Start to add China example to other data sources, #151

vignettes/other-data-sources.Rmd

@@ -24,14 +24,14 @@ This vignette focuses on using other data sources with conmat.
 
 # Using `socialmixr`
 
-We can use some other functions from `socialmixr` to extract similar estimates for different populations in different countries.
+We can use some functions from `socialmixr` to extract similar estimates for different populations in different countries.
 
 We could extract some data from Italy using the [`socialmixr`](https://epiforecasts.io/socialmixr/) R package:
 
 ```{r}
 library(socialmixr)
 
-italy_2005 <- wpp_age("Italy", "2005")
+italy_2005 <- socialmixr::wpp_age("Italy", "2005")
 
 head(italy_2005)
 ```
@@ -64,6 +64,39 @@ Models built on contact patterns (and thus contact surveys) different to your po
 
 For further discussion on this problem, refer to the paper "Apparent structural changes in contact patterns during COVID-19 were driven by survey design and long-term demographic trends" by Harris et al. (2024). https://arxiv.org/abs/2406.01639
 
+We will walk through model creation using other contact surveys in this example. Here we use China. 
+
+```{r}
+# Another way of downloading the contact survey from socialmixr
+socialmixr::list_surveys()
+
+# Once we know which survey we want, we download it from Zenodo
+china_survey <- socialmixr::get_survey("https://doi.org/10.5281/zenodo.3878754")
+
+china_imputed <- impupte_contact_data(china_survey)
+
+china_filtered <- china_imputed %>%
+    dplyr::group_by(part_id) %>%
+    dplyr::mutate(
+      missing_any_contact_age = any(is.na(cnt_age_exact)),
+      missing_any_contact_setting = any(
+        is.na(cnt_home) | 
+          is.na(cnt_work) | 
+          is.na(cnt_school) | 
+          is.na(cnt_transport) | 
+          is.na(cnt_otherplace) | 
+          is.na(cnt_otherpublicplace)
+      )
+    ) %>%
+    dplyr::ungroup() %>%
+    dplyr::filter(
+      !is.na(part_age),
+      !missing_any_contact_age,
+      !missing_any_contact_setting
+    )
+```
+
+
 # Creating a next generation matrix (NGM)
 
 To create a next generation matrix, you can use either a conmat population