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.
Description
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.
Usage
engdeaths
Format
An object of class data.frame
with 6260 rows and 24 columns.
Source
Sahu and Böhning (2021). @format A data frame with 6260 rows and 24 columns:
- Areacode
Areacode identifier of the 313 Local Authority Districts, Counties and Unitary Authorities (LADCUA)
- mapid
A numeric column identifying the map area needed for plotting
- spaceid
A numeric variable taking value 1 to 313 identifying the LADCUA's
- Region
Identifies one of the 9 English regions
- popn
Population number in mid-2019
- jsa
Percentage of the working age population receiving job-seekers allowance during January 2020
- houseprice
Median house price in March 2020
- popdensity
Population density in mid-2019
- no2
Estimated average value of NO2 at the centroid of the LADCUA
- covid
Number of Covid-19 deaths within 28 days of a positive test
- allcause
Number deaths
- noofcases
Number of cases
- n0
Log of the standardized case morbidity during the current week
- n1
Log of the standardized case morbidity during the week before
- n2
Log of the standardized case morbidity during the second week before
- n3
Log of the standardized case morbidity during the third week before
- n4
Log of the standardized case morbidity during the fourth week before
- Edeaths
Expected number of Covid-19 deaths. See Sahu and Bohning (2021) for methodology.
- Ecases
Expected number of cases.
- logEdeaths
Log of the column
Edeaths
- logEcases
Log of the column Ecases
- highdeathsmr
A binary (0-1) random variable taking the value 1 if the SMR of Covid-19 death is higher than 1
References
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.
Examples
colnames(engdeaths)
dim(engdeaths)
summary(engdeaths[, 11:24])