rebase oropouche-analysis branch

.gitignore

@@ -4,14 +4,19 @@
 .Ruserdata
 priority-pathogens.Rproj
 src/*.csv
-src/*/*.csv
-src/*/*/*.csv
 src/*/*.png
+src/*/*.rds
 src/*/lassa_functions.R
 pathway
 src/db_extraction/utils.R
 .Renviron
 Renviron
+src/*/*/.shp
+src/*/*/.shx
+src/*/*/.cpg
+src/*/*/.dbf
+src/*/*/.prj
+src/zika_serop/shapefile/*
 
 # ---VVV--- added by orderly ---VVV----------------
 # Don't manually edit content between these markers

DESCRIPTION

@@ -13,6 +13,7 @@ Authors@R: c(
     person("Gina", "Cuomo-Dannenburg", role = "aut", comment = c(ORCID = "0000-0001-6821-0352")),
     person("Ruth", "McCabe", role = "aut", comment = c(ORCID = "0000-0002-6368-9103")),
     person("Kelly", "McCain", role = "aut", comment = c(ORCID = "0000-0003-2393-2217")),
+    person("Anna", "Vicco", role = "aut", comment = c(ORCID = "0000-0002-6555-3090")), 
     person("Patrick", "Doohan", role = "aut", comment = c(ORCID = "0000-0001-8076-1106")),
     person("Tristan", "Naidoo", role = "aut", comment = c(ORCID = 0000-0001-9970-2421)))
 Description: A live view of a the systematic literature reviews conducted by the Pathogen Epidemiology Review Group (PERG). The data in these plots come from PERG's epireview package, which contains the latest available open access pathogen data from the group. 
@@ -22,14 +23,17 @@ Imports:
     estmeansd,
     flextable,
     ggforce,
+    ggpattern,
     ggplot2,
     ggrepel,
     ggsci,
     ggspatial,
+    gpkg,
     gt,
     grid,
     gridExtra,
     harrypotter,
+    maps,
     meta,
     metafor,
     mixdist,
@@ -42,9 +46,11 @@ Imports:
     rmarkdown,
     rnaturalearth,
     rnaturalearthdata,
+    RSQLite,
     scales,
     sf,
     stringr,
+    tidygeocoder,
     tidyverse,
     tm,
     webshot2

R/zika_maps.R

@@ -0,0 +1,114 @@
+library(ggplot2)
+library(sf)
+library(rnaturalearth)
+library(gpkg)
+library(RSQLite)
+library(ggrepel)
+
+parameters <- readRDS("P:/Zika/priority-pathogens/archive/db_compilation/20250205-144757-57dcf554/parameters.rds")
+outbreaks <- readRDS("P:/Zika/priority-pathogens/archive/db_compilation/20250205-144757-57dcf554/outbreaks.rds")
+
+world <- ne_countries(scale = 'medium', returnclass = 'sf')
+# 
+# world <- geopackage('data/gadm_410-levels.gpkg')
+# 
+outbreaks_agg <- outbreaks %>%
+  mutate(outbreak_country = case_when(
+    outbreak_country == 'France (Martinique)' ~ "France",
+    TRUE ~ outbreak_country
+  )) %>%
+  group_by(covidence_id, outbreak_country) %>%
+  count() %>%
+  group_by(outbreak_country) %>%
+  count()
+
+out_sf <- world %>%
+  left_join(outbreaks_agg, by = c('admin' = 'outbreak_country')) %>%# by.y ="outbreak_country", by.x = 'sovereignt')
+  mutate(admin = case_when(
+    admin == 'Federated States of Micronesia' ~ "Micronesia",
+    TRUE ~ admin
+  ))
+
+out_plt <- ggplot() +
+  geom_sf(data = out_sf, lwd = 0.3, col = "grey30", aes(fill = n)) +
+  scale_fill_viridis_c(option = 'plasma', direction = -1, na.value = 'grey80') +
+  theme_light() +
+  theme(axis.text = element_blank()) +
+  labs(fill = 'Number of papers\nreporting outbreaks',
+       x = '',
+       y = '') +
+  geom_label_repel(data = out_sf %>% filter(!is.na(n)),
+                   aes(x=label_x,y=label_y,label=paste0(admin,": ",n), 
+                   fontface = "bold"), size = 2,
+                   max.overlaps = 50,
+                   label.padding = 0.2) +
+  coord_sf(xlim=c(-180,180), ylim=c(-60,90))     # cut out antarctica
+
+
+
+# Sero plot 
+sero_all <- parameters %>%
+  filter(parameter_type =='Seroprevalence - IgG' | grepl("PRNT", parameter_type))%>%
+  group_by(covidence_id, population_country) %>%
+  count() %>%
+  group_by(population_country) %>%
+  count() %>%
+  mutate(population_country = case_when(
+    population_country == 'DRC' ~ "Democratic Republic of the Congo",
+    TRUE ~ population_country
+  ))
+
+sero_all_sf <- world %>%
+  left_join(sero_all, by = c('admin' = 'population_country')) %>%# by.y ="outbreak_country", by.x = 'sovereignt')
+  mutate(admin = case_when(
+    admin == 'Federated States of Micronesia' ~ "Micronesia",
+    admin == 'Democratic Republic of the Congo' ~ "DRC",
+    TRUE ~ admin
+  ))
+
+sero_all <- ggplot() +
+  geom_sf(data = sero_all_sf, lwd = 0.3, col = "grey30", aes(fill = n)) +
+  scale_fill_viridis_c(option = 'plasma', direction = -1, na.value = 'grey80') +
+  theme_light() +
+  labs(fill = 'Number of papers\nreporting IgG or PRNT',
+       x = '',
+       y = '') +
+  theme(axis.text = element_blank()) +
+  coord_sf(xlim=c(-180,180), ylim=c(-60,90))
+
+
+# general pop only 
+sero_gen <- parameters %>%
+  filter(parameter_type =='Seroprevalence - IgG' | grepl("PRNT", parameter_type))%>%
+  filter(population_group == 'General population' & population_sample_type == "Population based") %>%
+  group_by(covidence_id, population_country) %>%
+  count() %>%
+  group_by(population_country) %>%
+  count() %>%
+  mutate(population_country = case_when(
+    population_country == 'DRC' ~ "Democratic Republic of the Congo",
+    TRUE ~ population_country
+  ))
+
+sero_gen_sf <- world %>%
+  left_join(sero_gen, by = c('admin' = 'population_country')) %>%# by.y ="outbreak_country", by.x = 'sovereignt')
+  mutate(admin = case_when(
+    admin == 'Federated States of Micronesia' ~ "Micronesia",
+    admin == 'Democratic Republic of the Congo' ~ "DRC",
+    TRUE ~ admin
+  ))
+
+sero_gen <- ggplot() +
+  geom_sf(data = sero_gen_sf, lwd = 0.3, col = "grey30", aes(fill = n)) +
+  scale_fill_viridis_c(option = 'plasma', direction = -1, na.value = 'grey80') +
+  theme_light() +
+  labs(fill = 'Number of papers\nreporting IgG or PRNT',
+       x = '',
+       y = '') +
+  theme(axis.text = element_blank()) +
+  coord_sf(xlim=c(-180,180), ylim=c(-60,90))
+
+
+ggsave("data/zika_plots/outbreaks.png", out_plt)
+ggsave("data/zika_plots/sero_all.png", sero_all)
+ggsave("data/zika_plots/sero_general.png", sero_gen)