R_t {swash} | R Documentation |
Effective Reproduction Number for Epidemic Data
Description
Calculation of the effective reproduction number for infection/surveillance data
Usage
R_t(
infections,
GP = 4,
correction = FALSE
)
Arguments
infections |
|
GP |
Generation period, in days |
correction |
Correction of values equal to zero? (Recommended) |
Details
The function calculates the effective reproduction number (=growth factor), R_t
, of an infections time series.
Value
list
with two entries:
R_t: |
Object of class |
infections_data: |
Object of class |
Author(s)
Thomas Wieland
References
Bonifazi G et al. (2021) A simplified estimate of the effective reproduction number Rt using its relation with the doubling time and application to Italian COVID-19 data. The European Physical Journal Plus 136, 386. doi:10.1140/epjp/s13360-021-01339-6
Wieland T (2020) A phenomenological approach to assessing the effectiveness of COVID-19 related nonpharmaceutical interventions in Germany. Safety Science 131, 104924. doi:10.1016/j.ssci.2020.104924
See Also
Examples
data(COVID19Cases_geoRegion)
# Get SWISS COVID19 cases at NUTS 3 level
COVID19Cases_geoRegion <-
COVID19Cases_geoRegion[!COVID19Cases_geoRegion$geoRegion %in% c("CH", "CHFL"),]
# Exclude CH = Switzerland total and CHFL = Switzerland and Liechtenstein total
COVID19Cases_geoRegion <-
COVID19Cases_geoRegion[COVID19Cases_geoRegion$datum <= "2020-05-31",]
# Extract first COVID-19 wave
COVID19Cases_BS <-
COVID19Cases_geoRegion[(COVID19Cases_geoRegion$geoRegion == "ZH")
& (COVID19Cases_geoRegion$sumTotal > 0),]
# COVID cases for Zurich
Rt_BS <- R_t(infections = COVID19Cases_BS$entries)
# Effective reproduction number
Rt_BS