## Look at incidence rates over time in the general population, and those effected directly by the policy change
GraphStudySpecIncRates <- StudySpecIncRates %>%
mutate(`Policy change (2005)` = ifelse(Year < 2005, 'Pre change', 'Post change') %>%
factor(levels = c('Pre change', 'Post change'))) %>%
mutate(CoB = CoB %>% relevel("UK born")) %>%
ggplot(aes(
x = Year,
y = Incidence,
colour = `Policy change (2005)`,
fill = `Policy change (2005)`
)) +
geom_pointrange(aes(ymin = Inc_LCI, ymax = Inc_UCI), fatten = 1.1, size = 1) +
geom_line(aes(group = `Policy change (2005)`), size = 0.8, alpha = 0.6) +
geom_vline(xintercept = 2004) +
scale_color_brewer(palette = "Dark2") +
labs(y = "Incidence rate (per 100,000)") +
PaperTheme() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
facet_grid(CoB ~ `Age group`, scale = 'free_y') +
theme(legend.position = "top")
## Look at average in cohorts between those Pre and post policy change
## Look at average in cohorts between those Pre and post policy change
## define the scale of incidence rates
AvgRestCohortVacInc <- RestCohortVacInc %>%
group_by(VacScheme, PolicyChange, Age, CoB) %>%
summarise(
Incidence = epi_conf(Cases, Population)$est * RateScale,
LCI = epi_conf(Cases, Population)$lower * RateScale,
UCI = epi_conf(Cases, Population)$upper * RateScale
) %>%
ungroup %>%
mutate(Cohort = case_when(VacScheme %in% "Universal school-age (14)"
& CoB %in% "UK born" &
PolicyChange %in% "Pre change" ~ "UNCUK14",
VacScheme %in% "Universal school-age (14)"
& CoB %in% "UK born" &
PolicyChange %in% "Post change" ~ "UCUK14",
VacScheme %in% "Targeted high-risk neonates (0)"
& CoB %in% "UK born" &
PolicyChange %in% "Pre change" ~ "TNCUKBirth",
VacScheme %in% "Targeted high-risk neonates (0)"
& CoB %in% "UK born" &
PolicyChange %in% "Post change" ~ "TCUKBirth",
VacScheme %in% "Universal school-age (14)"
& CoB %in% "Non-UK born" &
PolicyChange %in% "Pre change" ~ "UNCNUK14",
VacScheme %in% "Universal school-age (14)"
& CoB %in% "Non-UK born" &
PolicyChange %in% "Post change" ~ "UCNUK14",
VacScheme %in% "Targeted high-risk neonates (0)"
& CoB %in% "Non-UK born" &
PolicyChange %in% "Pre change" ~ "TNCNUKBirth",
VacScheme %in% "Targeted high-risk neonates (0)"
& CoB %in% "Non-UK born" &
PolicyChange %in% "Post change" ~ "TCNUKBirth"
) %>%
factor
)
## Exploratory plots
## Plot of average incidence in each cohort, for both Universal and targetted vaccination
## Rates shown are for the appropriate vaccinated popupalation
## Non-UK born are shown for comparision of trend only as they may not have been exposed to the scheme
## Year of eligibility is converted into a factor so that each year is treated independantly
GraphSumPolicyChangeChange <- AvgRestCohortVacInc %>%
filter(CoB %in% c('UK born', 'Non-UK born')) %>%
mutate(CoB = CoB %>% relevel("UK born"),
VacScheme = VacScheme %>%
relevel("Universal school-age (14)")) %>%
mutate(`Policy Change (2005)` = PolicyChange) %>%
drop_na(Incidence) %>%
ggplot(
aes(
x = Age,
y = Incidence,
shape = `Policy Change (2005)`,
colour = `Policy Change (2005)`,
group = `Policy Change (2005)`
)
) +
geom_pointrange(aes(min = LCI, max = UCI),
fatten = 2,
size = 1.05,
position = position_dodge(width = 0.3)) +
geom_line(position = position_dodge(width = 0.3), alpha = 0.6) +
facet_grid(facets = CoB ~ VacScheme, scales = 'free') +
scale_color_brewer(palette = "Dark2") +
PaperTheme() +
labs(y = "Incidence rate (per 100,000)") +
guides(shape = guide_legend(nrow = 2)) +
theme(legend.position = "top")
## Facetted by year for targeted vaccination of neonates
GraphTargetedPolicyChangeChange <- RestCohortVacInc %>%
filter(CoB %in% c('UK born', 'Non-UK born'),
VacScheme %in% 'Targeted high-risk neonates (0)') %>%
mutate(`Policy Change (2005)` = PolicyChange) %>%
ggplot(
aes(
x = Age,
y = Incidence,
colour = `Policy Change (2005)`,
group = `Policy Change (2005)`
)
) +
geom_pointrange(aes(min = Inc_LCI, max = Inc_UCI),
fatten = 1.5,
size = 1.05,
position = position_dodge(width = 0.4)) +
geom_line(position = position_dodge(width = 0.4), alpha = 0.6) +
scale_color_brewer(palette = "Dark2") +
facet_grid(facets = CoB ~ YearEligib, scales = 'free_y') +
PaperTheme() +
labs(y = "Incidence rate (per 100,000)") +
theme(legend.position = 'top')
## Facetted by year for universal vaccination of those at school-age
GraphUniversalPolicyChangeChange <- RestCohortVacInc %>%
filter(CoB %in% c('UK born', 'Non-UK born'),
VacScheme %in% 'Universal school-age (14)') %>%
mutate(`Policy Change (2005)` = PolicyChange) %>%
ggplot(
aes(
x = Age,
y = Incidence,
colour = `Policy Change (2005)`,
group = `Policy Change (2005)`
)
) +
geom_pointrange(aes(min = Inc_LCI, max = Inc_UCI),
fatten = 1.5,
size = 1.05,
position = position_dodge(width = 0.4)) +
geom_line(position = position_dodge(width = 0.4), alpha = 0.6) +
facet_grid(facets = CoB ~ YearEligib, scales = 'free_y') +
scale_color_brewer(palette = "Dark2") +
PaperTheme() +
labs(y = "Incidence rate (per 100,000)") +
theme(legend.position = 'top',
axis.text.x = element_text(angle = 90, hjust = 1))
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