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@actions-user
actions-user committed Jul 2, 2024
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Expand Up @@ -126,11 +126,13 @@ onset_to_death <- epiparameter::epidist_db(
#> To retrieve the citation use the 'get_citation' function
```

To simulate a line list for COVID-19 with an Poisson contact
distribution with a mean number of contacts of 2 and a probability of
infection per contact of 0.5, we use the `sim_linelist()` function. The
mean number of contacts and probability of infection determine the
outbreak reproduction number, if the resulting reproduction number is
To simulate a line list for COVID-19 with a Poisson contact distribution
with a mean number of contacts of 2 and a probability of infection per
contact of 0.5, we use the `sim_linelist()` function. As outlined in
@bjornstad2020a, the mean number of contacts ($k$) and probability of
infection ($\pi$) are combined into a transmission rate that, multiplied
by the infectious period ($1/\gamma$), determines the outbreak
reproduction number ($R_o$). If the resulting reproduction number is
around one it means we will likely get a reasonably sized outbreak (10 -
1,000 cases, varying due to the stochastic simulation).

Expand All @@ -156,20 +158,20 @@ linelist <- sim_linelist(
onset_to_death = onset_to_death
)
head(linelist)
#> id case_name case_type sex age date_onset date_admission outcome
#> 1 1 Rushdi al-Ishak probable m 35 2023-01-01 <NA> recovered
#> 2 2 Jeffrey Le confirmed m 43 2023-01-01 <NA> recovered
#> 3 3 Dominic Barringer suspected m 1 2023-01-01 <NA> recovered
#> 4 5 Tyler Kelley probable m 78 2023-01-01 <NA> recovered
#> 5 6 Carolyn Moore confirmed f 22 2023-01-01 <NA> recovered
#> 6 8 Cheyenne Sayavong confirmed f 28 2023-01-01 2023-01-04 died
#> id case_name case_type sex age date_onset date_admission outcome
#> 1 1 Wajdi al-Demian probable m 35 2023-01-01 <NA> recovered
#> 2 2 Raaid el-Diab confirmed m 43 2023-01-01 2023-01-07 recovered
#> 3 3 Nickolas Nault suspected m 1 2023-01-01 <NA> recovered
#> 4 5 Hee Kennedy confirmed m 78 2023-01-01 2023-01-03 died
#> 5 6 Hope Arshad suspected f 22 2023-01-01 2023-01-28 died
#> 6 8 Shanta Holiday probable f 28 2023-01-01 <NA> recovered
#> date_outcome date_first_contact date_last_contact ct_value
#> 1 <NA> <NA> <NA> NA
#> 2 <NA> 2022-12-30 2023-01-05 24
#> 2 <NA> 2022-12-30 2023-01-05 24.1
#> 3 <NA> 2022-12-30 2023-01-02 NA
#> 4 <NA> 2022-12-29 2023-01-02 NA
#> 5 <NA> 2023-01-01 2023-01-03 24
#> 6 2023-01-16 2023-01-03 2023-01-04 24
#> 4 2023-01-21 2022-12-29 2023-01-02 24.1
#> 5 2023-01-10 2023-01-01 2023-01-03 NA
#> 6 <NA> 2023-01-03 2023-01-04 NA
```

In this example, the line list is simulated using the default values
Expand All @@ -189,20 +191,20 @@ linelist <- sim_linelist(
outbreak_start_date = as.Date("2019-12-01")
)
head(linelist)
#> id case_name case_type sex age date_onset date_admission outcome
#> 1 1 Kiersten Matthews confirmed f 72 2019-12-01 <NA> recovered
#> 2 2 Omar Cruz confirmed m 85 2019-12-01 <NA> recovered
#> 3 3 Emilio Alvarado suspected m 24 2019-12-01 <NA> recovered
#> 4 4 Sonya Santiago confirmed f 67 2019-12-01 2019-12-03 recovered
#> 5 5 Michelle Brooks probable f 37 2019-12-02 <NA> recovered
#> 6 6 Anastasia Hamlin confirmed f 14 2019-12-02 <NA> recovered
#> id case_name case_type sex age date_onset date_admission outcome
#> 1 1 Kristiana Acheampong confirmed f 88 2019-12-01 <NA> recovered
#> 2 3 Jadeeda el-Abdalla confirmed f 8 2019-12-01 <NA> recovered
#> 3 4 Dominic Sandoval probable m 48 2019-12-01 <NA> recovered
#> 4 5 Zoe Johnson confirmed f 3 2019-12-01 <NA> recovered
#> 5 6 Breann Bruski probable f 25 2019-12-01 <NA> recovered
#> 6 7 Joseph Charley suspected m 57 2019-12-01 <NA> recovered
#> date_outcome date_first_contact date_last_contact ct_value
#> 1 <NA> <NA> <NA> 23.5
#> 2 <NA> 2019-11-30 2019-12-06 23.5
#> 3 <NA> 2019-11-30 2019-12-01 NA
#> 4 <NA> 2019-12-07 2019-12-09 23.5
#> 5 <NA> 2019-12-01 2019-12-04 NA
#> 6 <NA> 2019-12-01 2019-12-04 23.5
#> 1 <NA> <NA> <NA> 26.7
#> 2 <NA> 2019-11-30 2019-12-02 26.7
#> 3 <NA> 2019-11-30 2019-12-03 NA
#> 4 <NA> 2019-12-02 2019-12-04 26.7
#> 5 <NA> 2019-11-28 2019-12-04 NA
#> 6 <NA> 2019-12-05 2019-12-06 NA
```

To simulate a table of contacts of cases (i.e. to reflect a contact
Expand All @@ -215,26 +217,21 @@ contacts <- sim_contacts(
infectious_period = infectious_period,
prob_infection = 0.5
)
#> Warning: Number of cases exceeds maximum outbreak size.
#> Returning data early with 10176 cases and 20217 total contacts (including cases).
```

``` r
head(contacts)
#> from to age sex date_first_contact date_last_contact
#> 1 Brandon Byrnes Mustaba el-Wahba 14 m 2023-01-01 2023-01-03
#> 2 Brandon Byrnes Lonnie Williams 33 m 2022-12-31 2023-01-05
#> 3 Brandon Byrnes Robert Brown 34 m 2022-12-28 2023-01-02
#> 4 Brandon Byrnes Desiree Mabry 76 f 2023-01-03 2023-01-06
#> 5 Brandon Byrnes Salvador Trevino 73 m 2023-01-05 2023-01-07
#> 6 Desiree Mabry Gina Yu 90 f 2023-01-05 2023-01-06
#> was_case status
#> 1 N under_followup
#> 2 N lost_to_followup
#> 3 N under_followup
#> 4 Y case
#> 5 N under_followup
#> 6 N under_followup
#> from to age sex date_first_contact
#> 1 Munisa el-Kamal Alicia Topper 76 f 2023-01-05
#> 2 Munisa el-Kamal Donald Ramirez 24 m 2023-01-01
#> 3 Munisa el-Kamal Brittney Jarmond 7 f 2023-01-05
#> 4 Munisa el-Kamal Ramalaan el-Saadeh 57 m 2023-01-01
#> 5 Alicia Topper Cody Cohen 7 m 2023-01-02
#> 6 Alicia Topper Ashley Kohl 48 f 2022-12-31
#> date_last_contact was_case status
#> 1 2023-01-07 Y case
#> 2 2023-01-03 Y case
#> 3 2023-01-05 N under_followup
#> 4 2023-01-04 N unknown
#> 5 2023-01-04 Y case
#> 6 2023-01-03 Y case
```

If both the line list and contacts table are required, they can be
Expand All @@ -252,38 +249,38 @@ outbreak <- sim_outbreak(
onset_to_death = onset_to_death
)
head(outbreak$linelist)
#> id case_name case_type sex age date_onset date_admission outcome
#> 1 1 Annnees al-Nazir probable m 24 2023-01-01 <NA> recovered
#> 2 2 Muammar al-Miah probable m 46 2023-01-02 <NA> recovered
#> 3 4 Melina Tarin probable f 71 2023-01-02 <NA> recovered
#> 4 6 Alysh Lovejoy suspected f 13 2023-01-03 <NA> recovered
#> 5 9 Dylan Scanlon confirmed m 28 2023-01-03 <NA> recovered
#> 6 11 Nikolay Mcinnis suspected m 15 2023-01-03 <NA> recovered
#> id case_name case_type sex age date_onset date_admission outcome
#> 1 1 Okatomi Reish confirmed f 30 2023-01-01 <NA> recovered
#> 2 6 Angel Escalante confirmed m 83 2023-01-01 <NA> recovered
#> 3 8 Miqdaad el-Turay probable m 17 2023-01-01 <NA> recovered
#> 4 9 Jennifer Gonzalez confirmed f 74 2023-01-01 <NA> died
#> 5 10 Brendan Wu confirmed m 33 2023-01-01 2023-01-03 recovered
#> 6 12 Erminio Mandell probable m 24 2023-01-01 <NA> recovered
#> date_outcome date_first_contact date_last_contact ct_value
#> 1 <NA> <NA> <NA> NA
#> 2 <NA> 2023-01-04 2023-01-07 NA
#> 3 <NA> 2023-01-03 2023-01-05 NA
#> 4 <NA> 2023-01-04 2023-01-06 NA
#> 5 <NA> 2023-01-04 2023-01-07 25.6
#> 6 <NA> 2023-01-05 2023-01-06 NA
#> 1 <NA> <NA> <NA> 23.9
#> 2 <NA> 2023-01-01 2023-01-05 23.9
#> 3 <NA> 2022-12-31 2023-01-02 NA
#> 4 2023-01-21 2023-01-07 2023-01-08 23.9
#> 5 <NA> 2023-01-01 2023-01-01 23.9
#> 6 <NA> 2023-01-02 2023-01-05 NA
```

``` r
head(outbreak$contacts)
#> from to age sex date_first_contact date_last_contact
#> 1 Annnees al-Nazir Muammar al-Miah 46 m 2023-01-04 2023-01-07
#> 2 Annnees al-Nazir Siena Quimby 76 f 2022-12-27 2023-01-02
#> 3 Muammar al-Miah Melina Tarin 71 f 2023-01-03 2023-01-05
#> 4 Muammar al-Miah Destinee Embry 49 f 2023-01-01 2023-01-04
#> 5 Melina Tarin Alysh Lovejoy 13 f 2023-01-04 2023-01-06
#> 6 Alysh Lovejoy Andrew Knott 55 m 2023-01-03 2023-01-05
#> was_case status
#> 1 Y case
#> 2 N lost_to_followup
#> 3 Y case
#> 4 N under_followup
#> 5 Y case
#> 6 N under_followup
#> from to age sex date_first_contact
#> 1 Okatomi Reish Jesse Lynn 44 f 2023-01-04
#> 2 Okatomi Reish Joshua Rose 89 m 2023-01-05
#> 3 Okatomi Reish Wadee'a al-Rayes 11 f 2023-01-04
#> 4 Okatomi Reish Khaleel al-Hamady 19 m 2022-12-30
#> 5 Okatomi Reish Angel Escalante 83 m 2023-01-01
#> 6 Angel Escalante Burhaan el-Hashemi 87 m 2022-12-29
#> date_last_contact was_case status
#> 1 2023-01-05 N lost_to_followup
#> 2 2023-01-05 N unknown
#> 3 2023-01-05 N under_followup
#> 4 2023-01-03 N under_followup
#> 5 2023-01-05 Y case
#> 6 2023-01-02 N unknown
```

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