sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19.tex

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  pdftitle={Documentation of the article `COVID-19 vaccines confer protection in hospitalized pregnant and postpartum women with severe COVID-19'},
  pdfauthor={Codes and outputs},
  hidelinks,
  pdfcreator={LaTeX via pandoc}}
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\title{Documentation of the article `COVID-19 vaccines confer protection
in hospitalized pregnant and postpartum women with severe COVID-19'}
\author{Codes and outputs}
\date{Feb 10, 2022}

\begin{document}
\maketitle

{
\setcounter{tocdepth}{1}
\tableofcontents
}
\newpage

\hypertarget{description}{%
\section{Description}\label{description}}

This file presents the documentation of the analysis of article
``COVID-19 vaccines confer protection in hospitalized pregnant and
postpartum women with severe COVID-19''.

\hypertarget{about-the-database-and-r-packages-used}{%
\section{About the database and R packages
used}\label{about-the-database-and-r-packages-used}}

The data are analyzed using the free-software R
(\url{https://www.R-project.org}) in version 4.0.3. Next, we present and
load the libraries used in the data analysis process.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#load packages}
\NormalTok{loadlibrary }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x) \{}
  \ControlFlowTok{if}\NormalTok{ (}\SpecialCharTok{!}\FunctionTok{require}\NormalTok{(x, }\AttributeTok{character.only =} \ConstantTok{TRUE}\NormalTok{)) \{}
    \FunctionTok{install.packages}\NormalTok{(x, }\AttributeTok{dependencies =}\NormalTok{ T)}
    \ControlFlowTok{if}\NormalTok{ (}\SpecialCharTok{!}\FunctionTok{require}\NormalTok{(x, }\AttributeTok{character.only =} \ConstantTok{TRUE}\NormalTok{))}
      \FunctionTok{stop}\NormalTok{(}\StringTok{"Package not found"}\NormalTok{)}
\NormalTok{  \}}
\NormalTok{\}}

\NormalTok{packages }\OtherTok{\textless{}{-}}
  \FunctionTok{c}\NormalTok{(}
    \StringTok{"readr"}\NormalTok{,}
    \StringTok{"readxl"}\NormalTok{,}
    \StringTok{"janitor"}\NormalTok{,}
    \StringTok{"dplyr"}\NormalTok{,}
    \StringTok{"forcats"}\NormalTok{,}
    \StringTok{"stringr"}\NormalTok{,}
    \StringTok{"lubridate"}\NormalTok{,}
    \StringTok{"summarytools"}\NormalTok{,}
    \StringTok{"magrittr"}\NormalTok{,}
    \StringTok{"questionr"}\NormalTok{, }
    \StringTok{"knitr"}\NormalTok{,}
    \StringTok{"data.table"}\NormalTok{,}
    \StringTok{"modelsummary"}\NormalTok{, }
    \StringTok{"kableExtra"}\NormalTok{, }
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    \StringTok{"miceafter"}\NormalTok{, }
    \StringTok{"VIM"}\NormalTok{,}
    \StringTok{"miceadds"}
\NormalTok{  )}

\FunctionTok{lapply}\NormalTok{(packages, loadlibrary)}
\end{Highlighting}
\end{Shaded}

One can see below the functions that will be used in the data analysis.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#functions for summary measures}
\NormalTok{media }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
  \FunctionTok{mean}\NormalTok{(x, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{mediana }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
  \FunctionTok{median}\NormalTok{(x, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{DP }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
  \FunctionTok{sd}\NormalTok{(x, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{minimo }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
\NormalTok{  base}\SpecialCharTok{::}\FunctionTok{min}\NormalTok{(x, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{maximo }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
\NormalTok{  base}\SpecialCharTok{::}\FunctionTok{max}\NormalTok{(x, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{q25 }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
\NormalTok{  stats}\SpecialCharTok{::}\FunctionTok{quantile}\NormalTok{(x, }\AttributeTok{p =} \FloatTok{0.25}\NormalTok{, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{q75 }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
\NormalTok{  stats}\SpecialCharTok{::}\FunctionTok{quantile}\NormalTok{(x, }\AttributeTok{p =} \FloatTok{0.75}\NormalTok{, }\AttributeTok{na.rm =} \ConstantTok{TRUE}\NormalTok{)}
\NormalTok{IQR }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
  \FunctionTok{round}\NormalTok{(}\FunctionTok{q75}\NormalTok{(x) }\SpecialCharTok{{-}} \FunctionTok{q25}\NormalTok{(x), }\DecValTok{2}\NormalTok{)}
\NormalTok{n }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)}
  \FunctionTok{sum}\NormalTok{(}\SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(x))}
\end{Highlighting}
\end{Shaded}

This is a retrospective cohort study using the data from the Influenza
Epidemiological Surveillance Information System, SIVEP-Gripe (Sistema de
Informação de Vigilância Epidemiológica da Gripe) database.

The SIVEP-Gripe is a nationwide surveillance database created to monitor
severe acute respiratory infections and data on virus circulation and
respiratory infections in Brazil.

The period analyzed comprises epidemiological data from 2021, with a
database obtained on December 2, 2021 on the website
\url{https://opendatasus.saude.gov.br}. The dataset can be obtained at
\url{https://www.kaggle.com/agatharodrigues/covid19-vaccine-maternal-population}.
It is loaded below:

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#loading the datasets}
\CommentTok{\#2021}
\NormalTok{dados }\OtherTok{\textless{}{-}} \FunctionTok{read\_delim}\NormalTok{(}
  \StringTok{"INFLUD21{-}29{-}11{-}2021.csv"}\NormalTok{,}
  \StringTok{";"}\NormalTok{,}
  \AttributeTok{escape\_double =} \ConstantTok{FALSE}\NormalTok{,}
  \AttributeTok{locale =} \FunctionTok{locale}\NormalTok{(}\AttributeTok{encoding =} \StringTok{"ISO{-}8859{-}2"}\NormalTok{),}
  \AttributeTok{trim\_ws =} \ConstantTok{TRUE}
\NormalTok{)}

\CommentTok{\#Create case year variable}
\NormalTok{dados }\OtherTok{\textless{}{-}}\NormalTok{  dados }\SpecialCharTok{\%\textgreater{}\%}
\NormalTok{  dplyr}\SpecialCharTok{::}\FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{dt\_sint =} \FunctionTok{as.Date}\NormalTok{(DT\_SIN\_PRI, }\AttributeTok{format =} \StringTok{"\%d/\%m/\%Y"}\NormalTok{), }\CommentTok{\#date of first symptoms}
    \AttributeTok{dt\_nasc =} \FunctionTok{as.Date}\NormalTok{(DT\_NASC, }\AttributeTok{format =} \StringTok{"\%d/\%m/\%Y"}\NormalTok{), }\CommentTok{\#date of birth}
    \AttributeTok{dt\_vac\_gripe =} \FunctionTok{as.Date}\NormalTok{(DT\_UT\_DOSE, }\AttributeTok{format =} \StringTok{"\%d/\%m/\%Y"}\NormalTok{), }\CommentTok{\#date of Influenza vaccine}
    \AttributeTok{ano =}\NormalTok{ lubridate}\SpecialCharTok{::}\FunctionTok{year}\NormalTok{(dt\_sint), }\CommentTok{\#year of the case}
\NormalTok{  )}
\end{Highlighting}
\end{Shaded}

There are 1625471 observations in the database. To see the dictionary of
variables, access (in Portuguese):
\url{https://opendatasus.saude.gov.br/dataset/ae90fa8f-3e94-467e-a33f-94adbb66edf8/resource/8f571374-c555-4ec0-8e44-00b1e8b11c25/download/dicionario-de-dados-srag-hospitalizado-27.07.2020-final.pdf}

\hypertarget{case-selection-and-data-treatment}{%
\section{Case selection and data
treatment}\label{case-selection-and-data-treatment}}

The first filter is to select cases from May 02, 2021 (18th
epidemiological week of symptoms of 2021) to November 27, 2021
(epidemiological week 47 of 2021).

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#selection of cases from 18th epidemiological week of symptoms (May 2, 2021) }
\CommentTok{\#to November 27, 2021 (week 43 of 2021).}
\NormalTok{sem1 }\OtherTok{\textless{}{-}} \DecValTok{18}
\NormalTok{sem2 }\OtherTok{\textless{}{-}} \DecValTok{47}

\NormalTok{dados1 }\OtherTok{\textless{}{-}}\NormalTok{ dados }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{(SEM\_PRI }\SpecialCharTok{\textgreater{}=}\NormalTok{ sem1 }\SpecialCharTok{\&}\NormalTok{  SEM\_PRI }\SpecialCharTok{\textless{}=}\NormalTok{ sem2)}
\end{Highlighting}
\end{Shaded}

There are 756681 observations in the database after selection of valid
years.

The next selection is female:

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#filtering F}
\NormalTok{dados2 }\OtherTok{\textless{}{-}} \FunctionTok{filter}\NormalTok{(dados1, CS\_SEXO }\SpecialCharTok{==} \StringTok{"F"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

There are 338892 observations in the database.

Selection of women of childbearing age (10 to 55 years):

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#creating the age variable as the difference between dt\_sint and dt\_nasc.}
\CommentTok{\#In cases without dt\_nasc, we consider}
\CommentTok{\#the NU\_AGE\_N field}
\NormalTok{dados2 }\OtherTok{\textless{}{-}}\NormalTok{ dados2 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}
         \AttributeTok{idade =} \FunctionTok{as.period}\NormalTok{(}\FunctionTok{interval}\NormalTok{(}\AttributeTok{start =}\NormalTok{ dt\_nasc, }\AttributeTok{end =}\NormalTok{ dt\_sint))}\SpecialCharTok{$}\NormalTok{year, }
         \AttributeTok{age =} \FunctionTok{ifelse}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(idade), NU\_IDADE\_N, idade)}
\NormalTok{  )}

\CommentTok{\#Filtering of cases aged 55 and under}
\NormalTok{dados3 }\OtherTok{\textless{}{-}}\NormalTok{ dados2 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{(age }\SpecialCharTok{\textgreater{}} \DecValTok{9} \SpecialCharTok{\&}\NormalTok{ age }\SpecialCharTok{\textless{}=} \DecValTok{55}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

There are 141540 observations in the database.

The next step is to identify pregnant and postpartum people (variable
\texttt{classi\_gesta\_puerp}) and then select only those cases.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Creating the classification variable if pregnant, postpartum and }
\DocumentationTok{\#\#neither pregnant nor postpartum}
\NormalTok{dados3 }\OtherTok{\textless{}{-}}\NormalTok{ dados3 }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{classi\_gesta\_puerp =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      CS\_GESTANT }\SpecialCharTok{==} \DecValTok{1}  \SpecialCharTok{\textasciitilde{}} \StringTok{"1tri"}\NormalTok{,}
\NormalTok{      CS\_GESTANT }\SpecialCharTok{==} \DecValTok{2}  \SpecialCharTok{\textasciitilde{}} \StringTok{"2tri"}\NormalTok{,}
\NormalTok{      CS\_GESTANT }\SpecialCharTok{==} \DecValTok{3}  \SpecialCharTok{\textasciitilde{}} \StringTok{"3tri"}\NormalTok{,}
\NormalTok{      CS\_GESTANT }\SpecialCharTok{==} \DecValTok{4}  \SpecialCharTok{\textasciitilde{}} \StringTok{"IG\_ig"}\NormalTok{,}
\NormalTok{      CS\_GESTANT }\SpecialCharTok{==} \DecValTok{5} \SpecialCharTok{\&}
\NormalTok{        PUERPERA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"puerp"}\NormalTok{,}
\NormalTok{      CS\_GESTANT }\SpecialCharTok{==} \DecValTok{9} \SpecialCharTok{\&}\NormalTok{ PUERPERA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"puerp"}\NormalTok{,}
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"} 
\NormalTok{    )}
\NormalTok{  )}

\FunctionTok{freq}\NormalTok{(dados3}\SpecialCharTok{$}\NormalTok{classi\_gesta\_puerp)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##            n    % val%
## 1tri     800  0.6  0.6
## 2tri    2110  1.5  1.5
## 3tri    4958  3.5  3.5
## IG_ig    368  0.3  0.3
## no    131497 92.9 92.9
## puerp   1807  1.3  1.3
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#filtering only pregnant and postpartum women}
\NormalTok{dados4 }\OtherTok{\textless{}{-}}\NormalTok{ dados3 }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{filter}\NormalTok{(classi\_gesta\_puerp }\SpecialCharTok{!=} \StringTok{"no"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

There are 10043 observations in the database.

We selected only confirmed cases of COVID-19.

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{dados4 }\OtherTok{\textless{}{-}}\NormalTok{ dados4 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{classi\_fin =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      CLASSI\_FIN }\SpecialCharTok{==} \DecValTok{5} \SpecialCharTok{\textasciitilde{}} \StringTok{"covid"}\NormalTok{,}
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}
\NormalTok{    )}
\NormalTok{  )}


\CommentTok{\#filtering only covid cases }
\NormalTok{dados5 }\OtherTok{\textless{}{-}}\NormalTok{ dados4 }\SpecialCharTok{\%\textgreater{}\%} 
    \FunctionTok{filter}\NormalTok{(CLASSI\_FIN }\SpecialCharTok{==} \DecValTok{5}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

There are 5806 observations in the database.

Now let's select the cases of COVID by PCR or antigen, but which are
also not positive for Influenza.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#COVID case diagnosed by PCR}
\NormalTok{dados5 }\OtherTok{\textless{}{-}}\NormalTok{ dados5 }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{pcr\_covid\_SN =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{    (PCR\_SARS2 }\SpecialCharTok{==} \DecValTok{1}\NormalTok{) }\SpecialCharTok{|}
\NormalTok{      (}
        \FunctionTok{str\_detect}\NormalTok{(DS\_PCR\_OUT, }\StringTok{"SARS|COVID|COV|CORONA|CIVID"}\NormalTok{) }
\NormalTok{      ) }\SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,  }
    \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}  
\NormalTok{  ))}

\CommentTok{\#Influenza case diagnosed by PCR }
\NormalTok{dados5 }\OtherTok{\textless{}{-}}\NormalTok{ dados5 }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{pcr\_influenza\_SN =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{    (POS\_PCRFLU }\SpecialCharTok{==} \DecValTok{1}\NormalTok{) }\SpecialCharTok{|}
\NormalTok{      (}
        \FunctionTok{str\_detect}\NormalTok{(DS\_PCR\_OUT, }\StringTok{"INFLU|INFLUENZA"}\NormalTok{) }
\NormalTok{      ) }\SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{, }
    \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}  
\NormalTok{  ))}

\FunctionTok{with}\NormalTok{(dados5, }\FunctionTok{table}\NormalTok{(pcr\_influenza\_SN, pcr\_covid\_SN))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##                 pcr_covid_SN
## pcr_influenza_SN   no  yes
##              no  2806 2999
##              yes    1    0
\end{verbatim}

There is no case that is positive for COVID and for Influenza by PCR.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Case of COVID diagnosed by antigen}
\NormalTok{dados5 }\OtherTok{\textless{}{-}}\NormalTok{ dados5 }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{antigenio\_covid\_SN =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{    (AN\_SARS2 }\SpecialCharTok{==} \DecValTok{1}\NormalTok{) }\SpecialCharTok{|}
\NormalTok{      (}
        \FunctionTok{str\_detect}\NormalTok{(DS\_AN\_OUT, }\StringTok{"SARS|COVID|COV|CORONA|CIVID"}\NormalTok{) }
\NormalTok{      ) }\SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,  }
    \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"} 
\NormalTok{  ))}


\CommentTok{\#Influenza case diagnosed by antigen}
\NormalTok{dados5 }\OtherTok{\textless{}{-}}\NormalTok{ dados5 }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{antigenio\_influenza\_SN =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{    (POS\_AN\_FLU }\SpecialCharTok{==} \DecValTok{1}\NormalTok{) }\SpecialCharTok{|}
\NormalTok{      (}
        \FunctionTok{str\_detect}\NormalTok{(DS\_AN\_OUT, }\StringTok{"INFLU|INFLUENZA"}\NormalTok{) }
\NormalTok{      ) }\SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,  }
    \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}  
\NormalTok{  ))}

\FunctionTok{with}\NormalTok{(dados5, }\FunctionTok{table}\NormalTok{(antigenio\_influenza\_SN, antigenio\_covid\_SN))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##                       antigenio_covid_SN
## antigenio_influenza_SN   no  yes
##                    no  4306 1499
##                    yes    0    1
\end{verbatim}

There is one positive case for COVID and for Influenza by antigen.

We will now select the cases of COVID confirmed by PCR or antigen.

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(dados5, }\FunctionTok{table}\NormalTok{(pcr\_covid\_SN, antigenio\_covid\_SN))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##             antigenio_covid_SN
## pcr_covid_SN   no  yes
##          no  1518 1289
##          yes 2788  211
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#filtering only covid cases by PCR or antigen}
\NormalTok{dados6 }\OtherTok{\textless{}{-}}\NormalTok{ dados5 }\SpecialCharTok{\%\textgreater{}\%} 
    \FunctionTok{filter}\NormalTok{(pcr\_covid\_SN }\SpecialCharTok{==} \StringTok{"yes"} \SpecialCharTok{|}\NormalTok{ antigenio\_covid\_SN }\SpecialCharTok{==} \StringTok{"yes"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

There are 4288 observations in the database.

Now it's time to remove cases that are also positive for Influenza.

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(dados6, }\FunctionTok{table}\NormalTok{(pcr\_influenza\_SN, antigenio\_influenza\_SN))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##                 antigenio_influenza_SN
## pcr_influenza_SN   no  yes
##              no  4287    0
##              yes    0    1
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#filtering only negative cases of Influenza by PCR or antigen}
\NormalTok{dados7 }\OtherTok{\textless{}{-}}\NormalTok{ dados6 }\SpecialCharTok{\%\textgreater{}\%} 
    \FunctionTok{filter}\NormalTok{(pcr\_influenza\_SN }\SpecialCharTok{!=} \StringTok{"yes"} \SpecialCharTok{\&}\NormalTok{ antigenio\_influenza\_SN }\SpecialCharTok{!=} \StringTok{"yes"}\NormalTok{)  }
\end{Highlighting}
\end{Shaded}

There are 4287 observations in the database.

We will only select the finalized cases (death or cure). The variable
that indicates the outcome is \texttt{EVOLUCAO}, with the categories:
1-Cure; 2-Death; 3- Death from other causes; 9-Ignored.

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(dados7, }\FunctionTok{freq}\NormalTok{(EVOLUCAO))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##       n    % val%
## 1  3351 78.2 84.9
## 2   487 11.4 12.3
## 3     8  0.2  0.2
## 9   100  2.3  2.5
## NA  341  8.0   NA
\end{verbatim}

Let's select only the finalized cases:

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#filtering only completed cases}
\NormalTok{dados8 }\OtherTok{\textless{}{-}}\NormalTok{ dados7 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{((EVOLUCAO }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{|}\NormalTok{ EVOLUCAO }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{|}\NormalTok{ EVOLUCAO }\SpecialCharTok{==} \DecValTok{3}\NormalTok{) }\SpecialCharTok{\&} \SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(EVOLUCAO))}


\CommentTok{\#creating the evolution variable}
\NormalTok{dados8 }\OtherTok{\textless{}{-}}\NormalTok{ dados8 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{death =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{    EVOLUCAO }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"cure"}\NormalTok{, }
\NormalTok{    EVOLUCAO }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"death"}\NormalTok{,}
\NormalTok{    EVOLUCAO }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"death"}
\NormalTok{  ))}

\FunctionTok{with}\NormalTok{(dados8, }\FunctionTok{freq}\NormalTok{(death))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##          n    % val%
## cure  3351 87.1 87.1
## death  495 12.9 12.9
\end{verbatim}

There are 3846 observations in the database.

The variable that indicates whether the person received a vaccine
against COVID-19 is \texttt{VACINA\_COV}, with categories: 1-yes; 2-no;
9-ignored.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Frequency table for VACINA\_COV}
\FunctionTok{with}\NormalTok{(dados8, }\FunctionTok{freq}\NormalTok{(VACINA\_COV))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##       n    % val%
## 1   650 16.9 18.7
## 2  2084 54.2 60.0
## 9   738 19.2 21.3
## NA  374  9.7   NA
\end{verbatim}

Let's now group ``NA'' and ``9'' in the same category (NA - missing
data) and label the valid categories.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#recoding the vaccine\_cov variable }
\NormalTok{dados8 }\OtherTok{\textless{}{-}}\NormalTok{ dados8 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{vaccine\_cov =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{    VACINA\_COV }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{, }
\NormalTok{    VACINA\_COV }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
    \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}
\NormalTok{  ))}
\CommentTok{\#frequency table for vaccine\_cov}
\FunctionTok{with}\NormalTok{(dados8, }\FunctionTok{freq}\NormalTok{(vaccine\_cov))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##        n    % val%
## no  2084 54.2 76.2
## yes  650 16.9 23.8
## NA  1112 28.9   NA
\end{verbatim}

The next step is filtering cases that we have information about COVID-19
vaccination. These data are analyzed in the following.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Filtering cases with information about vaccination}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{ dados8 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{(}\SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(vaccine\_cov))}
\end{Highlighting}
\end{Shaded}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{freq}\NormalTok{(vaccine\_cov))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##        n    % val%
## no  2084 76.2 76.2
## yes  650 23.8 23.8
\end{verbatim}

The variable \texttt{vaccine\_cov} only indicates if the pregnant or
postpartum women took the vaccine, regardless of the dose. There is no
information on whether the person only took the first dose or the
second. The closest we come to this is to consider the column
\texttt{DOSE\_2\_COV}, which indicates the date of the second dose.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Create second dose date variable}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
\NormalTok{  dplyr}\SpecialCharTok{::}\FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{dt\_dose2\_cov =} \FunctionTok{as.Date}\NormalTok{(DOSE\_2\_COV, }\AttributeTok{format =} \StringTok{"\%d/\%m/\%Y"}\NormalTok{)}
\NormalTok{  )}

\CommentTok{\#Create variable that indicates that it has the date of the second dose}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final}\SpecialCharTok{\%\textgreater{}\%}
\NormalTok{  dplyr}\SpecialCharTok{::}\FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{indic\_dt\_dose2\_cov =} \FunctionTok{ifelse}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(dt\_dose2\_cov) }\SpecialCharTok{\&} \SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(vaccine\_cov), }\DecValTok{0}\NormalTok{, }\FunctionTok{ifelse}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(vaccine\_cov), }\ConstantTok{NA}\NormalTok{, }\DecValTok{1}\NormalTok{))}
\NormalTok{  )}

\CommentTok{\# first dose date frequency table}
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{freq}\NormalTok{(indic\_dt\_dose2\_cov, }\AttributeTok{total =}  \ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##          n     %  val%
## 0     2534  92.7  92.7
## 1      200   7.3   7.3
## Total 2734 100.0 100.0
\end{verbatim}

There is only information on the date of the second dose for 200 cases
of 650 cases indicated as ``yes'' for COVID-19 vaccine.

Now we will analyze the not vaccinated group versus two dose vaccinated
group.

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Create second dose date variable}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{(vaccine\_cov }\SpecialCharTok{==} \StringTok{"no"} \SpecialCharTok{|}\NormalTok{ (vaccine\_cov }\SpecialCharTok{==} \StringTok{"yes"} \SpecialCharTok{\&}\NormalTok{ indic\_dt\_dose2\_cov }\SpecialCharTok{==} \DecValTok{1}\NormalTok{))}

\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{freq}\NormalTok{(vaccine\_cov))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##        n    % val%
## no  2084 91.2 91.2
## yes  200  8.8  8.8
\end{verbatim}

\#Analysis

\hypertarget{epidemiologic-characteristics}{%
\subsection{Epidemiologic
characteristics}\label{epidemiologic-characteristics}}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# Ethnicity}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{ethnicity =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      CS\_RACA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"white"}\NormalTok{,}
\NormalTok{      CS\_RACA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"black"}\NormalTok{,}
\NormalTok{      CS\_RACA }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"yellow"}\NormalTok{,}
\NormalTok{      CS\_RACA }\SpecialCharTok{==} \DecValTok{4} \SpecialCharTok{\textasciitilde{}} \StringTok{"brown"}\NormalTok{,}
\NormalTok{      CS\_RACA }\SpecialCharTok{==} \DecValTok{5} \SpecialCharTok{\textasciitilde{}} \StringTok{"indigenous"}\NormalTok{,}
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}
\NormalTok{    ), }
    \AttributeTok{white\_color =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      ethnicity }\SpecialCharTok{==} \StringTok{"white"} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{, }
      \FunctionTok{is.na}\NormalTok{(ethnicity) }\SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{, }
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}
\NormalTok{    )}
\NormalTok{  )}

\CommentTok{\# Education}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{education2 =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      CS\_ESCOL\_N }\SpecialCharTok{\textless{}=} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"up to 9 years"}\NormalTok{, }
\NormalTok{      CS\_ESCOL\_N }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"from 9 to 12 years"}\NormalTok{, }
\NormalTok{      CS\_ESCOL\_N }\SpecialCharTok{==} \DecValTok{4} \SpecialCharTok{\textasciitilde{}} \StringTok{"over 12 years"}\NormalTok{,}
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}
\NormalTok{    )}
\NormalTok{  )}
\NormalTok{data\_final}\SpecialCharTok{$}\NormalTok{education2 }\OtherTok{\textless{}{-}}
  \FunctionTok{factor}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{education2, }\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"up to 9 years"}\NormalTok{, }\StringTok{"from 9 to 12 years"}\NormalTok{, }\StringTok{"over 12 years"}\NormalTok{))}

\CommentTok{\# residence area}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{residence =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      CS\_ZONA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"urban"}\NormalTok{,}
\NormalTok{      CS\_ZONA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"rural"}\NormalTok{,}
\NormalTok{      CS\_ZONA }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"periurban"}\NormalTok{,}
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}
\NormalTok{    )}
\NormalTok{  )}

\CommentTok{\# residence area 2 (grouping the categories urban and periurban)}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{residence2 =} \FunctionTok{case\_when}\NormalTok{(}
\NormalTok{      CS\_ZONA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"urban/periurban"}\NormalTok{,}
\NormalTok{      CS\_ZONA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"rural"}\NormalTok{,}
\NormalTok{      CS\_ZONA }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"urban/periurban"}\NormalTok{,}
      \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}
\NormalTok{    )}
\NormalTok{  )}
\NormalTok{data\_final}\SpecialCharTok{$}\NormalTok{residence2 }\OtherTok{\textless{}{-}}
  \FunctionTok{factor}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{residence2, }\AttributeTok{levels =} \FunctionTok{c}\NormalTok{(}\StringTok{"rural"}\NormalTok{, }\StringTok{"urban/periurban"}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\hypertarget{ethnicity}{%
\subsubsection{Ethnicity}\label{ethnicity}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(ethnicity, vaccine\_cov,  }\AttributeTok{prop =} \StringTok{"c"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{FALSE}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{FALSE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Column Proportions  
## ethnicity * vaccine_cov  
## Data Frame: data_final  
## 
## ------------ ------------- --------------- -------------- ---------------
##                vaccine_cov              no            yes           Total
##    ethnicity                                                             
##        black                   96 (  5.1%)     6 (  3.3%)    102 (  4.9%)
##        brown                  753 ( 39.9%)    61 ( 33.3%)    814 ( 39.3%)
##   indigenous                    5 (  0.3%)     4 (  2.2%)      9 (  0.4%)
##        white                 1022 ( 54.1%)   111 ( 60.7%)   1133 ( 54.7%)
##       yellow                   12 (  0.6%)     1 (  0.5%)     13 (  0.6%)
##        Total                 1888 (100.0%)   183 (100.0%)   2071 (100.0%)
## ------------ ------------- --------------- -------------- ---------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{ethnicity, data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$ethnicity and data_final$vaccine_cov
## p-value = 0.007548
## alternative hypothesis: two.sided
\end{verbatim}

\hypertarget{white-color}{%
\subsubsection{White color}\label{white-color}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(white\_color, vaccine\_cov,  }\AttributeTok{prop =} \StringTok{"c"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Column Proportions  
## white_color * vaccine_cov  
## Data Frame: data_final  
## 
## 
## ------------- ------------- --------------- -------------- ---------------
##                 vaccine_cov              no            yes           Total
##   white_color                                                             
##            no                  866 ( 45.9%)    72 ( 39.3%)    938 ( 45.3%)
##           yes                 1022 ( 54.1%)   111 ( 60.7%)   1133 ( 54.7%)
##         Total                 1888 (100.0%)   183 (100.0%)   2071 (100.0%)
## ------------- ------------- --------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    2.6088      1    0.1063  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.31        0.96       1.78   
## ----------------------------------
\end{verbatim}

\hypertarget{education-years}{%
\subsubsection{Education (years)}\label{education-years}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(education2, vaccine\_cov, }\AttributeTok{prop =} \StringTok{"c"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Column Proportions  
## education2 * vaccine_cov  
## Data Frame: data_final  
## 
## 
## -------------------- ------------- --------------- -------------- ---------------
##                        vaccine_cov              no            yes           Total
##           education2                                                             
##        up to 9 years                  279 ( 26.7%)    20 ( 19.8%)    299 ( 26.1%)
##   from 9 to 12 years                  573 ( 54.9%)    55 ( 54.5%)    628 ( 54.8%)
##        over 12 years                  192 ( 18.4%)    26 ( 25.7%)    218 ( 19.0%)
##                Total                 1044 (100.0%)   101 (100.0%)   1145 (100.0%)
## -------------------- ------------- --------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    4.3072      2    0.1161  
## ----------------------------
\end{verbatim}

\hypertarget{age}{%
\subsubsection{Age}\label{age}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{datasummary}\NormalTok{((vaccine\_cov) }\SpecialCharTok{\textasciitilde{}}\NormalTok{ age}\SpecialCharTok{*}\NormalTok{(n}\SpecialCharTok{+}\NormalTok{media}\SpecialCharTok{+}\NormalTok{DP}\SpecialCharTok{+}\NormalTok{mediana}\SpecialCharTok{+}\NormalTok{q25}\SpecialCharTok{+}\NormalTok{q75}\SpecialCharTok{+}\NormalTok{IQR),}
            \AttributeTok{data =}\NormalTok{ data\_final, }\AttributeTok{output =} \StringTok{\textquotesingle{}markdown\textquotesingle{}}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{longtable}[]{@{}lrrrrrrr@{}}
\toprule
& n & media & DP & mediana & q25 & q75 & IQR \\
\midrule
\endhead
no & 2084.00 & 29.72 & 7.09 & 30.00 & 25.00 & 35.00 & 10.00 \\
yes & 200.00 & 31.44 & 7.72 & 31.00 & 25.00 & 37.00 & 12.00 \\
\bottomrule
\end{longtable}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#t{-}test}
\FunctionTok{t.test}\NormalTok{(age }\SpecialCharTok{\textasciitilde{}}\NormalTok{ vaccine\_cov, }\AttributeTok{data =}\NormalTok{ data\_final)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Welch Two Sample t-test
## 
## data:  age by vaccine_cov
## t = -3.0298, df = 232.39, p-value = 0.002724
## alternative hypothesis: true difference in means between group no and group yes is not equal to 0
## 95 percent confidence interval:
##  -2.8372657 -0.6012756
## sample estimates:
##  mean in group no mean in group yes 
##          29.72073          31.44000
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#effect size}
\NormalTok{c\_cohen }\OtherTok{\textless{}{-}} \FunctionTok{cohens\_d}\NormalTok{(age }\SpecialCharTok{\textasciitilde{}} \FunctionTok{as.factor}\NormalTok{(vaccine\_cov), }\AttributeTok{data=}\NormalTok{data\_final)}
\NormalTok{c\_cohen}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cohen's d |         95% CI
## --------------------------
## -0.24     | [-0.39, -0.10]
## 
## - Estimated using pooled SD.
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{interpret\_d}\NormalTok{(c\_cohen}\SpecialCharTok{$}\NormalTok{Cohens\_d,}\AttributeTok{rules=}\StringTok{"cohen1988"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## [1] "small"
## (Rules: cohen1988)
\end{verbatim}

\hypertarget{residence-area}{%
\subsubsection{Residence area}\label{residence-area}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(residence, vaccine\_cov, }\AttributeTok{prop =} \StringTok{"c"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{FALSE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Column Proportions  
## residence * vaccine_cov  
## Data Frame: data_final  
## 
## ----------- ------------- --------------- -------------- ---------------
##               vaccine_cov              no            yes           Total
##   residence                                                             
##   periurban                    6 (  0.3%)     0 (  0.0%)      6 (  0.3%)
##       rural                  113 (  5.8%)     9 (  4.8%)    122 (  5.7%)
##       urban                 1838 ( 93.9%)   179 ( 95.2%)   2017 ( 94.0%)
##       Total                 1957 (100.0%)   188 (100.0%)   2145 (100.0%)
## ----------- ------------- --------------- -------------- ---------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{residence, data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$residence and data_final$vaccine_cov
## p-value = 0.8508
## alternative hypothesis: two.sided
\end{verbatim}

\hypertarget{residence-area-2-grouping-the-categories-urban-and-periurban}{%
\subsubsection{Residence area 2 (grouping the categories urban and
periurban)}\label{residence-area-2-grouping-the-categories-urban-and-periurban}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(residence2, vaccine\_cov, }\AttributeTok{prop =} \StringTok{"c"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Column Proportions  
## residence2 * vaccine_cov  
## Data Frame: data_final  
## 
## 
## ----------------- ------------- --------------- -------------- ---------------
##                     vaccine_cov              no            yes           Total
##        residence2                                                             
##             rural                  113 (  5.8%)     9 (  4.8%)    122 (  5.7%)
##   urban/periurban                 1844 ( 94.2%)   179 ( 95.2%)   2023 ( 94.3%)
##             Total                 1957 (100.0%)   188 (100.0%)   2145 (100.0%)
## ----------------- ------------- --------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.1546      1    0.6941  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.22        0.61       2.44   
## ----------------------------------
\end{verbatim}

\hypertarget{comorbities}{%
\subsection{Comorbities}\label{comorbities}}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Cardiac}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{cardiac =} \FunctionTok{case\_when}\NormalTok{(CARDIOPATI }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             CARDIOPATI }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Hematologic}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{hematologic =} \FunctionTok{case\_when}\NormalTok{(HEMATOLOGI }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                 HEMATOLOGI }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                 \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Hepatic}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{hepatic =} \FunctionTok{case\_when}\NormalTok{(HEPATICA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             HEPATICA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Asthma}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{asthma =} \FunctionTok{case\_when}\NormalTok{(ASMA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                            ASMA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                            \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Diabetes}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{diabetes =} \FunctionTok{case\_when}\NormalTok{(DIABETES }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                              DIABETES }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                              \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Neurologic}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{neurologic =} \FunctionTok{case\_when}\NormalTok{(NEUROLOGIC }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                NEUROLOGIC }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Pneumologic}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{pneumologic =} \FunctionTok{case\_when}\NormalTok{(PNEUMOPATI }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                 PNEUMOPATI }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                 \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Imunossupression}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{imuno =} \FunctionTok{case\_when}\NormalTok{(IMUNODEPRE }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                           IMUNODEPRE }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                           \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Renal}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{renal =} \FunctionTok{case\_when}\NormalTok{(RENAL }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                           RENAL }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                           \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\#Obesity}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{obesity =} \FunctionTok{case\_when}\NormalTok{(OBESIDADE }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             OBESIDADE }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\hypertarget{cardiac}{%
\subsubsection{Cardiac}\label{cardiac}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, cardiac, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * cardiac  
## Data Frame: data_final  
## 
## 
## ------------- --------- ------------- ------------- --------------
##                 cardiac            no           yes          Total
##   vaccine_cov                                                     
##            no             738 (87.6%)   104 (12.4%)   842 (100.0%)
##           yes              71 (76.3%)    22 (23.7%)    93 (100.0%)
##         Total             809 (86.5%)   126 (13.5%)   935 (100.0%)
## ------------- --------- ------------- ------------- --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    8.2348      1    0.0041  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     2.20        1.31       3.70   
## ----------------------------------
\end{verbatim}

\hypertarget{hematologic}{%
\subsubsection{Hematologic}\label{hematologic}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, hematologic, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{FALSE}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * hematologic  
## Data Frame: data_final  
## 
## 
## ------------- ------------- ------------- ---------- --------------
##                 hematologic            no        yes          Total
##   vaccine_cov                                                      
##            no                 807 (99.1%)   7 (0.9%)   814 (100.0%)
##           yes                  87 (97.8%)   2 (2.2%)    89 (100.0%)
##         Total                 894 (99.0%)   9 (1.0%)   903 (100.0%)
## ------------- ------------- ------------- ---------- --------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     2.65        0.54      12.96   
## ----------------------------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{hematologic, data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$hematologic and data_final$vaccine_cov
## p-value = 0.2198
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##   0.2642886 14.1850125
## sample estimates:
## odds ratio 
##   2.646116
\end{verbatim}

\hypertarget{diabetes}{%
\subsubsection{Diabetes}\label{diabetes}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{diabetes, }\AttributeTok{chisq=}\ConstantTok{TRUE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * diabetes  
## Data Frame: data_final  
## 
## 
## ------------- ---------- ------------- ------------- --------------
##                 diabetes            no           yes          Total
##   vaccine_cov                                                      
##            no              708 (83.1%)   144 (16.9%)   852 (100.0%)
##           yes               73 (77.7%)    21 (22.3%)    94 (100.0%)
##         Total              781 (82.6%)   165 (17.4%)   946 (100.0%)
## ------------- ---------- ------------- ------------- --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##     1.382      1    0.2398  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.41        0.84       2.37   
## ----------------------------------
\end{verbatim}

\hypertarget{obesity}{%
\subsubsection{Obesity}\label{obesity}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{obesity, }\AttributeTok{chisq=}\ConstantTok{TRUE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * obesity  
## Data Frame: data_final  
## 
## 
## ------------- --------- ------------- ------------- --------------
##                 obesity            no           yes          Total
##   vaccine_cov                                                     
##            no             680 (78.1%)   191 (21.9%)   871 (100.0%)
##           yes              76 (84.4%)    14 (15.6%)    90 (100.0%)
##         Total             756 (78.7%)   205 (21.3%)   961 (100.0%)
## ------------- --------- ------------- ------------- --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    1.6129      1    0.2041  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.66        0.36       1.19   
## ----------------------------------
\end{verbatim}

\hypertarget{asthma}{%
\subsubsection{Asthma}\label{asthma}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{asthma, }\AttributeTok{chisq=}\ConstantTok{TRUE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * asthma  
## Data Frame: data_final  
## 
## 
## ------------- -------- ------------- ------------ --------------
##                 asthma            no          yes          Total
##   vaccine_cov                                                   
##            no            767 (92.2%)   65 ( 7.8%)   832 (100.0%)
##           yes             81 (90.0%)    9 (10.0%)    90 (100.0%)
##         Total            848 (92.0%)   74 ( 8.0%)   922 (100.0%)
## ------------- -------- ------------- ------------ --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.2718      1    0.6021  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.31        0.63       2.73   
## ----------------------------------
\end{verbatim}

\hypertarget{hepatic}{%
\subsubsection{Hepatic}\label{hepatic}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{hepatic, }\AttributeTok{chisq=}\ConstantTok{FALSE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * hepatic  
## Data Frame: data_final  
## 
## 
## ------------- --------- -------------- ---------- --------------
##                 hepatic             no        yes          Total
##   vaccine_cov                                                   
##            no             807 ( 99.6%)   3 (0.4%)   810 (100.0%)
##           yes              88 ( 98.9%)   1 (1.1%)    89 (100.0%)
##         Total             895 ( 99.6%)   4 (0.4%)   899 (100.0%)
## ------------- --------- -------------- ---------- --------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     3.06        0.31      29.70   
## ----------------------------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{hepatic)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$vaccine_cov and data_final$hepatic
## p-value = 0.3415
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##   0.05758056 38.46642499
## sample estimates:
## odds ratio 
##   3.050859
\end{verbatim}

\hypertarget{neurologic}{%
\subsubsection{Neurologic}\label{neurologic}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{neurologic, }\AttributeTok{chisq=}\ConstantTok{FALSE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * neurologic  
## Data Frame: data_final  
## 
## 
## ------------- ------------ ------------- ----------- --------------
##                 neurologic            no         yes          Total
##   vaccine_cov                                                      
##            no                802 (98.9%)    9 (1.1%)   811 (100.0%)
##           yes                 86 (97.7%)    2 (2.3%)    88 (100.0%)
##         Total                888 (98.8%)   11 (1.2%)   899 (100.0%)
## ------------- ------------ ------------- ----------- --------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     2.07        0.44       9.75   
## ----------------------------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{neurologic)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$vaccine_cov and data_final$neurologic
## p-value = 0.2936
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##   0.2143274 10.2318114
## sample estimates:
## odds ratio 
##   2.070139
\end{verbatim}

\hypertarget{pneumologic}{%
\subsubsection{Pneumologic}\label{pneumologic}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{pneumologic, }\AttributeTok{chisq=}\ConstantTok{FALSE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * pneumologic  
## Data Frame: data_final  
## 
## 
## ------------- ------------- ------------- ----------- --------------
##                 pneumologic            no         yes          Total
##   vaccine_cov                                                       
##            no                 805 (98.9%)    9 (1.1%)   814 (100.0%)
##           yes                  86 (96.6%)    3 (3.4%)    89 (100.0%)
##         Total                 891 (98.7%)   12 (1.3%)   903 (100.0%)
## ------------- ------------- ------------- ----------- --------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     3.12        0.83      11.74   
## ----------------------------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{pneumologic)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$vaccine_cov and data_final$pneumologic
## p-value = 0.1059
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##   0.5323484 12.7897697
## sample estimates:
## odds ratio 
##   3.114462
\end{verbatim}

\hypertarget{imunossupression}{%
\subsubsection{Imunossupression}\label{imunossupression}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{imuno, }\AttributeTok{chisq=}\ConstantTok{FALSE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * imuno  
## Data Frame: data_final  
## 
## 
## ------------- ------- ------------- ----------- --------------
##                 imuno            no         yes          Total
##   vaccine_cov                                                 
##            no           801 (98.6%)   11 (1.4%)   812 (100.0%)
##           yes            84 (94.4%)    5 (5.6%)    89 (100.0%)
##         Total           885 (98.2%)   16 (1.8%)   901 (100.0%)
## ------------- ------- ------------- ----------- --------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     4.33        1.47      12.77   
## ----------------------------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{imuno, data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$imuno and data_final$vaccine_cov
## p-value = 0.01526
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##   1.149292 13.896222
## sample estimates:
## odds ratio 
##    4.32279
\end{verbatim}

\hypertarget{renal}{%
\subsubsection{Renal}\label{renal}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ctable}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov, data\_final}\SpecialCharTok{$}\NormalTok{renal, }\AttributeTok{chisq=}\ConstantTok{FALSE}\NormalTok{, }\AttributeTok{prop=}\StringTok{"r"}\NormalTok{,  }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{OR =} \ConstantTok{TRUE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * renal  
## Data Frame: data_final  
## 
## 
## ------------- ------- ------------- ----------- --------------
##                 renal            no         yes          Total
##   vaccine_cov                                                 
##            no           797 (98.9%)    9 (1.1%)   806 (100.0%)
##           yes            87 (97.8%)    2 (2.2%)    89 (100.0%)
##         Total           884 (98.8%)   11 (1.2%)   895 (100.0%)
## ------------- ------- ------------- ----------- --------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     2.04        0.43       9.57   
## ----------------------------------
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{fisher.test}\NormalTok{(data\_final}\SpecialCharTok{$}\NormalTok{renal, data\_final}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Fisher's Exact Test for Count Data
## 
## data:  data_final$renal and data_final$vaccine_cov
## p-value = 0.3002
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
##   0.21058 10.04877
## sample estimates:
## odds ratio 
##   2.033657
\end{verbatim}

\hypertarget{symptoms}{%
\subsection{Symptoms}\label{symptoms}}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# Fever}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{fever =} \FunctionTok{case\_when}\NormalTok{(FEBRE }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                           FEBRE }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                           \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Cough}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{cough =} \FunctionTok{case\_when}\NormalTok{(TOSSE }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                           TOSSE }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                           \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Sore throat}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{sore\_throat =} \FunctionTok{case\_when}\NormalTok{(GARGANTA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                 GARGANTA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                 \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Dyspnea}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{dyspnea =} \FunctionTok{case\_when}\NormalTok{(DISPNEIA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             DISPNEIA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Respiratory discomfort}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{resp\_disc =} \FunctionTok{case\_when}\NormalTok{(DESC\_RESP }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                               DESC\_RESP }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                               \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Desaturation}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{desaturation =} \FunctionTok{case\_when}\NormalTok{(SATURACAO }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                  SATURACAO }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                  \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Diarrhea}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{diarrhea =} \FunctionTok{case\_when}\NormalTok{(DIARREIA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                              DIARREIA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                              \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Vomit}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{vomit =} \FunctionTok{case\_when}\NormalTok{(VOMITO }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                           VOMITO }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                           \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Abdominal pain}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{abd\_pain =} \FunctionTok{case\_when}\NormalTok{(DOR\_ABD }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                              DOR\_ABD }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                              \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Fatigue}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{fatigue =} \FunctionTok{case\_when}\NormalTok{(FADIGA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             FADIGA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Olfactory loss}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{olfac\_loss =} \FunctionTok{case\_when}\NormalTok{(PERD\_OLFT }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                PERD\_OLFT }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Loss of taste}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{loss\_taste =} \FunctionTok{case\_when}\NormalTok{(PERD\_PALA }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                PERD\_PALA }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Any respiratory symptom}
\NormalTok{df }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{select}\NormalTok{(dyspnea,fatigue,desaturation,resp\_disc)}

\NormalTok{soma }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)\{}
  \ControlFlowTok{if}\NormalTok{ (}\FunctionTok{sum}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(x))}\SpecialCharTok{==}\DecValTok{4}\NormalTok{)}
    \FunctionTok{return}\NormalTok{(}\ConstantTok{NA\_character\_}\NormalTok{)}
  \ControlFlowTok{else}
    \FunctionTok{return}\NormalTok{(}\FunctionTok{sum}\NormalTok{(}\SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(x) }\SpecialCharTok{\&}\NormalTok{ x}\SpecialCharTok{==}\StringTok{"yes"}\NormalTok{)) }
\NormalTok{\}}
\NormalTok{data\_final}\SpecialCharTok{$}\NormalTok{qt\_sintomas\_resp\_aux }\OtherTok{\textless{}{-}} \FunctionTok{apply}\NormalTok{(df,}\DecValTok{1}\NormalTok{,soma)}

\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{resp\_symp =} \FunctionTok{case\_when}\NormalTok{(qt\_sintomas\_resp\_aux }\SpecialCharTok{\textgreater{}=}\DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                               qt\_sintomas\_resp\_aux }\SpecialCharTok{==}\DecValTok{0} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                               \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}
\CommentTok{\# Any symptom}
\NormalTok{df }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{select}\NormalTok{(dyspnea,fatigue,desaturation,resp\_disc,}
\NormalTok{         fever,cough,sore\_throat,diarrhea,vomit,abd\_pain,olfac\_loss,loss\_taste)}
\NormalTok{soma }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)\{}
  \ControlFlowTok{if}\NormalTok{ (}\FunctionTok{sum}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(x))}\SpecialCharTok{==}\DecValTok{12}\NormalTok{)}
    \FunctionTok{return}\NormalTok{(}\ConstantTok{NA\_character\_}\NormalTok{)}
  \ControlFlowTok{else}
    \FunctionTok{return}\NormalTok{(}\FunctionTok{sum}\NormalTok{(}\SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(x) }\SpecialCharTok{\&}\NormalTok{ x}\SpecialCharTok{==}\StringTok{"yes"}\NormalTok{)) }
\NormalTok{\}}
\NormalTok{data\_final}\SpecialCharTok{$}\NormalTok{qt\_sintomas\_aux }\OtherTok{\textless{}{-}} \FunctionTok{apply}\NormalTok{(df,}\DecValTok{1}\NormalTok{,soma)}

\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{  data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{symptom =} \FunctionTok{case\_when}\NormalTok{(qt\_sintomas\_aux }\SpecialCharTok{\textgreater{}=} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             qt\_sintomas\_aux }\SpecialCharTok{==} \DecValTok{0} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\hypertarget{fever}{%
\subsubsection{Fever}\label{fever}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, fever, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * fever  
## Data Frame: data_final  
## 
## 
## ------------- ------- ------------- -------------- ---------------
##                 fever            no            yes           Total
##   vaccine_cov                                                     
##            no           783 (42.1%)   1077 (57.9%)   1860 (100.0%)
##           yes            94 (53.4%)     82 (46.6%)    176 (100.0%)
##         Total           877 (43.1%)   1159 (56.9%)   2036 (100.0%)
## ------------- ------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    7.9362      1    0.0048  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.63        0.47       0.86   
## ----------------------------------
\end{verbatim}

\hypertarget{cough}{%
\subsubsection{Cough}\label{cough}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, cough, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * cough  
## Data Frame: data_final  
## 
## 
## ------------- ------- ------------- -------------- ---------------
##                 cough            no            yes           Total
##   vaccine_cov                                                     
##            no           406 (20.9%)   1532 (79.1%)   1938 (100.0%)
##           yes            45 (24.7%)    137 (75.3%)    182 (100.0%)
##         Total           451 (21.3%)   1669 (78.7%)   2120 (100.0%)
## ------------- ------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    1.1998      1    0.2734  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.81        0.57       1.15   
## ----------------------------------
\end{verbatim}

\hypertarget{sore-throat}{%
\subsubsection{Sore throat}\label{sore-throat}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, sore\_throat, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * sore_throat  
## Data Frame: data_final  
## 
## 
## ------------- ------------- -------------- ------------- ---------------
##                 sore_throat             no           yes           Total
##   vaccine_cov                                                           
##            no                 1263 (73.9%)   447 (26.1%)   1710 (100.0%)
##           yes                  126 (79.2%)    33 (20.8%)    159 (100.0%)
##         Total                 1389 (74.3%)   480 (25.7%)   1869 (100.0%)
## ------------- ------------- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    1.9375      1    0.1639  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.74        0.50       1.10   
## ----------------------------------
\end{verbatim}

\hypertarget{dyspnea}{%
\subsubsection{Dyspnea}\label{dyspnea}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, dyspnea, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * dyspnea  
## Data Frame: data_final  
## 
## 
## ------------- --------- ------------- -------------- ---------------
##                 dyspnea            no            yes           Total
##   vaccine_cov                                                       
##            no             565 (29.5%)   1349 (70.5%)   1914 (100.0%)
##           yes              76 (43.9%)     97 (56.1%)    173 (100.0%)
##         Total             641 (30.7%)   1446 (69.3%)   2087 (100.0%)
## ------------- --------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    14.8145     1     1e-04  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.53        0.39       0.73   
## ----------------------------------
\end{verbatim}

\hypertarget{respiratory-discomfort}{%
\subsubsection{Respiratory discomfort}\label{respiratory-discomfort}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, resp\_disc, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * resp_disc  
## Data Frame: data_final  
## 
## 
## ------------- ----------- ------------- -------------- ---------------
##                 resp_disc            no            yes           Total
##   vaccine_cov                                                         
##            no               792 (43.5%)   1028 (56.5%)   1820 (100.0%)
##           yes                95 (55.2%)     77 (44.8%)    172 (100.0%)
##         Total               887 (44.5%)   1105 (55.5%)   1992 (100.0%)
## ------------- ----------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    8.2652      1     0.004  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.62        0.46       0.86   
## ----------------------------------
\end{verbatim}

\hypertarget{desaturation}{%
\subsubsection{Desaturation}\label{desaturation}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, desaturation, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * desaturation  
## Data Frame: data_final  
## 
## 
## ------------- -------------- ------------- -------------- ---------------
##                 desaturation            no            yes           Total
##   vaccine_cov                                                            
##            no                  815 (44.3%)   1025 (55.7%)   1840 (100.0%)
##           yes                  103 (59.9%)     69 (40.1%)    172 (100.0%)
##         Total                  918 (45.6%)   1094 (54.4%)   2012 (100.0%)
## ------------- -------------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    14.7886     1     1e-04  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.53        0.39       0.73   
## ----------------------------------
\end{verbatim}

\hypertarget{diarrhea}{%
\subsubsection{Diarrhea}\label{diarrhea}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, diarrhea, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * diarrhea  
## Data Frame: data_final  
## 
## 
## ------------- ---------- -------------- ------------- ---------------
##                 diarrhea             no           yes           Total
##   vaccine_cov                                                        
##            no              1488 (88.7%)   189 (11.3%)   1677 (100.0%)
##           yes               143 (89.9%)    16 (10.1%)    159 (100.0%)
##         Total              1631 (88.8%)   205 (11.2%)   1836 (100.0%)
## ------------- ---------- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##     0.109      1    0.7412  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.88        0.51       1.51   
## ----------------------------------
\end{verbatim}

\hypertarget{vomit}{%
\subsubsection{Vomit}\label{vomit}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, vomit, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * vomit  
## Data Frame: data_final  
## 
## 
## ------------- ------- -------------- ------------- ---------------
##                 vomit             no           yes           Total
##   vaccine_cov                                                     
##            no           1480 (88.0%)   202 (12.0%)   1682 (100.0%)
##           yes            143 (89.9%)    16 (10.1%)    159 (100.0%)
##         Total           1623 (88.2%)   218 (11.8%)   1841 (100.0%)
## ------------- ------- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.3573      1     0.55   
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.82        0.48       1.40   
## ----------------------------------
\end{verbatim}

\hypertarget{abdominal-pain}{%
\subsubsection{Abdominal pain}\label{abdominal-pain}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, abd\_pain, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * abd_pain  
## Data Frame: data_final  
## 
## 
## ------------- ---------- -------------- ------------- ---------------
##                 abd_pain             no           yes           Total
##   vaccine_cov                                                        
##            no              1494 (90.1%)   164 ( 9.9%)   1658 (100.0%)
##           yes               138 (88.5%)    18 (11.5%)    156 (100.0%)
##         Total              1632 (90.0%)   182 (10.0%)   1814 (100.0%)
## ------------- ---------- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.2655      1    0.6064  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.19        0.71       1.99   
## ----------------------------------
\end{verbatim}

\hypertarget{fatigue}{%
\subsubsection{Fatigue}\label{fatigue}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, fatigue, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * fatigue  
## Data Frame: data_final  
## 
## 
## ------------- --------- -------------- ------------- ---------------
##                 fatigue             no           yes           Total
##   vaccine_cov                                                       
##            no             1147 (66.0%)   590 (34.0%)   1737 (100.0%)
##           yes              110 (67.5%)    53 (32.5%)    163 (100.0%)
##         Total             1257 (66.2%)   643 (33.8%)   1900 (100.0%)
## ------------- --------- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.0829      1    0.7735  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.94        0.67       1.32   
## ----------------------------------
\end{verbatim}

\hypertarget{olfactory-loss}{%
\subsubsection{Olfactory loss}\label{olfactory-loss}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, olfac\_loss, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * olfac_loss  
## Data Frame: data_final  
## 
## 
## ------------- ------------ -------------- ------------- ---------------
##                 olfac_loss             no           yes           Total
##   vaccine_cov                                                          
##            no                1372 (81.6%)   310 (18.4%)   1682 (100.0%)
##           yes                 127 (79.4%)    33 (20.6%)    160 (100.0%)
##         Total                1499 (81.4%)   343 (18.6%)   1842 (100.0%)
## ------------- ------------ -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.3308      1    0.5652  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.15        0.77       1.72   
## ----------------------------------
\end{verbatim}

\hypertarget{loss-of-taste}{%
\subsubsection{Loss of taste}\label{loss-of-taste}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, loss\_taste, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * loss_taste  
## Data Frame: data_final  
## 
## 
## ------------- ------------ -------------- ------------- ---------------
##                 loss_taste             no           yes           Total
##   vaccine_cov                                                          
##            no                1403 (83.2%)   284 (16.8%)   1687 (100.0%)
##           yes                 129 (81.1%)    30 (18.9%)    159 (100.0%)
##         Total                1532 (83.0%)   314 (17.0%)   1846 (100.0%)
## ------------- ------------ -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    0.2937      1    0.5879  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     1.15        0.76       1.74   
## ----------------------------------
\end{verbatim}

\hypertarget{any-respiratory-symptom}{%
\subsubsection{Any respiratory symptom}\label{any-respiratory-symptom}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, resp\_symp, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * resp_symp  
## Data Frame: data_final  
## 
## 
## ------------- ----------- ------------- -------------- ---------------
##                 resp_symp            no            yes           Total
##   vaccine_cov                                                         
##            no               361 (18.2%)   1618 (81.8%)   1979 (100.0%)
##           yes                56 (30.6%)    127 (69.4%)    183 (100.0%)
##         Total               417 (19.3%)   1745 (80.7%)   2162 (100.0%)
## ------------- ----------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    15.6528     1     1e-04  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.51        0.36       0.71   
## ----------------------------------
\end{verbatim}

\hypertarget{any-symptom}{%
\subsubsection{Any symptom}\label{any-symptom}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, symptom, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * symptom  
## Data Frame: data_final  
## 
## 
## ------------- --------- ----------- -------------- ---------------
##                 symptom          no            yes           Total
##   vaccine_cov                                                     
##            no             78 (3.8%)   1980 (96.2%)   2058 (100.0%)
##           yes             16 (8.2%)    178 (91.8%)    194 (100.0%)
##         Total             94 (4.2%)   2158 (95.8%)   2252 (100.0%)
## ------------- --------- ----------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##     7.727      1    0.0054  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.44        0.25       0.77   
## ----------------------------------
\end{verbatim}

\hypertarget{outcome}{%
\subsection{Outcome}\label{outcome}}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\# ICU}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{icu =} \FunctionTok{case\_when}\NormalTok{(UTI }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                         UTI }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                         \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}


\CommentTok{\# Length time in ICU}
\NormalTok{data\_final}\OtherTok{\textless{}{-}}\NormalTok{  data\_final}\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{dt\_enticu  =} \FunctionTok{as.Date}\NormalTok{(DT\_ENTUTI,  }\AttributeTok{format =} \StringTok{"\%d/\%m/\%Y"}\NormalTok{),}
         \AttributeTok{dt\_exicu =} \FunctionTok{as.Date}\NormalTok{(DT\_SAIDUTI, }\AttributeTok{format =} \StringTok{"\%d/\%m/\%Y"}\NormalTok{), }
         \AttributeTok{time\_icu =} \FunctionTok{as.numeric}\NormalTok{(dt\_exicu }\SpecialCharTok{{-}}\NormalTok{ dt\_enticu)}
\NormalTok{  )}

\CommentTok{\# ventilatory support}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{ventilatory\_support =} \FunctionTok{case\_when}\NormalTok{(SUPORT\_VEN }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"invasive"}\NormalTok{,}
\NormalTok{                                SUPORT\_VEN }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{\textasciitilde{}} \StringTok{"non{-}invasive"}\NormalTok{,}
\NormalTok{                                  SUPORT\_VEN }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}

\CommentTok{\# Intubation}
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{intubation =} \FunctionTok{case\_when}\NormalTok{(SUPORT\_VEN }\SpecialCharTok{==} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                                SUPORT\_VEN }\SpecialCharTok{==} \DecValTok{2} \SpecialCharTok{|}\NormalTok{ SUPORT\_VEN }\SpecialCharTok{==} \DecValTok{3} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                                \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\hypertarget{icu}{%
\subsubsection{ICU}\label{icu}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, icu, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * icu  
## Data Frame: data_final  
## 
## 
## ------------- ----- -------------- ------------- ---------------
##                 icu             no           yes           Total
##   vaccine_cov                                                   
##            no         1239 (62.6%)   740 (37.4%)   1979 (100.0%)
##           yes          143 (76.5%)    44 (23.5%)    187 (100.0%)
##         Total         1382 (63.8%)   784 (36.2%)   2166 (100.0%)
## ------------- ----- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    13.6244     1     2e-04  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.52        0.36       0.73   
## ----------------------------------
\end{verbatim}

\hypertarget{length-time-in-icu}{%
\subsubsection{Length time in ICU}\label{length-time-in-icu}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{data\_final\_aux }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{ (icu }\SpecialCharTok{==} \StringTok{"yes"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{datasummary}\NormalTok{((vaccine\_cov) }\SpecialCharTok{\textasciitilde{}}\NormalTok{ time\_icu}\SpecialCharTok{*}\NormalTok{(n}\SpecialCharTok{+}\NormalTok{media}\SpecialCharTok{+}\NormalTok{DP}\SpecialCharTok{+}\NormalTok{mediana}\SpecialCharTok{+}\NormalTok{q25}\SpecialCharTok{+}\NormalTok{q75}\SpecialCharTok{+}\NormalTok{IQR),}
            \AttributeTok{data =}\NormalTok{ data\_final\_aux, }\AttributeTok{output =} \StringTok{\textquotesingle{}markdown\textquotesingle{}}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{longtable}[]{@{}lrrrrrrr@{}}
\toprule
& n & media & DP & mediana & q25 & q75 & IQR \\
\midrule
\endhead
no & 548.00 & 13.09 & 12.22 & 10.00 & 5.00 & 18.00 & 13.00 \\
yes & 21.00 & 9.38 & 9.30 & 5.00 & 3.00 & 13.00 & 10.00 \\
\bottomrule
\end{longtable}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#t{-}test}
\FunctionTok{t.test}\NormalTok{(time\_icu }\SpecialCharTok{\textasciitilde{}}\NormalTok{ vaccine\_cov, }\AttributeTok{data =}\NormalTok{ data\_final\_aux)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Welch Two Sample t-test
## 
## data:  time_icu by vaccine_cov
## t = 1.7692, df = 22.727, p-value = 0.09028
## alternative hypothesis: true difference in means between group no and group yes is not equal to 0
## 95 percent confidence interval:
##  -0.6305326  8.0474599
## sample estimates:
##  mean in group no mean in group yes 
##         13.089416          9.380952
\end{verbatim}

\hypertarget{ventilatory-support}{%
\subsubsection{Ventilatory support}\label{ventilatory-support}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, ventilatory\_support, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * ventilatory_support  
## Data Frame: data_final  
## 
## 
## ------------- --------------------- ------------- ------------- -------------- ---------------
##                 ventilatory_support      invasive            no   non-invasive           Total
##   vaccine_cov                                                                                 
##            no                         368 (18.8%)   711 (36.3%)    880 (44.9%)   1959 (100.0%)
##           yes                           9 ( 4.8%)    99 (52.4%)     81 (42.9%)    189 (100.0%)
##         Total                         377 (17.6%)   810 (37.7%)    961 (44.7%)   2148 (100.0%)
## ------------- --------------------- ------------- ------------- -------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    31.3063     2       0    
## ----------------------------
\end{verbatim}

\hypertarget{intubation}{%
\subsubsection{Intubation}\label{intubation}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, intubation, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * intubation  
## Data Frame: data_final  
## 
## 
## ------------- ------------ -------------- ------------- ---------------
##                 intubation             no           yes           Total
##   vaccine_cov                                                          
##            no                1591 (81.2%)   368 (18.8%)   1959 (100.0%)
##           yes                 180 (95.2%)     9 ( 4.8%)    189 (100.0%)
##         Total                1771 (82.4%)   377 (17.6%)   2148 (100.0%)
## ------------- ------------ -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    22.4651     1       0    
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.22        0.11       0.43   
## ----------------------------------
\end{verbatim}

\hypertarget{death}{%
\subsubsection{Death}\label{death}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_final, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, death, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * death  
## Data Frame: data_final  
## 
## 
## ------------- ------- -------------- ------------- ---------------
##                 death           cure         death           Total
##   vaccine_cov                                                     
##            no           1790 (85.9%)   294 (14.1%)   2084 (100.0%)
##           yes            194 (97.0%)     6 ( 3.0%)    200 (100.0%)
##         Total           1984 (86.9%)   300 (13.1%)   2284 (100.0%)
## ------------- ------- -------------- ------------- ---------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    18.7715     1       0    
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##    0.188       0.083      0.428   
## ----------------------------------
\end{verbatim}

\hypertarget{propensity-scoring-method-psm---information-about-date-of-second-dose}{%
\section{Propensity Scoring Method (PSM) - information about date of
second
dose}\label{propensity-scoring-method-psm---information-about-date-of-second-dose}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{data\_final }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{vaccine1 =} \FunctionTok{ifelse}\NormalTok{(vaccine\_cov }\SpecialCharTok{==} \StringTok{"yes"}\NormalTok{, }\DecValTok{1}\NormalTok{, }\DecValTok{0}\NormalTok{),}
         \AttributeTok{id =} \DecValTok{1}\SpecialCharTok{:}\FunctionTok{dim}\NormalTok{(data\_final)[}\DecValTok{1}\NormalTok{]) }

\NormalTok{data\_final1 }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{select}\NormalTok{(id, vaccine1, age, cardiac)}

\NormalTok{data\_final1 }\OtherTok{\textless{}{-}}\NormalTok{ data\_final1 }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{mutate}\NormalTok{(}
    \AttributeTok{cardiac1 =} \FunctionTok{ifelse}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(cardiac) }\SpecialCharTok{==} \ConstantTok{TRUE}\NormalTok{, }\StringTok{"na"}\NormalTok{, cardiac)}
\NormalTok{  )}
  
\CommentTok{\#PSM}
\NormalTok{psm1 }\OtherTok{\textless{}{-}} \FunctionTok{matchit}\NormalTok{(vaccine1 }\SpecialCharTok{\textasciitilde{}}\NormalTok{ age }\SpecialCharTok{+}\NormalTok{ cardiac1, }\AttributeTok{data =}\NormalTok{ data\_final1, }\AttributeTok{method =} \StringTok{"nearest"}\NormalTok{, }\AttributeTok{ratio =}\DecValTok{1}\NormalTok{)}

\FunctionTok{summary}\NormalTok{(psm1)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
## Call:
## matchit(formula = vaccine1 ~ age + cardiac1, data = data_final1, 
##     method = "nearest", ratio = 1)
## 
## Summary of Balance for All Data:
##             Means Treated Means Control Std. Mean Diff. Var. Ratio eCDF Mean
## distance           0.0965        0.0867          0.2648     1.9872    0.0595
## age               31.4400       29.7207          0.2227     1.1850    0.0409
## cardiac1na         0.5350        0.5960         -0.1222          .    0.0610
## cardiac1no         0.3550        0.3541          0.0018          .    0.0009
## cardiac1yes        0.1100        0.0499          0.1921          .    0.0601
##             eCDF Max
## distance      0.1179
## age           0.1056
## cardiac1na    0.0610
## cardiac1no    0.0009
## cardiac1yes   0.0601
## 
## 
## Summary of Balance for Matched Data:
##             Means Treated Means Control Std. Mean Diff. Var. Ratio eCDF Mean
## distance           0.0965        0.0965          0.0010     1.0023    0.0002
## age               31.4400       31.2950          0.0188     1.0431    0.0035
## cardiac1na         0.5350        0.5300          0.0100          .    0.0050
## cardiac1no         0.3550        0.3550          0.0000          .    0.0000
## cardiac1yes        0.1100        0.1150         -0.0160          .    0.0050
##             eCDF Max Std. Pair Dist.
## distance       0.010          0.0042
## age            0.015          0.0214
## cardiac1na     0.005          0.0100
## cardiac1no     0.000          0.0000
## cardiac1yes    0.005          0.0160
## 
## Percent Balance Improvement:
##             Std. Mean Diff. Var. Ratio eCDF Mean eCDF Max
## distance               99.6       99.7      99.6     91.5
## age                    91.6       75.2      91.6     85.8
## cardiac1na             91.8          .      91.8     91.8
## cardiac1no            100.0          .     100.0    100.0
## cardiac1yes            91.7          .      91.7     91.7
## 
## Sample Sizes:
##           Control Treated
## All          2084     200
## Matched       200     200
## Unmatched    1884       0
## Discarded       0       0
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{plot}\NormalTok{(psm1, }\AttributeTok{type =} \StringTok{"jitter"}\NormalTok{, }\AttributeTok{interactive =} \ConstantTok{FALSE}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-73-1.pdf}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{plot}\NormalTok{(psm1, }\AttributeTok{type =} \StringTok{"qq"}\NormalTok{, }\AttributeTok{interactive =} \ConstantTok{FALSE}\NormalTok{,}
     \AttributeTok{which.xs =} \FunctionTok{c}\NormalTok{(}\StringTok{"age"}\NormalTok{, }\StringTok{"cardiac1"}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-73-2.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-73-3.pdf}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{plot}\NormalTok{(}\FunctionTok{summary}\NormalTok{(psm1))}
\end{Highlighting}
\end{Shaded}

\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-73-4.pdf}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#Selecting only the selected observations}
\NormalTok{data\_aux }\OtherTok{\textless{}{-}}\NormalTok{ data\_final1[psm1}\SpecialCharTok{$}\NormalTok{weights}\SpecialCharTok{==}\DecValTok{1}\NormalTok{, ]}

\CommentTok{\#Now let\textquotesingle{}s join data\_aux with data\_final}

\NormalTok{data\_psm }\OtherTok{\textless{}{-}} \FunctionTok{right\_join}\NormalTok{(data\_final, data\_aux, }\AttributeTok{by=} \FunctionTok{c}\NormalTok{(}\StringTok{"id"}\NormalTok{, }\StringTok{"vaccine1"}\NormalTok{, }\StringTok{"age"}\NormalTok{, }\StringTok{"cardiac"}\NormalTok{))}

\FunctionTok{freq}\NormalTok{(data\_psm}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##       n  % val%
## no  200 50   50
## yes 200 50   50
\end{verbatim}

\hypertarget{for-outcomes}{%
\subsection{For outcomes}\label{for-outcomes}}

\hypertarget{icu-1}{%
\subsubsection{ICU}\label{icu-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_psm, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, icu, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * icu  
## Data Frame: data_psm  
## 
## 
## ------------- ----- ------------- ------------- --------------
##                 icu            no           yes          Total
##   vaccine_cov                                                 
##            no         121 (63.7%)    69 (36.3%)   190 (100.0%)
##           yes         143 (76.5%)    44 (23.5%)   187 (100.0%)
##         Total         264 (70.0%)   113 (30.0%)   377 (100.0%)
## ------------- ----- ------------- ------------- --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    6.7444      1    0.0094  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.54        0.34       0.85   
## ----------------------------------
\end{verbatim}

\hypertarget{length-time-in-icu-1}{%
\subsubsection{Length time in ICU}\label{length-time-in-icu-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{data\_psm\_aux }\OtherTok{\textless{}{-}}\NormalTok{ data\_psm }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{filter}\NormalTok{ (icu }\SpecialCharTok{==} \StringTok{"yes"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{datasummary}\NormalTok{((vaccine\_cov) }\SpecialCharTok{\textasciitilde{}}\NormalTok{ time\_icu}\SpecialCharTok{*}\NormalTok{(n}\SpecialCharTok{+}\NormalTok{media}\SpecialCharTok{+}\NormalTok{DP}\SpecialCharTok{+}\NormalTok{mediana}\SpecialCharTok{+}\NormalTok{q25}\SpecialCharTok{+}\NormalTok{q75}\SpecialCharTok{+}\NormalTok{IQR),}
            \AttributeTok{data =}\NormalTok{ data\_psm\_aux, }\AttributeTok{output =} \StringTok{\textquotesingle{}markdown\textquotesingle{}}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{longtable}[]{@{}lrrrrrrr@{}}
\toprule
& n & media & DP & mediana & q25 & q75 & IQR \\
\midrule
\endhead
no & 57.00 & 14.09 & 11.67 & 12.00 & 5.00 & 18.00 & 13.00 \\
yes & 21.00 & 9.38 & 9.30 & 5.00 & 3.00 & 13.00 & 10.00 \\
\bottomrule
\end{longtable}

\begin{Shaded}
\begin{Highlighting}[]
\CommentTok{\#teste t}
\FunctionTok{t.test}\NormalTok{(time\_icu }\SpecialCharTok{\textasciitilde{}}\NormalTok{ vaccine\_cov, }\AttributeTok{data =}\NormalTok{ data\_psm\_aux)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## 
##  Welch Two Sample t-test
## 
## data:  time_icu by vaccine_cov
## t = 1.8447, df = 44.556, p-value = 0.07173
## alternative hypothesis: true difference in means between group no and group yes is not equal to 0
## 95 percent confidence interval:
##  -0.4335558  9.8470897
## sample estimates:
##  mean in group no mean in group yes 
##         14.087719          9.380952
\end{verbatim}

\hypertarget{ventilatory-support-1}{%
\subsubsection{Ventilatory support}\label{ventilatory-support-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_psm, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, ventilatory\_support, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * ventilatory_support  
## Data Frame: data_psm  
## 
## 
## ------------- --------------------- ------------ ------------- -------------- --------------
##                 ventilatory_support     invasive            no   non-invasive          Total
##   vaccine_cov                                                                               
##            no                         39 (20.6%)    68 (36.0%)     82 (43.4%)   189 (100.0%)
##           yes                          9 ( 4.8%)    99 (52.4%)     81 (42.9%)   189 (100.0%)
##         Total                         48 (12.7%)   167 (44.2%)    163 (43.1%)   378 (100.0%)
## ------------- --------------------- ------------ ------------- -------------- --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    24.5106     2       0    
## ----------------------------
\end{verbatim}

\hypertarget{intubation-1}{%
\subsubsection{Intubation}\label{intubation-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_psm, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, intubation, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * intubation  
## Data Frame: data_psm  
## 
## 
## ------------- ------------ ------------- ------------ --------------
##                 intubation            no          yes          Total
##   vaccine_cov                                                       
##            no                150 (79.4%)   39 (20.6%)   189 (100.0%)
##           yes                180 (95.2%)    9 ( 4.8%)   189 (100.0%)
##         Total                330 (87.3%)   48 (12.7%)   378 (100.0%)
## ------------- ------------ ------------- ------------ --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    20.0693     1       0    
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##     0.19        0.09       0.41   
## ----------------------------------
\end{verbatim}

\hypertarget{death-1}{%
\subsubsection{Death}\label{death-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{with}\NormalTok{(data\_psm, }\FunctionTok{ctable}\NormalTok{(vaccine\_cov, death, }\AttributeTok{prop =} \StringTok{"r"}\NormalTok{, }\AttributeTok{useNA =} \StringTok{"no"}\NormalTok{, }\AttributeTok{chisq =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{OR=}\ConstantTok{TRUE}\NormalTok{))}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Cross-Tabulation, Row Proportions  
## vaccine_cov * death  
## Data Frame: data_psm  
## 
## 
## ------------- ------- ------------- ------------ --------------
##                 death          cure        death          Total
##   vaccine_cov                                                  
##            no           174 (87.0%)   26 (13.0%)   200 (100.0%)
##           yes           194 (97.0%)    6 ( 3.0%)   200 (100.0%)
##         Total           368 (92.0%)   32 ( 8.0%)   400 (100.0%)
## ------------- ------- ------------- ------------ --------------
## 
## ----------------------------
##  Chi.squared   df   p.value 
## ------------- ---- ---------
##    12.2622     1     5e-04  
## ----------------------------
## 
## ----------------------------------
##  Odds Ratio   Lo - 95%   Hi - 95% 
## ------------ ---------- ----------
##    0.207       0.083      0.515   
## ----------------------------------
\end{verbatim}

\hypertarget{multivariate-imputation-by-chained-equations-mice}{%
\section{Multivariate Imputation by Chained Equations
(MICE)}\label{multivariate-imputation-by-chained-equations-mice}}

A total of 2284 patients were analyzed and divided into two groups,
according to their COVID-19 vaccination status: unvaccinated (n = 2084;
91.2\%) and vaccinated (n = 200; 8.8\%) groups. With respect to this
dataset, to deal with possible nonresponse bias, we explore the missing
values and we conduct a multiple imputation.

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{data\_na }\OtherTok{\textless{}{-}}\NormalTok{ data\_final }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{select}\NormalTok{(}
\NormalTok{    vaccine\_cov,}
\NormalTok{    age,}
\NormalTok{    white\_color,}
\NormalTok{    cardiac,}
\NormalTok{    diabetes,}
\NormalTok{    hematologic,}
\NormalTok{    obesity,}
\NormalTok{    asthma,}
\NormalTok{    hepatic,}
\NormalTok{    neurologic,}
\NormalTok{    pneumologic,}
\NormalTok{    imuno,}
\NormalTok{    renal,}
\NormalTok{    education2,}
\NormalTok{    residence2,}
\NormalTok{    fever,}
\NormalTok{    cough,}
\NormalTok{    sore\_throat,}
\NormalTok{    dyspnea,}
\NormalTok{    resp\_disc,}
\NormalTok{    desaturation,}
\NormalTok{    diarrhea,}
\NormalTok{    vomit,}
\NormalTok{    abd\_pain,}
\NormalTok{    fatigue,}
\NormalTok{    olfac\_loss,}
\NormalTok{    loss\_taste,}
\NormalTok{    icu,}
\NormalTok{    intubation,}
\NormalTok{    death}
\NormalTok{  )}

\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{vaccine\_cov }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{vaccine\_cov)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{white\_color }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{white\_color)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{cardiac }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{cardiac)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{diabetes }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{diabetes)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{hematologic }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{hematologic)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{obesity }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{obesity)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{asthma }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{asthma)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{hepatic }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{hepatic)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{neurologic }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{neurologic)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{pneumologic }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{pneumologic)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{imuno }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{imuno)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{renal }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{renal)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{residence2 }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{residence2)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{fever }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{fever)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{cough }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{cough)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{sore\_throat }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{sore\_throat)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{dyspnea }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{dyspnea)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{resp\_disc }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{resp\_disc)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{desaturation }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{desaturation)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{diarrhea }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{diarrhea)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{vomit }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{vomit)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{abd\_pain }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{abd\_pain)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{fatigue }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{fatigue)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{olfac\_loss }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{olfac\_loss)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{loss\_taste }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{loss\_taste)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{icu }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{icu)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{intubation }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{intubation)}
\NormalTok{data\_na}\SpecialCharTok{$}\NormalTok{death }\OtherTok{\textless{}{-}} \FunctionTok{as.factor}\NormalTok{(data\_na}\SpecialCharTok{$}\NormalTok{death)}

\FunctionTok{print}\NormalTok{(}\FunctionTok{dfSummary}\NormalTok{(data\_na, }\AttributeTok{varnumbers =} \ConstantTok{FALSE}\NormalTok{), }\AttributeTok{method =} \StringTok{"render"}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

Note that all comorbities variables and the education variable have high
proportions of missing data. The percentage of valid responses is, at
least, of 79,4\% for variables related to the symptoms.

\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-83-1.pdf}

To deal with missing data, we consider a multiple imputation by fully
conditional specification. The mice package implements this method,
where each incomplete variable is imputed by a separate model. According
to the previously analysis, the most of the variables with missing data
are binary. The variables ``hematologic'', ``hepatic'', ``neurologic'',
``pneumologic'', ``renal'' and ``imuno'' present categories extremely
unbalanced, with approximately 60\% missing data each one. For this
reason and to avoid problems of bias and efficiency, these variables
will not be considered in the process of multiple imputation. The
``residence'' variable was recategorized in two levels, urban/periurban
and rural because the periurban level has only 6 observations. We
considered as a imputation method for dichotomous variable the logistic
regression (logreg), except when the percentage of missing values for
the variable is greater than 50\%. In this situation, we consider a a
bootstrapped logistic regression model (logreg.boot). For education
variable, we considered a proportional odds model (polr). Following,
because of high percentage of missing data on some variables, we present
100 imputed datasets e the trace plots to investigate the convergence of
the method.

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{cols.dont.want }\OtherTok{\textless{}{-}} \FunctionTok{c}\NormalTok{(}\StringTok{"hematologic"}\NormalTok{, }\StringTok{"hepatic"}\NormalTok{, }\StringTok{"neurologic"}\NormalTok{, }\StringTok{"pneumologic"}\NormalTok{, }\StringTok{"renal"}\NormalTok{, }\StringTok{"imuno"}\NormalTok{)}
\NormalTok{data\_na2 }\OtherTok{\textless{}{-}}\NormalTok{ data\_na[, }\SpecialCharTok{!} \FunctionTok{names}\NormalTok{(data\_na) }\SpecialCharTok{\%in\%}\NormalTok{ cols.dont.want, drop }\OtherTok{=}\NormalTok{ F]}

\NormalTok{mice.impute.logreg }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{ (y, ry, x, }\AttributeTok{wy =} \ConstantTok{NULL}\NormalTok{, ...) }
\NormalTok{\{}
  \ControlFlowTok{if}\NormalTok{ (}\FunctionTok{is.null}\NormalTok{(wy)) }
\NormalTok{    wy }\OtherTok{\textless{}{-}} \SpecialCharTok{!}\NormalTok{ry}
\NormalTok{  aug }\OtherTok{\textless{}{-}} \FunctionTok{augment}\NormalTok{(y, ry, x, wy)}
\NormalTok{  x }\OtherTok{\textless{}{-}}\NormalTok{ aug}\SpecialCharTok{$}\NormalTok{x}
\NormalTok{  y }\OtherTok{\textless{}{-}}\NormalTok{ aug}\SpecialCharTok{$}\NormalTok{y}
\NormalTok{  ry }\OtherTok{\textless{}{-}}\NormalTok{ aug}\SpecialCharTok{$}\NormalTok{ry}
\NormalTok{  wy }\OtherTok{\textless{}{-}}\NormalTok{ aug}\SpecialCharTok{$}\NormalTok{wy}
\NormalTok{  w }\OtherTok{\textless{}{-}}\NormalTok{ aug}\SpecialCharTok{$}\NormalTok{w}
\NormalTok{  x }\OtherTok{\textless{}{-}} \FunctionTok{cbind}\NormalTok{(}\DecValTok{1}\NormalTok{, }\FunctionTok{as.matrix}\NormalTok{(x))}
\NormalTok{  expr }\OtherTok{\textless{}{-}} \FunctionTok{expression}\NormalTok{(}\FunctionTok{glm.fit}\NormalTok{(}\AttributeTok{x =}\NormalTok{ x[ry, , }\AttributeTok{drop =} \ConstantTok{FALSE}\NormalTok{], }\AttributeTok{y =}\NormalTok{ y[ry], }
                             \AttributeTok{family =} \FunctionTok{binomial}\NormalTok{(}\AttributeTok{link =}\NormalTok{ logit), }\AttributeTok{weights =}\NormalTok{ w[ry], }\AttributeTok{maxit =} \DecValTok{150}\NormalTok{))}
\NormalTok{  fit }\OtherTok{\textless{}{-}} \FunctionTok{eval}\NormalTok{(expr)}
\NormalTok{  fit.sum }\OtherTok{\textless{}{-}} \FunctionTok{summary.glm}\NormalTok{(fit)}
\NormalTok{  beta }\OtherTok{\textless{}{-}} \FunctionTok{coef}\NormalTok{(fit)}
\NormalTok{  rv }\OtherTok{\textless{}{-}} \FunctionTok{t}\NormalTok{(}\FunctionTok{chol}\NormalTok{(}\FunctionTok{sym}\NormalTok{(fit.sum}\SpecialCharTok{$}\NormalTok{cov.unscaled)))}
\NormalTok{  beta.star }\OtherTok{\textless{}{-}}\NormalTok{ beta }\SpecialCharTok{+}\NormalTok{ rv }\SpecialCharTok{\%*\%} \FunctionTok{rnorm}\NormalTok{(}\FunctionTok{ncol}\NormalTok{(rv))}
\NormalTok{  p }\OtherTok{\textless{}{-}} \DecValTok{1}\SpecialCharTok{/}\NormalTok{(}\DecValTok{1} \SpecialCharTok{+} \FunctionTok{exp}\NormalTok{(}\SpecialCharTok{{-}}\NormalTok{(x[wy, , }\AttributeTok{drop =} \ConstantTok{FALSE}\NormalTok{] }\SpecialCharTok{\%*\%}\NormalTok{ beta.star)))}
\NormalTok{  vec }\OtherTok{\textless{}{-}}\NormalTok{ (}\FunctionTok{runif}\NormalTok{(}\FunctionTok{nrow}\NormalTok{(p)) }\SpecialCharTok{\textless{}=}\NormalTok{ p)}
\NormalTok{  vec[vec] }\OtherTok{\textless{}{-}} \DecValTok{1}
  \ControlFlowTok{if}\NormalTok{ (}\FunctionTok{is.factor}\NormalTok{(y)) \{}
\NormalTok{    vec }\OtherTok{\textless{}{-}} \FunctionTok{factor}\NormalTok{(vec, }\FunctionTok{c}\NormalTok{(}\DecValTok{0}\NormalTok{, }\DecValTok{1}\NormalTok{), }\FunctionTok{levels}\NormalTok{(y))}
\NormalTok{  \}}
\NormalTok{  vec}
\NormalTok{\}}

\NormalTok{imputed\_Data }\OtherTok{\textless{}{-}} \FunctionTok{mice}\NormalTok{(data\_na2, }\AttributeTok{m=}\DecValTok{100}\NormalTok{, }\AttributeTok{maxit =} \DecValTok{60}\NormalTok{, }\AttributeTok{method =} \FunctionTok{c}\NormalTok{(}\StringTok{""}\NormalTok{, }\StringTok{""}\NormalTok{, }\StringTok{"logreg"}\NormalTok{, }\FunctionTok{rep}\NormalTok{(}\StringTok{"logreg.boot"}\NormalTok{, }\DecValTok{4}\NormalTok{), }\StringTok{"polyreg"}\NormalTok{, }
                          \FunctionTok{rep}\NormalTok{(}\StringTok{"logreg"}\NormalTok{, }\DecValTok{16}\NormalTok{)), }\AttributeTok{printFlag =} \ConstantTok{FALSE}\NormalTok{, }\AttributeTok{seed =} \DecValTok{300}\NormalTok{)}

\FunctionTok{summary}\NormalTok{(imputed\_Data)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Class: mids
## Number of multiple imputations:  100 
## Imputation methods:
##   vaccine_cov           age   white_color       cardiac      diabetes 
##            ""            ""      "logreg" "logreg.boot" "logreg.boot" 
##       obesity        asthma    education2    residence2         fever 
## "logreg.boot" "logreg.boot"     "polyreg"      "logreg"      "logreg" 
##         cough   sore_throat       dyspnea     resp_disc  desaturation 
##      "logreg"      "logreg"      "logreg"      "logreg"      "logreg" 
##      diarrhea         vomit      abd_pain       fatigue    olfac_loss 
##      "logreg"      "logreg"      "logreg"      "logreg"      "logreg" 
##    loss_taste           icu    intubation         death 
##      "logreg"      "logreg"      "logreg"            "" 
## PredictorMatrix:
##             vaccine_cov age white_color cardiac diabetes obesity asthma
## vaccine_cov           0   1           1       1        1       1      1
## age                   1   0           1       1        1       1      1
## white_color           1   1           0       1        1       1      1
## cardiac               1   1           1       0        1       1      1
## diabetes              1   1           1       1        0       1      1
## obesity               1   1           1       1        1       0      1
##             education2 residence2 fever cough sore_throat dyspnea resp_disc
## vaccine_cov          1          1     1     1           1       1         1
## age                  1          1     1     1           1       1         1
## white_color          1          1     1     1           1       1         1
## cardiac              1          1     1     1           1       1         1
## diabetes             1          1     1     1           1       1         1
## obesity              1          1     1     1           1       1         1
##             desaturation diarrhea vomit abd_pain fatigue olfac_loss loss_taste
## vaccine_cov            1        1     1        1       1          1          1
## age                    1        1     1        1       1          1          1
## white_color            1        1     1        1       1          1          1
## cardiac                1        1     1        1       1          1          1
## diabetes               1        1     1        1       1          1          1
## obesity                1        1     1        1       1          1          1
##             icu intubation death
## vaccine_cov   1          1     1
## age           1          1     1
## white_color   1          1     1
## cardiac       1          1     1
## diabetes      1          1     1
## obesity       1          1     1
\end{verbatim}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{plot}\NormalTok{(imputed\_Data)}
\end{Highlighting}
\end{Shaded}

\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-1.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-2.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-3.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-4.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-5.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-6.pdf}
\includegraphics{sup_mat_COVID-19-vaccines-confer-protection-in-hospitalized-pregnant-and-postpartum-women-with-severe-COVID-19_files/figure-latex/unnamed-chunk-84-7.pdf}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{dat\_imp }\OtherTok{\textless{}{-}} \FunctionTok{mids2milist}\NormalTok{(imputed\_Data)}
\end{Highlighting}
\end{Shaded}

Each one of these 100 imputed datasets were analysed using the function
\texttt{with()}, and including an expression for the statistical
analysis approach. Procedures to pool Chi-square values are available in
the miceadds package. To combine the 100 odds ratios, we use the
miceafter package.

\hypertarget{baseline-characteristics-of-the-subjects-according-to-vaccination-status}{%
\subsection{Baseline characteristics of the subjects according to
vaccination
status}\label{baseline-characteristics-of-the-subjects-according-to-vaccination-status}}

\hypertarget{white-color-1}{%
\subsubsection{White color}\label{white-color-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_w }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, white\_color))}
\NormalTok{Stat\_w }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_w[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_w}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_w, }\DecValTok{1}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(1, 18484.24)=3.054     p=0.08054
\end{verbatim}

\hypertarget{cardiac-1}{%
\subsubsection{Cardiac}\label{cardiac-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_c }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, cardiac))}
\NormalTok{Stat\_c }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_c[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_c}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_c, }\DecValTok{1}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(1, 270.94)=4.983     p=0.02642
\end{verbatim}

\hypertarget{diabetes-1}{%
\subsubsection{Diabetes}\label{diabetes-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_d }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, diabetes))}
\NormalTok{Stat\_d }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_d[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_d}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_d, }\DecValTok{1}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(1, 394.63)=0.892     p=0.34539
\end{verbatim}

\hypertarget{obesity-1}{%
\subsubsection{Obesity}\label{obesity-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_o }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, obesity))}
\NormalTok{Stat\_o }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_o[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_o}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_o, }\DecValTok{1}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(1, 439.29)=1.475     p=0.22518
\end{verbatim}

\hypertarget{asthma-1}{%
\subsubsection{Asthma}\label{asthma-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_a }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, asthma))}
\NormalTok{Stat\_a }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_a[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_a}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_a, }\DecValTok{1}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(1, 273.82)=1.085     p=0.29841
\end{verbatim}

\hypertarget{education}{%
\subsubsection{Education}\label{education}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_e }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, education2))}
\NormalTok{Stat\_e }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_e[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_e}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_e, }\DecValTok{2}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(2, 755.7)=2.461     p=0.08601
\end{verbatim}

\hypertarget{residence-area-2-grouping-the-categories-urban-and-periurban-1}{%
\subsubsection{Residence area 2 (grouping the categories urban and
periurban)}\label{residence-area-2-grouping-the-categories-urban-and-periurban-1}}

\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{fit\_res }\OtherTok{\textless{}{-}} \FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{exp =} \FunctionTok{chisq.test}\NormalTok{(vaccine\_cov, residence2))}
\NormalTok{Stat\_res }\OtherTok{\textless{}{-}} \FunctionTok{numeric}\NormalTok{()}
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m) Stat\_res[i] }\OtherTok{\textless{}{-}}\NormalTok{ fit\_res}\SpecialCharTok{$}\NormalTok{statistics[[i]]}\SpecialCharTok{$}\NormalTok{statistic}
\FunctionTok{micombine.chisquare}\NormalTok{(Stat\_res, }\DecValTok{2}\NormalTok{, }\AttributeTok{display =} \ConstantTok{TRUE}\NormalTok{, }\AttributeTok{version=}\DecValTok{1}\NormalTok{)}
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
## Combination of Chi Square Statistics for Multiply Imputed Data
## Using 100 Imputed Data Sets
## F(2, 44650.47)=0.07     p=0.93195
\end{verbatim}

\hypertarget{characteristics-of-covid-19-symptoms-by-vaccination-status}{%
\subsection{Characteristics of COVID-19 symptoms by vaccination
status}\label{characteristics-of-covid-19-symptoms-by-vaccination-status}}

\hypertarget{fever-1}{%
\subsubsection{Fever}\label{fever-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ fever))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.6434665 0.4735422  0.8743657
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{cough-1}{%
\subsubsection{Cough}\label{cough-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ cough))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.8208345 0.5776051   1.166488
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{sore-throat-1}{%
\subsubsection{Sore throat}\label{sore-throat-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ sore\_throat))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.7729552 0.5312457   1.124639
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{dyspnea-1}{%
\subsubsection{Dyspnea}\label{dyspnea-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ dyspnea))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,]  0.562676  0.412656  0.7672355
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{respiratory-discomfort-1}{%
\subsubsection{Respiratory discomfort}\label{respiratory-discomfort-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ resp\_disc))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.6371953 0.4682167   0.867158
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{desaturation-1}{%
\subsubsection{Desaturation}\label{desaturation-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ desaturation))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.5412815 0.3945068  0.7426633
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{diarrhea-1}{%
\subsubsection{Diarrhea}\label{diarrhea-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ diarrhea))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.9370858 0.5794052   1.515571
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{vomit-1}{%
\subsubsection{Vomit}\label{vomit-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ vomit))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.8352794 0.5083313   1.372514
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{abdominal-pain-1}{%
\subsubsection{Abdominal pain}\label{abdominal-pain-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ abd\_pain))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,]  1.169572 0.7296263   1.874794
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{fatigue-1}{%
\subsubsection{Fatigue}\label{fatigue-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ fatigue))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.9631591 0.6867503   1.350819
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{loss-of-smell}{%
\subsubsection{Loss of smell}\label{loss-of-smell}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ olfac\_loss))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,]  1.137034 0.7773557   1.663132
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{loss-of-taste-1}{%
\subsubsection{Loss of taste}\label{loss-of-taste-1}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ loss\_taste))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,]  1.181084 0.8003242   1.742992
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{any-respiratory-symptom-1}{%
\subsubsection{Any respiratory
symptom}\label{any-respiratory-symptom-1}}

\begin{Shaded}
\begin{Highlighting}[]
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m)\{}
\NormalTok{df }\OtherTok{\textless{}{-}}\NormalTok{ dat\_imp[[i]] }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{select}\NormalTok{(dyspnea,fatigue,desaturation,resp\_disc)}

\NormalTok{soma }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)\{}
  \ControlFlowTok{if}\NormalTok{ (}\FunctionTok{sum}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(x))}\SpecialCharTok{==}\DecValTok{4}\NormalTok{)}
    \FunctionTok{return}\NormalTok{(}\ConstantTok{NA\_character\_}\NormalTok{)}
  \ControlFlowTok{else}
    \FunctionTok{return}\NormalTok{(}\FunctionTok{sum}\NormalTok{(}\SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(x) }\SpecialCharTok{\&}\NormalTok{ x}\SpecialCharTok{==}\StringTok{"yes"}\NormalTok{)) }
\NormalTok{\}}
\NormalTok{dat\_imp[[i]]}\SpecialCharTok{$}\NormalTok{qt\_sintomas\_resp\_aux }\OtherTok{\textless{}{-}} \FunctionTok{apply}\NormalTok{(df,}\DecValTok{1}\NormalTok{,soma)}

\NormalTok{dat\_imp[[i]] }\OtherTok{\textless{}{-}}\NormalTok{  dat\_imp[[i]] }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{resp\_symp =} \FunctionTok{case\_when}\NormalTok{(qt\_sintomas\_resp\_aux }\SpecialCharTok{\textgreater{}=}\DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                               qt\_sintomas\_resp\_aux }\SpecialCharTok{==}\DecValTok{0} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                               \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}
\NormalTok{\}}

\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ resp\_symp))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.5210252 0.3724448  0.7288791
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{any-symptom-1}{%
\subsubsection{Any symptom}\label{any-symptom-1}}

\begin{Shaded}
\begin{Highlighting}[]
\ControlFlowTok{for}\NormalTok{ (i }\ControlFlowTok{in} \DecValTok{1}\SpecialCharTok{:}\NormalTok{imputed\_Data}\SpecialCharTok{$}\NormalTok{m)\{}
\NormalTok{df }\OtherTok{\textless{}{-}}\NormalTok{ dat\_imp[[i]] }\SpecialCharTok{\%\textgreater{}\%} 
  \FunctionTok{select}\NormalTok{(dyspnea,fatigue,desaturation,resp\_disc,}
\NormalTok{         fever,cough,sore\_throat,diarrhea,vomit,abd\_pain,olfac\_loss,loss\_taste)}
\NormalTok{soma }\OtherTok{\textless{}{-}} \ControlFlowTok{function}\NormalTok{(x)\{}
  \ControlFlowTok{if}\NormalTok{ (}\FunctionTok{sum}\NormalTok{(}\FunctionTok{is.na}\NormalTok{(x))}\SpecialCharTok{==}\DecValTok{12}\NormalTok{)}
    \FunctionTok{return}\NormalTok{(}\ConstantTok{NA\_character\_}\NormalTok{)}
  \ControlFlowTok{else}
    \FunctionTok{return}\NormalTok{(}\FunctionTok{sum}\NormalTok{(}\SpecialCharTok{!}\FunctionTok{is.na}\NormalTok{(x) }\SpecialCharTok{\&}\NormalTok{ x}\SpecialCharTok{==}\StringTok{"yes"}\NormalTok{)) }
\NormalTok{\}}
\NormalTok{dat\_imp[[i]]}\SpecialCharTok{$}\NormalTok{qt\_sintomas\_aux }\OtherTok{\textless{}{-}} \FunctionTok{apply}\NormalTok{(df,}\DecValTok{1}\NormalTok{,soma)}

\NormalTok{dat\_imp[[i]] }\OtherTok{\textless{}{-}}\NormalTok{  dat\_imp[[i]] }\SpecialCharTok{\%\textgreater{}\%}
  \FunctionTok{mutate}\NormalTok{(}\AttributeTok{symptom =} \FunctionTok{case\_when}\NormalTok{(qt\_sintomas\_aux }\SpecialCharTok{\textgreater{}=} \DecValTok{1} \SpecialCharTok{\textasciitilde{}} \StringTok{"yes"}\NormalTok{,}
\NormalTok{                             qt\_sintomas\_aux }\SpecialCharTok{==} \DecValTok{0} \SpecialCharTok{\textasciitilde{}} \StringTok{"no"}\NormalTok{,}
                             \ConstantTok{TRUE} \SpecialCharTok{\textasciitilde{}} \ConstantTok{NA\_character\_}\NormalTok{))}
\NormalTok{\}}

\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ symptom))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.4706185 0.2644071  0.8376544
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{characteristics-of-covid-19-symptoms-by-vaccination-status-1}{%
\subsection{Characteristics of COVID-19 symptoms by vaccination
status}\label{characteristics-of-covid-19-symptoms-by-vaccination-status-1}}

\hypertarget{icu-2}{%
\subsubsection{ICU}\label{icu-2}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ icu))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.5361446 0.3789471  0.7585517
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{intubation-2}{%
\subsubsection{Intubation}\label{intubation-2}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ intubation))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR 95 CI low 95 CI high
## [1,] 0.2267073 0.1160312  0.4429518
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\hypertarget{death-2}{%
\subsubsection{Death}\label{death-2}}

\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{pool\_odds\_ratio}\NormalTok{(}\FunctionTok{with}\NormalTok{(dat\_imp, }\AttributeTok{expr=}\FunctionTok{odds\_ratio}\NormalTok{(vaccine\_cov }\SpecialCharTok{\textasciitilde{}}\NormalTok{ death))) }
\end{Highlighting}
\end{Shaded}

\begin{verbatim}
##      pooled OR  95 CI low 95 CI high
## [1,] 0.1883021 0.08279405  0.4282638
## attr(,"class")
## [1] "mipool"
\end{verbatim}

\end{document}