epiforecasts/covidregionaldata: JHU and Google support

This release adds support for data sets from John Hopkins University and the Google open data project. Both of these sources aggregate a range of data at national and subnational levels. It also contains a range of small fixes and improvements to documentation. Finally, this release adds optional data processing which will be extended in future releases (contributions warmly welcomed). Thanks to @joseph-palmer, @RichardMN, and @kathsherratt for contributions towards this release. New features Support for data provided by John Hopkins University (by @joseph-palmer). Support for data provided by Google COVID-19 open data project (by @joseph-palmer). Added a available_regions method for all classes that shows level 1 regions with data available for the region of interest. This is of particular use when combined with the JHU or Google datasets where processing a large number of regions that are not required can take some time. Adds support for JHU or Google data to get_national_data(). This may also now be used to access lower level data from these sources but it may be better to instead use the classes directly or via initialise_dataclass(). Other changes The optional downloading of NHS region data in the UK() has been improved to include both the dynamic data previously supported and the archive document now produced (by @kathsherratt). The examples for the UK() class have been expanded to better showcase the package functionality. The documentation and examples for get_regional_data(), get_national_data(), and get_available_datasets() has been expanded with a focus on increasing the visibility of the underlying package structure. The documentation and examples for initialise_dataclass(), DataClass(), and CountryDataClass() has been expanded and improved. Improvements to the linking of documentation for related functions and classes. Improvements to the documentation for contributors (by @RichardMN). Improvements to the pkgdown documentation to organise packages into appropriate subcategories