-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathmyFun_readTransPairs.R
146 lines (115 loc) · 5.7 KB
/
myFun_readTransPairs.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
## Prepare calendar day -> No. of days since 2020/01/01
Get_calndr_str <- function(days_vec, tar_mth_str, tar_yr_str) {
tar_date_str = sapply(
days_vec,
function (tar_date, mth, yr) paste(yr, mth, toString(tar_date), sep = "/"),
mth = tar_mth_str,
yr = tar_yr_str
)
return( tar_date_str );
}
Get_ndays_from_20200101 <- function( tar_yr_str ) {
# Jan 01 to Jan 31
days_vec1 = seq(1, 31);
date_mth1 = Get_calndr_str(days_vec1, "1", tar_yr_str);
# Feb 01 to Feb 29
days_vec2 = seq(1, 29);
date_mth2 = Get_calndr_str(days_vec2, "2", tar_yr_str);
days_vec2 = days_vec2 + 31;
df_uniq_date = tibble(
nday = c(days_vec1, days_vec2),
str = as.Date( c(date_mth1, date_mth2) )
)
return( df_uniq_date )
}
Get_onset_day <- function(onset_date, df_uniq_date) {
tar_vec = sapply(
onset_date,
function (tar_date, df_uniq_date) {
if (str_detect(tar_date, "unknown")) {
tar_nday = 1000000;
} else if (str_detect(tar_date, "local")) {
tar_nday = 200000;
} else {
tar_nday = df_uniq_date$nday[ df_uniq_date$str == as.Date(tar_date) ];
}
return(tar_nday)
},
df_uniq_date = df_uniq_date
)
return(tar_vec)
}
Set_uniq_caseID <- function( tarID_vec ) {
result_vec = unname( sapply( tarID_vec, function (tar_id) paste0("-", tar_id, "-") ) );
return(result_vec)
}
#### Read raw transmission pair data ####
## Transform into "linelist" and "contacts" as package "epicontacts" (http://www.repidemicsconsortium.org/epicontacts/)
Read_TransPairs <- function( file_name ) {
df_uniq_date = Get_ndays_from_20200101( "2020" ); # Calender dates -> No. of days since 2020/01/01
raw_linelist <- read_csv( file_name );
raw_linelist$infector_id <- Set_uniq_caseID( raw_linelist$infector_id );
raw_linelist$infectee_id <- Set_uniq_caseID( raw_linelist$infectee_id );
tar_linelist <- raw_linelist %>% filter(
!str_detect(raw_linelist$infector_onsetDate, "unknown" ) &
!str_detect(raw_linelist$infectee_onsetDate, "unknown" )
)
tar_linelist_p1 <- tar_linelist
## Get onset times (days) of infector and infectee -----------------------------
tar_linelist_p1$infector_onsetDate <- unname( Get_onset_day(tar_linelist_p1$infector_onsetDate, df_uniq_date) );
tar_linelist_p1$infectee_onsetDate <- unname( Get_onset_day(tar_linelist_p1$infectee_onsetDate, df_uniq_date) );
# infectors' onset between 9 Jan 2020 and 13 Feb 2020
tar_linelist = tar_linelist_p1 %>% filter( infector_onsetDate >= 9 & infector_onsetDate < 45 );
## Isolation delay: time delay from onset to isolation of infector --------------------------
tar_linelist$infector_isolateDate_beforeSymptom <- unname( Get_onset_day( tar_linelist$infector_isolateDate_beforeSymptom, df_uniq_date ) );
tar_linelist$infector_isolateDate_afterSymptom <- unname( Get_onset_day( tar_linelist$infector_isolateDate_afterSymptom, df_uniq_date ) );
tar_linelist$infector_firstHospitalVisit <- unname( Get_onset_day( tar_linelist$infector_firstHospitalVisit, df_uniq_date ) );
tar_linelist$infector_labConfirmDate <- unname( Get_onset_day( tar_linelist$infector_labConfirmDate, df_uniq_date ) );
date_isol_vec = mapply(
function (A, B) min(A, B),
A = tar_linelist$infector_isolateDate_beforeSymptom,
B = tar_linelist$infector_isolateDate_afterSymptom
)
tar_linelist <- tar_linelist %>% mutate(
infector_isolateDelay = date_isol_vec - tar_linelist$infector_onsetDate
)
## Isolation delay: time delay from onset to isolation of infectee --------------------------
tar_linelist$infectee_isolateDate_beforeSymptom <- unname( Get_onset_day( tar_linelist$infectee_isolateDate_beforeSymptom, df_uniq_date ) );
tar_linelist$infectee_isolateDate_afterSymptom <- unname( Get_onset_day( tar_linelist$infectee_isolateDate_afterSymptom, df_uniq_date ) );
tar_linelist$infectee_firstHospitalVisit <- unname( Get_onset_day( tar_linelist$infectee_firstHospitalVisit, df_uniq_date ) );
date2_isol_vec = mapply(
function (A, B) min(A, B),
A = tar_linelist$infectee_isolateDate_beforeSymptom,
B = tar_linelist$infectee_isolateDate_afterSymptom
)
tar_linelist <- tar_linelist %>% mutate(
infectee_isolateDelay = date2_isol_vec - tar_linelist$infectee_onsetDate
)
#### Transform to linelist and contacts for "epicontact" ####
linelist = data.frame(
id = c( tar_linelist$infector_id, tar_linelist$infectee_id ),
age = c( tar_linelist$infector_age, tar_linelist$infectee_age ),
sex = c( tar_linelist$infector_sex, tar_linelist$infectee_sex ),
city_report = c( tar_linelist$infector_reportCity, tar_linelist$infectee_reportCity ),
city_infect = c( tar_linelist$infector_infectCity, tar_linelist$infectee_infectCity ),
date_onset = c( tar_linelist$infector_onsetDate, tar_linelist$infectee_onsetDate ),
delay_isol = c( tar_linelist$infector_isolateDelay, tar_linelist$infectee_isolateDelay )
)
linelist_uniq = distinct(linelist, id, .keep_all = T)
contacts = data.frame(
from = tar_linelist$infector_id,
to = tar_linelist$infectee_id,
date_onset_infector = tar_linelist$infector_onsetDate,
date_onset_infectee = tar_linelist$infectee_onsetDate,
serialInterval = tar_linelist$infectee_onsetDate - tar_linelist$infector_onsetDate,
is_household = tar_linelist$isHousehold,
delayIsol_infector = tar_linelist$infector_isolateDelay,
delayIsol_infectee = tar_linelist$infectee_isolateDelay
)
newlist = list(
"tar_linelist" = tar_linelist,
"linelist" = linelist_uniq,
"contacts" = contacts
)
return( newlist )
}