G - MPX NYC: Results

G.1 People

Race and gender identity

Code
targets::tar_read(plotdata_racegender) |>  
  plot_bar() +
  theme_mpxnyc_bar() +
  scale_axis_mpxnyc() +
  scale_fill_mpxnyc(name = "Race / gender") +
  theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_race)  |>
  plot_bar()  +
  theme_mpxnyc_bar() +
  scale_axis_mpxnyc() +
  scale_fill_mpxnyc(name = "Race") +
  theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_genderid) |>  
  plot_bar() +
  theme_mpxnyc_bar() +
  scale_axis_mpxnyc("MPX NYC sample proportion") +
  scale_fill_mpxnyc(name = "Gender\nmodality") +
    theme_mpxnyc_nomargin()

Age

How old are you?

Code
  targets::tar_read(plotdata_age) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Age group") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_age_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Sexual orientation

What is your sexual orientation?

Code
targets::tar_read(plotdata_sexorientation)  |>
  plot_bar()  +
  theme_mpxnyc_bar() +
  scale_axis_mpxnyc() +
  scale_fill_mpxnyc(name = "Sexual orientation") +
  theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_sexorientation_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Recruitment channel

Code
targets::tar_read(plotdata_channel) |>
  plot_bar()  +
  theme_mpxnyc_bar() +
  scale_axis_mpxnyc() +
  scale_fill_mpxnyc(name = "Recruitment\nchannel") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_channel_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

PrEP use

Are you on PrEP?

Code
  targets::tar_read(plotdata_hivprep) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Age group") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_hivprep_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

HIV status

What is your HIV status?

Code
  targets::tar_read(plotdata_hivstatus) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "HIV status") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_hivstatus_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

HIV viral suppression

Have you been told that your viral load is suppressed or undetectable?

Code
  targets::tar_read(plotdata_hivsuppressed) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "HIV status") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_hivsuppressed_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Mpox medical care

Did you receive care by a medical provider for your symptoms?

Code
  targets::tar_read(plotdata_mpoxcare) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Mpox care") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_mpoxcare_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Mpox testing

In the past 4 weeks, did you receive testing for mpox?

Code
  targets::tar_read(plotdata_mpoxtest) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Mpox test") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_mpoxtest_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Recent positive COVID-19 test

In the past 4 weeks, did you test positive for COVID-19?

Code
  targets::tar_read(plotdata_covidtestpositive) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Response") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_covidtestpositive_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

STI symptoms

Number of symptoms (calculated)

Code
  targets::tar_read(plotdata_stisymptoms) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "HIV status") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_stisymptoms_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Recent contact with Queer and Trans friends

How many queer and trans friends do you have who are important to you for any reason? Count only those you have been in touch with over the past 4 weeks.

Code
  targets::tar_read(plotdata_countfriends) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Count") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_countfriends_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Recent one-on-one physical contact

How many individuals have you had prolonged physical contact (but no sexual contact) with in the past 4 weeks, excluding group settings?

Code
  targets::tar_read(plotdata_countphysical) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Count") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_countphysical_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Recent one-on-one sexual contact

How many individuals have you had sex with in the past 4 weeks, excluding group sex partners?

Code
  targets::tar_read(plotdata_countsex) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Count") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_countsex_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Recent physical or sexual contact in group setting

Over the past 4 weeks, have you had sex with two or more people at the same time or had close physical contact with multiple people at the same time? (like at a party, sport game, concert, show)

Code
  targets::tar_read(plotdata_groupsex) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Count") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_groupsex_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

Hookup travel time

By the way, how long are you willing to travel to hook up?

Code
  targets::tar_read(plotdata_traveltime) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Place type") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_traveltime_racegender) |>
  plot_radar_grid()  +
  scale_radial_mpxnyc() +
  scale_fill_mpxnyc(name = "") +
  theme_mpxnyc_radar_people() +
  theme_mpxnyc_nomargin()

G.2 Gathering community districts

Gathering locations

Code
targets::tar_read(plotdata_place_census_overall)  |> 
  plot_placecensus_map() +
  scale_fill_mpxnyc(name = "", na.translate = FALSE, option = "light") +
  theme_mpxnyc_blank(
                      legend.position = "bottom", 
                      strip.text.y.left = ggplot2::element_text(size = 14, angle = 65, margin = ggplot2::margin(0,0,0,0), color = "#636363"),
                      strip.clip = "off"
                      )

Community districts reported by participants as places of residence or gathering were ranked by frequency and divided into three groups, each representing approximately one third of all reported locations. Group A contains the most frequently reported districts, followed by Groups B and C.
Code
targets::tar_read(plotdata_place_census_racegender)  |> 
  plot_placecensus_map() +
  scale_fill_mpxnyc(name = "", na.translate = FALSE, option = "light") +
  theme_mpxnyc_blank(
                      legend.position = "bottom", 
                      strip.text.y.left = ggplot2::element_text(size = 14, angle = 65, margin = ggplot2::margin(0,0,0,0), color = "#636363"),
                      strip.clip = "off"
                      )

Community districts reported by participants in the race and gender group of interest as places of residence or gathering were ranked by frequency and divided into three groups, each representing approximately one third of all reported locations. Group A contains the most frequently reported districts, followed by Groups B and C.

Gathering type

Code
  targets::tar_read(plotdata_placetype) |>
    plot_bar() +
    theme_mpxnyc_bar() +
    scale_axis_mpxnyc() +
    scale_fill_mpxnyc(name = "Place type") +
    theme_mpxnyc_nomargin()

Code
targets::tar_read(plotdata_placetype_placesex) |>
  dplyr::mutate(proportion = abs(proportion)) |>
  plot_radar_stratified() +
    ggplot2::coord_polar() +
  scale_axis_mpxnyc() +
  ggplot2::scale_y_continuous(limits = c(-0.3, 0.84)) +
  scale_fill_mpxnyc(name = "") +
  ggplot2::geom_label(ggplot2::aes(label = scales::percent(proportion, accuracy = 1), x = level, y = 0.5 ), border.color = "white", label.size = 0, size = 3.5) +
  theme_mpxnyc_bar_places(
      plot.margin = ggplot2::unit(c(0,0,0,0), "cm"), 
      panel.spacing = ggplot2::unit(0, "cm"),
      legend.position = "bottom",
      panel.grid.major.y = ggplot2::element_blank(),
      panel.grid.major.x = ggplot2::element_blank(),
      axis.text.x = ggplot2::element_blank(),
      strip.text.y.left = ggplot2::element_text(angle = 90)
      )
Figure G.1: MPX NYC contact venue type by distance from home and sexual contact
Code
targets::tar_read(plotdata_placetype_distancefromhome) |>
  dplyr::mutate(proportion = abs(proportion)) |>
  plot_radar_stratified() +
    ggplot2::coord_polar() +
  scale_axis_mpxnyc() +
  ggplot2::scale_y_continuous(limits = c(-0.3, 0.84)) +
  scale_fill_mpxnyc(name = "") +
  ggplot2::geom_label(ggplot2::aes(label = scales::percent(proportion, accuracy = 1), x = level, y = 0.5 ), border.color = "white", label.size = 0, size = 3.5) +
  theme_mpxnyc_bar_places(
      plot.margin = ggplot2::unit(c(0,0,0,0), "cm"), 
      panel.spacing = ggplot2::unit(0, "cm"),
      legend.position = "bottom",
      panel.grid.major.y = ggplot2::element_blank(),
      panel.grid.major.x = ggplot2::element_blank(),
      axis.text.x = ggplot2::element_blank(),
      strip.text.y.left = ggplot2::element_text(angle = 90)
      )
Figure G.2: MPX NYC contact venue type by distance from home and sexual contact
Code
targets::tar_read(plotdata_placetype_bar_grid) |>
  dplyr::mutate(proportion = abs(proportion)) |>
  plot_bar_stratified2() +
    ggplot2::coord_polar() +
  scale_axis_mpxnyc() +
  ggplot2::scale_y_continuous(limits = c(-0.3, 0.84)) +
  scale_fill_mpxnyc(name = "") +
  ggplot2::geom_label(ggplot2::aes(label = scales::percent(proportion, accuracy = 1), x = level, y = 0.5 ), border.color = "white", label.size = 0, size = 3.5) +
  theme_mpxnyc_bar_places(
      plot.margin = ggplot2::unit(c(0,0,0,0), "cm"), 
      panel.spacing = ggplot2::unit(0, "cm"),
      legend.position = "bottom",
      panel.grid.major.y = ggplot2::element_blank(),
      panel.grid.major.x = ggplot2::element_blank(),
      axis.text.x = ggplot2::element_blank(),
      strip.text.y.left = ggplot2::element_text(angle = 90)
      )
Figure G.3: MPX NYC contact venue type by distance from home and sexual contact
Code
targets::tar_read(plotdata_placetype_distancefromhome_placeSex)  |>
  draw_table_3("Venue type by home distance and sexual contact")
Venue type by home distance and sexual contact
(MPX NYC, 2022)
N % (CI)
Same Community District - Did not have sex
Concert/Theatre/Show 5 12% (3-23)
Dance Party 17 40% (25-56)
Dark Room/Sex Party 3 7% (2-16)
Private Residence 10 24% (11-39)
Something Else 6 14% (5-25)
Sport Game 1 2% (2-9)
Same Community District - Had sex
Dance Party 6 4% (1-8)
Dark Room/Sex Party 8 6% (2-10)
Private Residence 120 83% (77-89)
Something Else 10 7% (3-11)
Same Borough - Did not have sex
Concert/Theatre/Show 35 30% (21-40)
Dance Party 43 37% (29-47)
Dark Room/Sex Party 3 3% (1-6)
Private Residence 10 9% (4-14)
Something Else 21 18% (11-26)
Sport Game 4 3% (1-7)
Same Borough - Had sex
Concert/Theatre/Show 1 1% (1-3)
Dance Party 13 11% (6-17)
Dark Room/Sex Party 19 17% (10-24)
Private Residence 63 55% (46-65)
Something Else 18 16% (10-22)
Different Borough - Did not have sex
Concert/Theatre/Show 23 22% (14-30)
Dance Party 50 47% (37-56)
Dark Room/Sex Party 4 4% (1-8)
Private Residence 8 8% (3-14)
Something Else 13 12% (6-19)
Sport Game 8 8% (3-13)
Different Borough - Had sex
Concert/Theatre/Show 3 3% (1-7)
Dance Party 14 15% (8-22)
Dark Room/Sex Party 25 27% (18-36)
Private Residence 39 41% (30-53)
Something Else 12 13% (6-21)
Sport Game 1 1% (1-4)

G.3 Spatial mixing

Age

Code
targets::tar_read(plotdata_age_mixing_matrix) |>
  plot_matrix_mixing() +
  scale_fill_mpxnyc_gradient("Spatial\nmixing\ncoefficient", labels = scales::label_percent(), breaks = c(-0.5, 0, 0.5, 1), limits = c(-0.5, 1)) +
  scale_color_mpxnyc_gradient() +
  ggplot2::scale_alpha_discrete(guide = "none") +
  theme_mpxnyc_mixing()
Figure G.4: Spatial mixing matrix by age. The spatial mixing ratio measures the extent to which members of one age subgroup share community districts with members of another relative to chance. Values greater than 1 indicate more mixing than expected, whereas values between 0 and 1 indicate less mixing than expected.

Sexual orientation

Code
targets::tar_read(plotdata_sexorientation_mixing_matrix) |>
  dplyr::filter(ego_level != "Something Else", alter_level != "Something Else") |> 
  plot_matrix_mixing() +
  scale_fill_mpxnyc_gradient("Spatial\nmixing\ncoefficient", labels = scales::label_percent(), breaks = c(-0.5, 0, 0.5, 1), limits = c(-0.5,  1.2)) +
  scale_color_mpxnyc_gradient() +
  ggplot2::scale_alpha_discrete(guide = "none") +
  theme_mpxnyc_mixing()
Figure G.5: Spatial mixing matrix by sexual orientation. The spatial mixing ratio measures the extent to which members of one sexual orientation subgroup share community districts with members of another subgroup relative to chance. Values greater than 1 indicate more mixing than expected, whereas values between 0 and 1 indicate less mixing than expected.

Race and gender modality

Code
targets::tar_read(plotdata_racegender_mixing_matrix) |>
    dplyr::filter(ego_level != "Another demographic", alter_level != "Another demographic") |> 
  plot_matrix_mixing() +
  scale_fill_mpxnyc_gradient("Spatial\nmixing\ncoefficient", labels = scales::label_percent(), breaks = c(-2, 0,  2), limits = c(-2, 2)) +
  scale_color_mpxnyc_gradient() +
  ggplot2::scale_alpha_discrete(guide = "none") +
  theme_mpxnyc_mixing()
Figure G.6: Spatial mixing matrix by race and gender. The spatial mixing ratio measures the extent to which members of one race and gender subgroup share community districts with members of another relative to chance. Values greater than 1 indicate more mixing than expected, whereas values between 0 and 1 indicate less mixing than expected.

`