Plotting values in ggplot over time by group, with condition where one group is one line of the mean, and the other group as individual lines in R

Probably the easiest way is to separate the data based on the status of Intervention. I've generated a somewhat larger dummy dataset that should have a similar shape to the data you provided.

library(ggplot2)

set.seed(1234)

states <- rownames(USArrests)
intervened <- sample(states, 10)

df <- expand.grid(year = 2010:2015, state = states)
df$Intervention <- as.numeric(df$state %in% intervened)
df$rate <- cumsum(rnorm(nrow(df)))
head(df)
#>   year   state Intervention      rate
#> 1 2010 Alabama            0 -0.574740
#> 2 2011 Alabama            0 -1.121372
#> 3 2012 Alabama            0 -1.685824
#> 4 2013 Alabama            0 -2.575862
#> 5 2014 Alabama            0 -3.053054
#> 6 2015 Alabama            0 -4.051441

It's easier to separate the data if you need to handle these seperately while plotting. You can subset the data in the data argument of a layer. As I understood you wanted to plot states with Intervention == 1 individually, so we do that with the regular geom_line(). Then, we want to summarize all states with Intervention == 0 and to do that we use the stat_summary() function. We need to set a common group for the summarised data as we want to summarise over different states.

ggplot(df, aes(x = year, y = rate, group = state)) +
  geom_line(
    data = ~ subset(., Intervention == 1),
    aes(colour = state)
  ) +
  stat_summary(
    data = ~ subset(., Intervention == 0),
    aes(group = -1),
    fun.data = mean_se,
    geom = "line", size = 2
  )

^{Created on 2021-02-24 by the reprex package (v1.0.0)}

Follow up:

You'd need to repeat the stat_summary() layer for every geom. For example: adding a ribbon with mean +/- sd values:

  stat_summary(
    data = ~ subset(., Intervention == 0),
    aes(group = -1),
    fun.data = function(x) {
      mx <- mean(x)
      sd <- sd(x)
      data.frame(
        ymin = mx - sd,
        ymax = mx + sd
      )
    },
    geom = "ribbon", alpha = 0.5
  )

You can replace "ribbon" with "errorbar" if you prefer that.