_level = "admin0")
MMR_An_dirus <- getRaster(dataset_id = "Explorer__2010_Anopheles_dirus_complex", shp = MMR_shp)

p <- autoplot(MMR_An_dirus, shp_df = MMR_shp, printed = FALSE)

vec <- getVecOcc(country = c("Myanmar"), species = "Anopheles dirus")
p[[1]] +
geom_point(data = vec, aes(longitude, latitude, colour = species))+
  scale_colour_manual(values = "black", name = "Vector survey locations")+
 scale_fill_distiller(name = "Predicted distribution of An. dirus complex", palette = "PuBuGn", direction = 1)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.