oregan-heterogeneous-transmission/ProbChainSizeOne.Rmd at main · DrakeLab/oregan-heterogeneous-transmission · GitHub

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---
title: "Probability of chain size 1"
output: html_document
date: "2025-02-13"
---

## Probability of chain size of one

```{r, warning=FALSE, message = FALSE}
library(tidyverse)
library(egg)


# results
dat <- expand.grid(p = seq(0,1, 0.01),
                   delta = 9,
                   R0D = 1.1,
                   k = 4,
                   model = c("Poisson", "Negative binomial") ,
                   version = c("mixture", "standard")
                   ) %>%
  mutate(Probability = case_when(model == "Poisson" & version == "mixture" ~
                                   p*exp(-(R0D + delta))+(1-p)*exp(-(R0D)),
                                 model == "Poisson" & version == "standard" ~
                                   exp(-(R0D + p*delta)),
                                 model == "Negative binomial" & version == "mixture" ~
                                   p*(k/(k + R0D + delta))^k + (1 - p)* (k/(k + R0D))^k,
                                 model == "Negative binomial" & version == "standard" ~
                                   (k/(k + R0D + p*delta))^k
                                 ))

ymax <- 0.5

poisson_colors <- c(scales::col2hcl("#226e83", l = 40), # dark blue
                    scales::col2hcl("#226e83", l = 70)) # light blue
negbin_colors <- c(scales::col2hcl("#e2908c", l = 40), # dark red
                    scales::col2hcl("#e2908c", l = 70)) # light red


fig_ProbChainOne_a <- dat %>% filter(model == "Poisson") %>%
  ggplot(aes(x = p, y = Probability, color = version)) +
    geom_line() +
    scale_color_manual(values = poisson_colors) +
    expand_limits(y = ymax) +
    xlab(expression(paste("fraction of population ", italic("p"), " in high contact group"))) +
    ylab(expression(paste("probability of chain size 1"))) +
    guides(color = guide_legend(position = "inside", title = NULL)) +
    annotate("text", label = "Poisson",
             x = 0, y = Inf, vjust = 1.5, hjust = 0, size = 3.5) +
    theme_minimal() +
    theme(panel.border = element_rect(color = "darkgrey", fill = NA, linewidth = 1),
          plot.margin = margin(l = 24, unit = "pt"),
          legend.position.inside = c(.95, .95),
          legend.justification.inside = c(1, 1))

fig_ProbChainOne_b <- dat %>% filter(model == "Negative binomial") %>%
  ggplot(aes(x = p, y = Probability, color = version)) +
    geom_line() +
    scale_color_manual(values = negbin_colors) +
    expand_limits(y = ymax) +
    xlab(expression(paste("fraction of population ", italic("p"), " in high contact group"))) +
    ylab(expression(paste("probability of chain size 1"))) +
    guides(color = guide_legend(position = "inside", title = NULL)) +
    annotate("text", label = "Negative binomial",
             x = 0, y = Inf, vjust = 1.5, hjust = 0, size = 3.5) +
    theme_minimal() +
    theme(panel.border = element_rect(color = "darkgrey", fill = NA, linewidth = 1),
          plot.margin = margin(l = 24, r = 12, unit = "pt"),
          legend.position.inside = c(.95, .95),
          legend.justification.inside = c(1, 1))

fig_ProbChainOne <- ggarrange(
    fig_ProbChainOne_a +
      labs(title="a") +
      theme(plot.margin = margin(b = 1, t = 1),
            axis.title.x = element_text(size=9),
            axis.title.y = element_text(size=10),
            legend.text = element_text(size=8)),
    fig_ProbChainOne_b +
      labs(title="b") +
      theme(axis.title.x = element_text(size=9),
            axis.title.y = element_blank(),
            legend.text=element_text(size=8)),
    nrow = 1, ncol = 2
    )
ggsave("fig_ProbChainOne.pdf", fig_ProbChainOne, height=8, width=14.5, units="cm")

```