---
title: "vaers: examples"
author: "Irucka Embry"
date: "`r Sys.Date()`"
output:
  rmarkdown::html_document:
    highlight: kate
    theme: readable
    code_download: TRUE
vignette: >
  %\VignetteIndexEntry{US VAERS data examples}
  %\VignetteEngine{knitr::rmarkdown}
  \usepackage[utf8]{inputenc}
---

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# About the data

There are 3 sets of data included in this package from the US Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA) **United States** Vaccine Adverse Event Reporting System (VAERS) program. There is the `vax` table which includes information about the vaccines. There is the `data` table which has data from the VAERS-1 form. There is the `symptoms` table which has the adverse events.

Please see the README, DESCRIPTION, and the individual R data files for more information.

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# Examples

```{r, warning = FALSE, message = FALSE, tidy = TRUE}

install.load::load_package("vaers", "vaersND", "data.table", "pivottabler", "skimr", "DT", "formatR")
# load needed packages using the load_package function from the install.load package (it is assumed that you have already installed these packages)


## load vaers_data

data(vaers_data)



# How many reports for each sex?

setkey(vaers_data, VAERS_ID)

vaers_data[, .N, by = list(SEX)] # Source 1



# How many people died, listed by ID (only using the vaers_data]?

vaers_data[DIED == "Y", list(VAERS_ID, DIED)]



# Identify the VAERS_IDs for females only

vaers_data[SEX == "F", list(VAERS_ID, SEX)]



## load vaers_symptoms

data(vaers_symptoms)


# How many reports of autism for SYMPTOM1?

setkey(vaers_symptoms, VAERS_ID)

vaers_symptoms[SYMPTOM1 == "Autism", .N] # Source 2



## load vaers_vax

data(vaers_vax)


# What are the counts for each of the VAX_TYPEs?

setkey(vaers_vax, VAERS_ID)

vaers_vax[, .N, by = list(VAX_TYPE)][order(VAX_TYPE)] # Source 1



# How many reports of MMR as the VAX_TYPE?

vaers_vax[VAX_TYPE == "MMR", .N] # Source 2



# How many reports of COVID19 as the VAX_TYPE or the VAX_NAME contains COVID19?

vaers_vax[VAX_TYPE == "COVID19" | VAX_NAME %like% "COVID19", .N] # Source 2



# join vaers_data and vaers_vax to get access to the type and name of the vaccination$
data_vax <- vaers_data[vaers_vax]

setkey(data_vax, VAERS_ID)


# get the total number of VAERS_IDs in data_vax
length(data_vax$VAERS_ID)

# get the total number of unique VAERS_IDs in data_vax
length(unique(data_vax$VAERS_ID))

# remove the duplicated rows
data_vax2 <- unique(data_vax)

setkey(data_vax2, VAERS_ID)


# How many people have died from all vaccines since 1990?
# Include the number of entries for each VAERS_ID
data_vax2[DIED == "Y", .N, list(VAERS_ID, DIED)] # Source 2


# How many people have died from all vaccines since 1990?
data_vax2[DIED == "Y", list(VAERS_ID, DIED)] # Source 2


# Explore rows 2 and 3 for VAERS_ID: 025003 using DT
datatable(data_vax2[2:3, ])


# How many people have died from the COVID19 Experimental Gene Therapy Technology {Search for discussion by Judy Mikovits, Ph.D.]?

data_vax2[VAX_TYPE == "COVID19" & DIED == "Y", list(VAERS_ID, DIED)] # Source 2



# What is the ratio, expressed as a percentage, of the COVID19 Experimental Gene Therapy Technology {Search for discussion by Judy Mikovits, Ph.D.] to all deaths associated with vaccination$ since 1990?

(nrow(data_vax2[VAX_TYPE == "COVID19" & DIED == "Y"]) / nrow(data_vax2[DIED == "Y"])) * 100 # Source 2



# What is the first date reported with COVID19 as the VAX_TYPE or the VAX_NAME contains COVID19?

data_vax2ed <- data_vax2[VAX_TYPE == "COVID19" | VAX_NAME %like% "COVID19"]

data_vax2ed[1, "VAX_DATE"]



# How many days from the vaccination date to the person's death date?
# copy the data_vax2 data.table object
data_vax2er <- copy(data_vax2)

# create a new column with the value of the time difference between the date the person died and the vaccination date
data_vax2er[, `Days_Vaccination$_Death` := data_vax2$DATEDIED - data_vax2$VAX_DATE]

# group the number of days and sort by the greatest number of days between the date the person died and the vaccination date
data_vax2err <- data_vax2er[, .(.N), by = .(`Days_Vaccination$_Death`)][order(-N)] # Source 2

data_vax2err 
```

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# Pivot Table

```{r, warning = FALSE, message = FALSE, tidy = TRUE}
# Create a pivot table of the data_vax2 data based on VAX_NAME and if they DIED
qpvt(data_vax2, c("VAX_NAME"), "DIED", "n()")
```

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# Summarize the data sets

```{r, warning = FALSE, message = FALSE, tidy = TRUE}
# use skimr to summarize each of the 3 data sets

skim(vaers_data)



skim(vaers_symptoms)



skim(vaers_vax)
```

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# Summarize the Non-Domestic data sets in comparison

```{r, warning = FALSE, message = FALSE, tidy = TRUE}
# load the data sets

data(vaersND_data)

data(vaersND_symptoms)

data(vaersND_vax)


# use skimr to summarize each of the 3 Non-Domestic data sets
skim(vaersND_data)



skim(vaersND_symptoms)



skim(vaersND_vax)
```

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# Data Source

US Centers for Disease Control and Prevention (CDC) and the US Food and Drug Administration (FDA) Vaccine Adverse Event Reporting System (VAERS), https://vaers.hhs.gov/.

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# Sources used in the R code

Source 1<br />
r - Is there an aggregate FUN option to count occurrences? - Stack Overflow answered by mnel on Aug 2 2013. See https://stackoverflow.com/questions/9809166/is-there-an-aggregate-fun-option-to-count-occurrences.

Source 2<br />
https://rdatatable.gitlab.io/data.table/articles/datatable-intro.html
Introduction to data.table

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# Useful links to find out more about the inherent dangers of vaccination$

Questioning the Universe Publishing (QUP) {Irucka Embry]: Resources to help us rethink the current crisis (in perception): **"Coronavirus" <del>Vaccination$</del> <ins>Experimental Gene Therapy Technology {Search for discussion by Judy Mikovits, Ph.D.]**
https://www.questionuniverse.com/rethink_current_crisis.html#cov_vaccin

Questioning the Universe Publishing (QUP) {Irucka Embry]: Resources to help us rethink, reimagine, & reFeel our world: **Vaccination$**<br />
https://www.questionuniverse.com/rethink.html#vaccine

EcoC&sup2;S [Irucka Embry): Resources for a Healthier You (Resources to help us take responsibility back to heal ourselves and each other): **Vaccination$**<br />
https://www.ecoccs.com/healing.html#vaccines