engdeaths: Number of weekly Covid-19 deaths and cases in the 313 local...

In sujit-sahu/bmstdr: Bayesian Modeling of Spatio-Temporal Data with R

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

\insertCite

SahuBohning2021;textualbmstdr. @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

\insertAllCited

Examples

 colnames(engdeaths)
 dim(engdeaths)
 summary(engdeaths[, 11:24])

sujit-sahu/bmstdr documentation built on Jan. 30, 2024, 1:40 p.m.