R/NetworkBuilding.R
edgelist_from_base.RdThis function computes the edgelist of a network of facilities across which subjects can be transferred. The edgelist is computed from a database that contains the records of the subjects' stays in the facilities.
edgelist_from_base(
base,
window_threshold = 365,
count_option = "successive",
prob_params = c(0.0036, 1/365, 0.128),
condition = "dates",
noloops = TRUE,
nmoves_threshold = NULL,
flag_vars = NULL,
flag_values = NULL,
verbose = FALSE
)(data.table) A database of records of stays of subjects in facilities. The table should have at least the following columns:
subjectID (character) unique subject identifier
facilityID (character) unique facility identifier
admDate (POSIXct) date of admission in the facility
disDate (POSIXct) date of discharge of the facility
(integer) A number of days. If two stays of a subject at two facilities occurred within this window, this constitutes a connection between the two facilities (given that potential other conditions are met).
(character) How to count connections. Options are "successive", "probability" or "all". See details.
(vector of numeric) Three numerical values to calculate the probability that a movement causes an introduction from hospital A to hospital B. See Donker T, Wallinga J, Grundmann H. (2010) <doi:10.1371/journal.pcbi.1000715> for more details. For use with count_option="probability". prob_params[1] is the rate of acquisition in hospital A (related to LOS in hospital A). Default: 0.0036 prob_params[2] is the rate of loss of colonisation (related to time between admissions). Default: 1/365 prob_params[4] is the rate of transmission to other patients in hospital B (related to LOS in hospital B). Default: 0.128
(character) Condition(s) used to decide what constitutes a connection. Can be "dates", "flags", or "both". See details.
(boolean). Should transfers within the same nodes (loops) be kept or set to 0. Defaults to TRUE, removing loops (setting matrix diagonal to 0).
(numeric) A threshold for the minimum number of subject transfer between two facilities. Set to NULL to deactivate, default to NULL.
(list) Additional variables that can help flag a transfer, besides the dates of admission and discharge. Must be a named list of two character vectors which are the names of the columns that can flag a transfer: the column that can flag a potential origin, and the column that can flag a potential target. The list must be named with "origin" and "transfer". Eg: list("origin" = "var1", "target" = "var2"). See details.
(list) A named list of two character vectors which contain the values of the variables in flag_var that are matched to flag a potential transfer. The list must be named with "origin" and "transfer". The character vectors might be of length greater than one. Eg: list("origin" = c("value1", "value2"), "target" = c("value2", "value2")). The values in 'origin' and 'target' are the values that flag a potential origin of a transfer, or a potential target, respectively. See details.
TRUE to print computation steps
A list of two data.tables, which are the edgelists. One in long format (el_long), and one aggregated by pair of nodes (el_aggr).
The edgelist contains the information on the connections between nodes of the network, that is the movements of subjects between facilities. The edgelist can be in two different formats: long or aggregated. In long format, each row corresponds to a single movement between two facilities, therefore only two columns are needed, one containing the origin facilities of a movement, the other containing the target facilities. In aggregated format, the edgelist is aggregated by unique pairs of origin-target facilities.
mydb <- create_fake_subjectDB(n_subjects = 100, n_facilities = 10)
myBase <- checkBase(mydb)
#> Checking for missing values...
#> Checking for duplicated records...
#> Removed 0 duplicates
#> Done.
edgelist_from_base(myBase)
#> $el_aggr
#> origin target N
#> 1: f01 f02 1
#> 2: f01 f03 1
#> 3: f01 f04 3
#> 4: f01 f06 5
#> 5: f01 f07 2
#> 6: f01 f08 1
#> 7: f02 f01 1
#> 8: f02 f03 3
#> 9: f02 f04 2
#> 10: f02 f05 3
#> 11: f02 f06 2
#> 12: f02 f07 1
#> 13: f02 f08 1
#> 14: f02 f09 1
#> 15: f02 f10 3
#> 16: f03 f01 3
#> 17: f03 f02 2
#> 18: f03 f04 1
#> 19: f03 f05 1
#> 20: f03 f06 2
#> 21: f03 f07 1
#> 22: f03 f08 2
#> 23: f03 f09 1
#> 24: f03 f10 3
#> 25: f04 f01 4
#> 26: f04 f02 2
#> 27: f04 f03 1
#> 28: f04 f05 1
#> 29: f04 f06 1
#> 30: f04 f07 5
#> 31: f04 f08 1
#> 32: f04 f09 3
#> 33: f05 f01 1
#> 34: f05 f02 1
#> 35: f05 f04 1
#> 36: f05 f06 1
#> 37: f05 f07 2
#> 38: f05 f08 1
#> 39: f05 f09 2
#> 40: f05 f10 2
#> 41: f06 f01 1
#> 42: f06 f02 1
#> 43: f06 f03 2
#> 44: f06 f04 2
#> 45: f06 f05 3
#> 46: f06 f07 1
#> 47: f06 f08 4
#> 48: f06 f09 1
#> 49: f06 f10 1
#> 50: f07 f01 2
#> 51: f07 f02 1
#> 52: f07 f03 4
#> 53: f07 f04 2
#> 54: f07 f06 1
#> 55: f07 f08 2
#> 56: f07 f10 2
#> 57: f08 f01 2
#> 58: f08 f02 2
#> 59: f08 f03 3
#> 60: f08 f04 1
#> 61: f08 f05 1
#> 62: f08 f07 1
#> 63: f08 f10 3
#> 64: f09 f02 3
#> 65: f09 f03 1
#> 66: f09 f04 1
#> 67: f09 f06 5
#> 68: f09 f08 1
#> 69: f09 f10 1
#> 70: f10 f01 1
#> 71: f10 f02 3
#> 72: f10 f03 2
#> 73: f10 f04 3
#> 74: f10 f05 2
#> 75: f10 f06 2
#> 76: f10 f07 2
#> 77: f10 f08 1
#> origin target N
#>
#> $el_long
#> sID origin target
#> 1: s053 f01 f02
#> 2: s025 f01 f03
#> 3: s040 f01 f04
#> 4: s043 f01 f04
#> 5: s057 f01 f04
#> ---
#> 142: s060 f10 f06
#> 143: s095 f10 f06
#> 144: s014 f10 f07
#> 145: s024 f10 f07
#> 146: s070 f10 f08
#>