engdeaths {bmstdr} | R Documentation |
Number of weekly Covid-19 deaths and cases in the 313 local Local Authority Districts, Counties and Unitary Authorities (LADCUA) in England during the 20 peaks in the first peak from March 13 to July 31, 2020.
engdeaths
An object of class data.frame
with 6260 rows and 28 columns.
Sahu and Böhning (2021). @format A data frame with 6260 rows and 19 columns:
Areacode identifier of the 313 Local Authority Districts, Counties and Unitary Authorities (LADCUA)
A numeric column identifying the map area needed for plotting
A numeric variable taking value 1 to 313 identifying the LADCUA's
Identifies one of the 9 English regions
Population number in mid-2019
Percentage of the working age population receiving job-seekers allowance during January 2020
Median house price in March 2020
Population density in mid-2019
Estimated average value of NO2 at the centroid of the LADCUA
Number of Covid-19 deaths within 28 days of a positive test
Number deaths
Number of cases
Number of cases during the week before
Number of cases during the second week before
Number of cases during the third week before
Number of cases during the fourth week before
Log of the standardized case morbidity during the current week
Log of the standardized case morbidity during the week before
Log of the standardized case morbidity during the second week before
Log of the standardized case morbidity during the third week before
Log of the standardized case morbidity during the fourth week before
Expected number of Covid-19 deaths. See Sahu and Bohning (2021) for methodology.
Expected number of cases.
Log of the column Edeaths
Log of the column Ecases
A binary (0-1) random variable taking the value 1 if the SMR of Covid-19 death is higher than 1
Sahu SK, Böhning D (2021). “Bayesian spatio-temporal joint disease mapping of Covid-19 cases and deaths in local authorities of England.” Spatial Statistics. doi: 10.1016/j.spasta.2021.100519.
colnames(engdeaths) dim(engdeaths) summary(engdeaths[, 11:28])