EpiForecasts’ COVID pages give national estimates for the reproduction number, rate of spread and doubling time for Lithuania and a discussion of their methods. The usual epiforecasts website has not been updated for a few days but you can still access an alternative presentation of EpiForecasts calculations.
Subnational estimates are available for some countries but not for Lithuania. This is an attempt to apply EpiForecasts methods and code to Lithuanian data. The populations of some Lithuanian municipalities are very small meaning that these approaches may not be applicable.
This summary information is also available as a table.
The Government of Lithuania’s COVID19 website Korona Stop is a good first resource for information about COVID19 in Lithuania.
The Ministry of Foreign Affairs has a dedicated website on COVID19 for foreigners in Lithuania
The Official Statistics Portal (OSP) has a dedicated dashboard on COVID19 (in Lithuanian, with English translations on highlighted terms). This can provide incidence per capita figures for each municipality.
OSP has also published statistical analyses of COVID19 in Lithuania including an excess mortality analysis in 2020.
Data is sourced from the National Public Health Centre under the Ministry of Health which provides a daily update of confirmed cases of COVID19 in Lithuania. This case data is provided as a JSON in Lithuanian at ftp://atviriduomenys.nvsc.lt/
The data has been processed using the EpiNow2 R package to estimate the time-varying reproduction number, rate of spread, and doubling time. EpiNow2 uses a range of open-source tools (Abbott et al.), and current best practices (Gostic et al.).
The map of Lithuania’s municipalities is from the OpenStreetMap and is © OpenStreetMap contributors. I used QGIS to convert the OpenStreetMap data into a shapefile which R could use. The visualisation was originally built using the RtD3 package following the example given for subnational results but now is based on the regional example given in the rt_vis package; both are by Hamish Gibbs.
Copyright © 2021 Richard Martin-Nielsen.