contactdata

The goal of contactdata is to provide access to social contact data for 177 countries. This data comes from

Kiesha Prem, Alex R. Cook, Mark Jit, Projecting social contact matrices in 152 countries using contact surveys and demographic data, PLoS Comp. Biol. (2017), https://doi.org/10.1371/journal.pcbi.1005697.

and

Kiesha Prem, Kevin van Zandvoort, Petra Klepac, Rosalind M. Eggo, Nicholas G. Davies, CMMID COVID-19 Working Group, Alex R. Cook, Mark Jit, Projecting contact matrices in 177 geographical regions: An update and comparison with empirical data for the COVID-19 era, PLoS Comp. Biol. (2021), https://doi.org/10.1371/journal.pcbi.1009098.

(please cite them in your publications, alongside this package).

Note that this package does not make any geopolitical statement and only provides the data as it has been published.<

contactdata offers an easier access to this data, makes it readily compatible with tidyverse packages, such as ggplot2, via the contact_countries() function, and provides an easy way to harmonise country nomenclature by using the countrycode package as authoritative name source.

Installation

You can install this package from CRAN:

install.packages("contactdata")

or the development version from GitHub, via my r-universe:

install.packages("contactdata", repos = "https://bisaloo.r-universe.dev")

Example

The most basic function allows you to get matrix data for a specific country:

library(contactdata)
contact_matrix("France")
#>         00_05   05_10   10_15   15_20   20_25   25_30   30_35   35_40   40_45
#> 00_05 2.78349 1.09714 0.59766 0.42514 0.54475 0.83666 1.12491 1.01569 0.63464
#> 05_10 1.33122 6.29510 1.27272 0.46477 0.35261 0.68506 1.02618 1.13031 0.99165
#> 10_15 0.39897 2.22464 9.84713 1.05305 0.45699 0.50444 0.66377 1.01329 1.16385
#> 15_20 0.30098 0.51971 3.20301 9.61013 1.15339 0.63465 0.54228 0.81646 0.95410
#> 20_25 0.37971 0.37347 0.44479 2.04600 3.20611 1.27444 0.82373 0.68958 0.68682
#> 25_30 0.72782 0.46144 0.35097 0.79856 1.67674 2.60892 1.49240 1.13783 0.96147
#> 30_35 0.79200 0.88463 0.67619 0.47619 0.92299 1.40768 2.20929 1.48891 1.13288
#> 35_40 0.74890 1.07171 0.88910 0.75047 0.72376 1.16507 1.45639 2.36740 1.65545
#> 40_45 0.51058 0.76735 1.06267 0.90561 0.87963 1.04440 1.34928 1.54511 2.22415
#> 45_50 0.33981 0.42638 0.67853 1.08318 0.90254 0.92989 1.09819 1.26458 1.37553
#> 50_55 0.31072 0.36274 0.59937 0.83731 1.00352 1.19355 1.06834 1.05459 1.36231
#> 55_60 0.39864 0.42351 0.50890 0.54609 0.71051 1.02643 1.13779 0.92754 1.01287
#> 60_65 0.38587 0.36993 0.34816 0.37182 0.48445 0.66960 0.78982 0.84058 0.74527
#> 65_70 0.29379 0.37405 0.33048 0.29065 0.37366 0.48083 0.65580 0.67714 0.68240
#> 70_75 0.20554 0.34026 0.38589 0.45420 0.31254 0.41868 0.44131 0.65480 0.77630
#> 75_80 0.26897 0.27668 0.35823 0.32506 0.26700 0.28903 0.42676 0.45384 0.51002
#>         45_50   50_55   55_60   60_65   65_70   70_75   75_80
#> 00_05 0.50544 0.52665 0.49783 0.39153 0.33717 0.26006 0.17979
#> 05_10 0.60923 0.49424 0.44941 0.41570 0.33297 0.24289 0.17912
#> 10_15 0.83145 0.55457 0.38642 0.30138 0.29915 0.26661 0.19652
#> 15_20 1.05109 0.63727 0.39461 0.28397 0.24315 0.19886 0.15800
#> 20_25 0.97167 0.70034 0.48631 0.29828 0.22838 0.24443 0.18815
#> 25_30 0.91936 0.95941 0.62849 0.43022 0.29327 0.22153 0.16448
#> 30_35 0.95357 0.83514 0.72204 0.51731 0.34141 0.23656 0.19808
#> 35_40 1.17352 0.91423 0.64593 0.56372 0.43426 0.33740 0.20415
#> 40_45 1.46235 1.06357 0.54927 0.52157 0.41118 0.33389 0.24101
#> 45_50 1.93332 1.16615 0.68328 0.45318 0.34997 0.32903 0.25424
#> 50_55 1.58509 1.70873 1.04120 0.59368 0.35534 0.33119 0.26512
#> 55_60 0.93730 1.19991 1.48381 0.82802 0.48857 0.32124 0.23713
#> 60_65 0.67297 0.67140 0.88300 1.21412 0.69313 0.50550 0.25726
#> 65_70 0.52748 0.55506 0.65119 0.74149 1.13052 0.52794 0.27354
#> 70_75 0.69078 0.54272 0.51067 0.89222 0.93588 1.25788 0.39716
#> 75_80 0.66095 0.66008 0.47413 0.41622 0.59534 0.62970 0.44627

You can also get several countries at once with the contact_df_countries() function, as detailed in the vignette.

Because it is very likely that users of this package will also need data about the population in each age group, it is also bundled in this package for convenience. Please see ?age_df_countries for more information.