Hai Duong: Measles
Duc Du, Thinh Ong
2020-01-29 (update: 2022-08-25)
Last updated: 2022-08-25
Checks: 6 1
Knit directory: Vaccination_COVID/
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knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE, out.width = "100%")
library(data.table)
library(dplyr)Warning: package 'dplyr' was built under R version 4.1.2
Attaching package: 'dplyr'The following objects are masked from 'package:data.table':
between, first, lastThe following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionlibrary(tidyr)Warning: package 'tidyr' was built under R version 4.1.2library(lubridate)
Attaching package: 'lubridate'The following objects are masked from 'package:data.table':
hour, isoweek, mday, minute, month, quarter, second, wday, week,
yday, yearThe following objects are masked from 'package:base':
date, intersect, setdiff, unionlibrary(ggplot2)
library(gtsummary)Warning: package 'gtsummary' was built under R version 4.1.2library(ggsci)
library(plotly)
Attaching package: 'plotly'The following object is masked from 'package:ggplot2':
last_plotThe following object is masked from 'package:stats':
filterThe following object is masked from 'package:graphics':
layoutdatap <- file.path("~", "Downloads", "updated_dataset")
covidvc <- readRDS(file.path(datap, "Combined_VAC_COVID19_2022-02-17.rds"))
measle_all <- readRDS(file.path(datap, "measles_haiduong.rds"))
measle_all <- data.table(measle_all)
hepb <- readRDS(file.path(datap, "hepb_haiduong.rds"))
hepb <- data.table(hepb)
hepb <- hepb[which(hepb$shot == 1),]
time_step <- "month"
measle_all$vacym <- floor_date(measle_all$vacdate, time_step)
measle_all$vacname2 <- factor(measle_all$vacname2, levels = c("Measles", "MR", "MMR"))Measles and COVID-19 vaccination per month
* High peak of MR shots in Nov 2019 * No disruption in Apr 2020 * Disruptions in Aug 2020 and Feb 2021
Vaccination campaign in Nov 2019
An MR vaccination campaign is triggered during this time in Hai Duong, focusing on children 1-5 year-old 
# No disruption in Apr 2020 but in Aug 2020 and Feb 2021
The monthly vaccination date at public clinics is usually at the end of the month. In Mar 2020: right before lockdown they vaccinate children and right after lockdown they came back to vaccinate children
Hai Duong had a Hai Duong city-wide lockdown from 14/8-28/8, this time looks like they only organised the vaccination day in Sep so all children scheduled in Aug miss the shot 
Zoom in 2021
Hai Duong had a province-wide lockdown from 28/1/2021 - 15/2 (Directive 15), 16/2 - 2/3 (Directive 16), 3/3 - 17/3 (Directive 15), 18/3 - 31/3 (Directive 19)
Directive 16 > 15 > 19 
Public vs private
First let decide how a shot is public or private
hospital other private public unknown
389 2171 36149 353342 12616 Extract children who get 2 shots
Some received the same vaccine in the same day, filter them out and continue
Some received 3 shots, filtered them out.
Change dataset from long to wide format
Aggregate them by month
Line plot
# A tibble: 6 × 10
pid denom low_ci high_ci vyear_1st vmonth_1st shot1 shot2 pct2 vacdate_…¹
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <chr> <dbl> <date>
1 11 26 23.4 63.1 2020 1 private priv… 42.3 2020-01-01
2 51 106 38.3 58.0 2020 1 public priv… 48.1 2020-01-01
3 33 46 56.5 84.0 2020 8 private priv… 71.7 2020-08-01
4 56 132 33.9 51.3 2020 8 public priv… 42.4 2020-08-01
5 11 17 38.3 85.8 2021 2 private priv… 64.7 2021-02-01
6 32 68 34.8 59.6 2021 2 public priv… 47.1 2021-02-01
# … with abbreviated variable name ¹vacdate_1st# A tibble: 18 × 10
pid denom low_ci high_ci vyear_1st vmonth_1st shot1 shot2 pct2 vacdate_…¹
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <chr> <dbl> <date>
1 31 62 37.0 63.0 2021 3 priva… priv… 50 2021-03-01
2 445 2897 14.1 16.7 2021 3 public priv… 15.4 2021-03-01
3 25 54 32.6 60.4 2021 4 priva… priv… 46.3 2021-04-01
4 304 1711 16.0 19.7 2021 4 public priv… 17.8 2021-04-01
5 18 50 22.9 50.8 2021 5 priva… priv… 36 2021-05-01
6 266 1664 14.3 17.8 2021 5 public priv… 16.0 2021-05-01
7 29 44 50.1 79.5 2021 6 priva… priv… 65.9 2021-06-01
8 354 2065 15.5 18.8 2021 6 public priv… 17.1 2021-06-01
9 26 48 39.2 68.6 2021 7 priva… priv… 54.2 2021-07-01
10 364 2030 16.3 19.7 2021 7 public priv… 17.9 2021-07-01
11 25 35 53.7 85.4 2021 8 priva… priv… 71.4 2021-08-01
12 372 1697 20.0 24.0 2021 8 public priv… 21.9 2021-08-01
13 11 27 22.4 61.2 2021 9 priva… priv… 40.7 2021-09-01
14 258 1281 18.0 22.4 2021 9 public priv… 20.1 2021-09-01
15 17 28 40.6 78.5 2021 10 priva… priv… 60.7 2021-10-01
16 237 694 30.6 37.8 2021 10 public priv… 34.1 2021-10-01
17 10 14 41.9 91.6 2021 11 priva… priv… 71.4 2021-11-01
18 156 276 50.4 62.5 2021 11 public priv… 56.5 2021-11-01
# … with abbreviated variable name ¹vacdate_1stPopulation level
Children who got 2 shots
tmp <- measle_all[which(measle_all$vacname2 == "MMR"),]
table(tmp$shot)
1
49723 hepb$dob_ym <- floor_date(hepb$dob, time_step)
measle_all$dob_ym <- floor_date(measle_all$dob, time_step)
measle_all$vac_ym <- floor_date(measle_all$vacdate, time_step)
R version 4.1.1 (2021-08-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] plotly_4.10.0 ggsci_2.9 gtsummary_1.6.1 ggplot2_3.3.5
[5] lubridate_1.8.0 tidyr_1.2.0 dplyr_1.0.9 data.table_1.14.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.9 assertthat_0.2.1 rprojroot_2.0.3
[4] digest_0.6.29 utf8_1.2.2 R6_2.5.1
[7] evaluate_0.16 httr_1.4.4 highr_0.9
[10] pillar_1.8.1 rlang_1.0.4 lazyeval_0.2.2
[13] rstudioapi_0.13 jquerylib_0.1.4 rmarkdown_2.15
[16] labeling_0.4.2 stringr_1.4.1 htmlwidgets_1.5.4
[19] munsell_0.5.0 compiler_4.1.1 httpuv_1.6.5
[22] xfun_0.32 pkgconfig_2.0.3 htmltools_0.5.3
[25] tidyselect_1.1.2 tibble_3.1.8 workflowr_1.7.0
[28] fansi_1.0.3 viridisLite_0.4.0 crayon_1.5.1
[31] withr_2.5.0 later_1.3.0 grid_4.1.1
[34] jsonlite_1.8.0 gtable_0.3.0 lifecycle_1.0.1
[37] DBI_1.1.3 git2r_0.30.1 magrittr_2.0.3
[40] scales_1.2.1 cli_3.3.0 stringi_1.7.8
[43] cachem_1.0.6 farver_2.1.0 broom.helpers_1.8.0
[46] fs_1.5.2 promises_1.2.0.1 bslib_0.4.0
[49] ellipsis_0.3.2 generics_0.1.3 vctrs_0.4.1
[52] RColorBrewer_1.1-2 tools_4.1.1 glue_1.6.2
[55] purrr_0.3.4 crosstalk_1.2.0 fastmap_1.1.0
[58] yaml_2.3.5 colorspace_2.0-3 gt_0.6.0
[61] knitr_1.39 sass_0.4.2