<?xml version="1.0" encoding="UTF-8"?>
<codeBook version="1.2.2" ID="AHRI.SAPRIN.COVID-19.Vaccine.Hesitancy.Dataset" xml-lang="en" xmlns="http://www.icpsr.umich.edu/DDI" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.icpsr.umich.edu/DDI http://www.icpsr.umich.edu/DDI/Version1-2-2.xsd">
<docDscr>
  <citation>
    <titlStmt>
      <IDNo>DDI.AHRI.SAPRIN.COVID-19.Vaccine.Hesitancy.Dataset</IDNo>
    </titlStmt>
    <prodStmt>
      <producer abbr="AHRI" affiliation="" role="">Africa Health Research Institute</producer>
      <prodDate date="">
        <_value></_value>
      </prodDate>
      <software version="v5">NADA</software>
    </prodStmt>
    <verStmt>
      <version></version>
    </verStmt>
  </citation>
</docDscr>
<stdyDscr>
  <citation>
    <titlStmt>
      <titl>AHRI.COVID-19 vaccine uptake, confidence and hesitancy in rural KwaZulu-Natal, South Africa between April 2021 and April 2022:a subset of the individual population-wide surveillance system annual interview</titl>
      <subTitl/>
      <altTitl/>
      <parTitl/>
      <IDNo>AHRI.SAPRIN.COVID-19.Vaccine.Hesitancy.Dataset</IDNo>
    </titlStmt>
    <rspStmt>
      <AuthEnty affiliation="SAPRIN/AHRI">Herbst, Kobus</AuthEnty>
      <AuthEnty affiliation="AHRI/MGH">Siedner, Mark</AuthEnty>
      <AuthEnty affiliation="AHRI/UCL">Harling, Guy</AuthEnty>
      <othId role="" affiliation="SAPRIN" email="">
        <p>Tinofa Mutevedzi</p>
      </othId>
      <othId role="PIP Coordinator" affiliation="AHRI" email="">
        <p>Thobeka Mngomezulu</p>
      </othId>
      <othId role="Head of Public Engagement" affiliation="AHRI" email="">
        <p>Nomathamsanqa Majozi</p>
      </othId>
      <othId role="SAPRIN Research Data Manager" affiliation="AHRI" email="">
        <p>Siyabonga Nxumalo</p>
      </othId>
      <othId role="Research Data Manager" affiliation="AHRI" email="">
        <p>Njabulo Dayi</p>
      </othId>
      <othId role="Head of Research Data Management" affiliation="AHRI" email="">
        <p>Dickman Gareta</p>
      </othId>
      <othId role="Senior Research Data Manager" affiliation="AHRI" email="">
        <p>Jaco Dreyer</p>
      </othId>
      <othId role="Senior Software Developer" affiliation="AHRI" email="">
        <p>Eugene Ehlers</p>
      </othId>
    </rspStmt>
    <prodStmt>
      <producer abbr="" affiliation="" role="">Africa Health Research Institute</producer>
      <copyright/>
      <software version="5.0" date="2023-06-01">NADA</software>
      <fundAg abbr="WT" role="Core funding">Wellcome Trust</fundAg>
      <fundAg abbr="SAPRIN" role="Surveillance funding">SAPRIN</fundAg>
      <grantNo>097410/Z/11/Z DSI-SAMRC</grantNo>
    </prodStmt>
    <distStmt>
      <depDate date=""/>
      <distDate date=""/>
    </distStmt>
    <serStmt>
      <serName/>
      <serInfo><![CDATA[]]></serInfo>
    </serStmt>
    <verStmt>
      <version date="">v1.0.0</version>
      <verResp/>
      <notes><![CDATA[]]></notes>
    </verStmt>
    <biblCit format=""><![CDATA[]]></biblCit>
    <notes><![CDATA[]]></notes>
  </citation>
  <stdyInfo>
    <studyBudget><![CDATA[]]></studyBudget>
    <subject>
      <keyword vocab="Africa Health Research Institute" vocabURI="www.ahri.org">Covid-19; Surveillance; South Africa; Health and Demographic Surveillance System; Behaviour; Attitudes</keyword>
      <topcClas vocab="Africa Health Research Institute" vocabURI="www.ahri.org">COVID-19; Vaccination; Public Health Surveillance; Epidemiology; South Africa</topcClas>
    </subject>
    <abstract><![CDATA[This dataset is a subset of the wider population-based Covid-19 surveillance run at the Africa Health Research Institute from 2020 onwards. The dataset covers one complete year of data collection, such that all residents had the opportunity to participate. The dataset specifically provides all observations and variables needed to replicate the analyses described in the journal article “COVID-19 vaccine uptake, confidence and hesitancy in rural KwaZulu-Natal, South Africa between April 2021 and April 2022: a continuous cross-sectional surveillance study” published in PLOS Global Public Health in 2023. The dataset includes variable on Covid vaccine uptake and willingness to take a hypothetical vaccine offer on the day of interview, as well as variables measuring four groups of potential predictors of these vaccine outcomes: demographics (age, sex), pre-existing conditions (information sources, government trust, education, urbanicity), contextual factors (impact of Covid on household economics and community wellbeing, Covid-related stigma, household age composition) and cues to action (recent case counts in KwaZulu-Natal, concern about impact if infected with Covid, knowledge of others with past Covid infection, household vaccination status, depression/anxiety) and interview date.]]></abstract>
    <sumDscr>
      <collDate date="2021-04-20" event="start" cycle=""/>
      <collDate date="2022-04-20" event="end" cycle=""/>
      <nation abbr="ZA">South Africa</nation>
      <geogCover>AHRI demographic surveillance area, uMkhanyakude district in northern KwaZulu-Natal</geogCover>
      <geogUnit/>
      <anlyUnit><![CDATA[Individual]]></anlyUnit>
      <universe><![CDATA[All individuals aged 18 and over resident within the areas of the Africa Health Research Institute Population Intervention Programme]]></universe>
      <dataKind>Survey data</dataKind>
    </sumDscr>
    <qualityStatement>
      <standardsCompliance>
        <standard>
          <standardName/>
          <producer/>
        </standard>
        <complianceDescription/>
      </standardsCompliance>
      <otherQualityStatement/>
    </qualityStatement>
    <notes><![CDATA[]]></notes>
    <exPostEvaluation completionDate="" type="">
      <evaluationProcess/>
      <outcomes/>
    </exPostEvaluation>
  </stdyInfo>
  <method>
    <dataColl>
      <timeMeth/>
      <frequenc/>
      <sampProc><![CDATA[All adult residents in the geographic area were eligible via an individual face-to-face interview. Multiple attempts were made to reach each individual if necessary. The final sample reflects all those who consented to and completed an interview.]]></sampProc>
      <sampleFrame>
        <sampleFrameName/>
        <custodian/>
        <universe/>
        <frameUnit isPrimary="">
          <unitType numberOfUnits=""/>
        </frameUnit>
        <updateProcedure/>
      </sampleFrame>
      <deviat/>
      <resInstru><![CDATA[]]></resInstru>
      <instrumentDevelopment type=""/>
      <collSitu><![CDATA[]]></collSitu>
      <actMin><![CDATA[]]></actMin>
      <ConOps><![CDATA[]]></ConOps>
      <weight><![CDATA[]]></weight>
      <cleanOps><![CDATA[Pentaho Data Integration was used to extract the datasets. NESSTAR Publisher was used to document the datasets.]]></cleanOps>
    </dataColl>
    <notes><![CDATA[]]></notes>
    <anlyInfo>
      <respRate><![CDATA[]]></respRate>
      <EstSmpErr><![CDATA[]]></EstSmpErr>
      <dataAppr><![CDATA[]]></dataAppr>
    </anlyInfo>
    <stdyClas><![CDATA[]]></stdyClas>
    <dataProcessing type=""/>
    <codingInstructions relatedProcesses="" type="">
      <txt/>
      <command formalLanguage=""/>
    </codingInstructions>
  </method>
  <dataAccs>
    <setAvail>
      <accsPlac URI=""/>
      <origArch/>
      <avlStatus/>
      <collSize/>
      <complete/>
      <fileQnty/>
      <notes><![CDATA[]]></notes>
    </setAvail>
    <useStmt>
      <restrctn/>
      <citReq><![CDATA[]]></citReq>
      <deposReq><![CDATA[]]></deposReq>
      <conditions><![CDATA[Access to the data requires accurate completion of the online data access application form accessible on the AHRI Data repository(&lt;https://data.ahri.org/&gt;). Data users are required to abide by the data use conditions stipulated on the application for access to the data. Failure to do so may result in their data access privileges being revoked by the Data Custodian. In order to recognise the effort and intellectual contributions of AHRI investigators in producing and curating the data, users of AHRI data must acknowledge the source of the data and abide by the terms and conditions under which the data is accessed and must cite the dataset in publication using the citation provided as part of this documentation. All analytical datasets published on the AHRI Data Repository are assigned digital object identifier (DOIs) and the DOIs can be found on the Data Repository under Study Description tab - Access policy. AHRI data users are required to always cite the dataset using the relevant DOI.]]></conditions>
      <disclaimer><![CDATA[]]></disclaimer>
    </useStmt>
    <notes><![CDATA[]]></notes>
  </dataAccs>
  <notes><![CDATA[]]></notes>
</stdyDscr>
<fileDscr ID="F8">
  <fileTxt>
    <fileName>covid_vax_plos_minimum_dataset</fileName>
    <fileCont></fileCont>
    <dimensns>
      <caseQnty>15709</caseQnty>
      <varQnty>27</varQnty>
    </dimensns>
    <dataChck></dataChck>
    <dataMsng></dataMsng>
    <verStmt>
      <version></version>
    </verStmt>
  </fileTxt>
  <notes></notes>
</fileDscr>
<dataDscr>
<var ID="V466" name="IIntId" files="F8" intrvl="contin">
  <varFormat type="numeric"/>
  <location width="12"/>
  <labl>Unique or Internal ID of Individual</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <sumStat type="min">17</sumStat>
  <sumStat type="max">258195</sumStat>
  <sumStat type="mean">77973.106</sumStat>
  <sumStat type="stdev">56476.976</sumStat>
</var>
<var ID="V467" name="HHIntId" files="F8" intrvl="contin">
  <varFormat type="numeric"/>
  <location width="12"/>
  <labl>Household ID</labl>
  <sumStat type="vald">15369</sumStat>
  <sumStat type="invd">340</sumStat>
  <sumStat type="min">11</sumStat>
  <sumStat type="max">41783</sumStat>
  <sumStat type="mean">12566.992</sumStat>
  <sumStat type="stdev">10594.969</sumStat>
</var>
<var ID="V468" name="InterviewDate" files="F8" intrvl="discrete">
  <varFormat type="character" formatname="Nesstar.date"/>
  <location width="11"/>
  <labl>Interview Date</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="min">2021-04-20</sumStat>
  <sumStat type="max">2022-04-20</sumStat>
</var>
<var ID="V469" name="Sex" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="12"/>
  <labl>Sex</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <catValu>1</catValu>
    <labl>Male</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Female</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>2147483642</catValu>
    <labl>Unknown</labl>
  </catgry>
</var>
<var ID="V470" name="agegroup" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Age of respondent (4 levels)</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <catValu>1</catValu>
    <labl>18-34</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>35-49</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>50-59</labl>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>60+</labl>
  </catgry>
</var>
<var ID="V471" name="InterviewMonth" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Month of interview</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <catValu>4</catValu>
    <labl>Apr 2021</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>5</catValu>
    <labl>May 2021</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>6</catValu>
    <labl>Jun 2021</labl>
  </catgry>
  <catgry>
    <catValu>7</catValu>
    <labl>Jul 2021</labl>
  </catgry>
  <catgry>
    <catValu>8</catValu>
    <labl>Aug 2021</labl>
  </catgry>
  <catgry>
    <catValu>9</catValu>
    <labl>Sep 2021</labl>
  </catgry>
  <catgry>
    <catValu>10</catValu>
    <labl>Oct 2021</labl>
  </catgry>
  <catgry>
    <catValu>11</catValu>
    <labl>Nov 2021</labl>
  </catgry>
  <catgry>
    <catValu>12</catValu>
    <labl>Dec 2021</labl>
  </catgry>
  <catgry>
    <catValu>13</catValu>
    <labl>Jan 2022</labl>
  </catgry>
  <catgry>
    <catValu>14</catValu>
    <labl>Feb 2022</labl>
  </catgry>
  <catgry>
    <catValu>15</catValu>
    <labl>Mar 2022</labl>
  </catgry>
  <catgry>
    <catValu>16</catValu>
    <labl>Apr 2022</labl>
  </catgry>
</var>
<var ID="V472" name="covax_willing" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="20"/>
  <labl>Covid vaccine uptake or willingness to take (5 levels)</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <labl>Already vaccinated</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Definitely would</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Probably would</labl>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Probably would not</labl>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>Definitely would not</labl>
  </catgry>
</var>
<var ID="V473" name="info_tradition" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Information from traditional sources</labl>
  <sumStat type="vald">11075</sumStat>
  <sumStat type="invd">4634</sumStat>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V474" name="info_personal" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Information from personal network sources</labl>
  <sumStat type="vald">11075</sumStat>
  <sumStat type="invd">4634</sumStat>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V475" name="info_healthcare" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Information from healthcare sources</labl>
  <sumStat type="vald">11075</sumStat>
  <sumStat type="invd">4634</sumStat>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V476" name="info_community" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Information from community sources</labl>
  <sumStat type="vald">11075</sumStat>
  <sumStat type="invd">4634</sumStat>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V477" name="gov_mistrust_std" files="F8" intrvl="contin">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Mistrust in government - per standard deviation</labl>
  <sumStat type="vald">15664</sumStat>
  <sumStat type="invd">45</sumStat>
  <sumStat type="min">-2.326</sumStat>
  <sumStat type="max">2.476</sumStat>
  <sumStat type="mean">-0.00452</sumStat>
  <sumStat type="stdev">1.001</sumStat>
</var>
<var ID="V478" name="educ_attain_cat" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="19"/>
  <labl>Highest educational attainment</labl>
  <sumStat type="vald">14455</sumStat>
  <sumStat type="invd">1254</sumStat>
  <catgry>
    <catValu>1</catValu>
    <labl>None</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Primary</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Some secondary</labl>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>Completed secondary</labl>
  </catgry>
  <catgry>
    <catValu>5</catValu>
    <labl>Any tertiary</labl>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V479" name="HH_older" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Has household member aged 60 or older</labl>
  <sumStat type="vald">15369</sumStat>
  <sumStat type="invd">340</sumStat>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V480" name="IsUrbanOrRural" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="12"/>
  <labl>Urbanicity of household</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <catValu>2</catValu>
    <labl>Peri-Urban</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Rural</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>Urban</labl>
  </catgry>
  <catgry>
    <catValu>2147483625</catValu>
    <labl>Unknown</labl>
  </catgry>
</var>
<var ID="V481" name="subUnits_num" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="22"/>
  <labl>Isigodi of residence</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <catValu>1</catValu>
    <labl>Ebaswazini</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Esiyembeni</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Gunjaneni</labl>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>KwaMsane (Isigodi)</labl>
  </catgry>
  <catgry>
    <catValu>5</catValu>
    <labl>KwaMsane (Township)</labl>
  </catgry>
  <catgry>
    <catValu>6</catValu>
    <labl>Kwahoho</labl>
  </catgry>
  <catgry>
    <catValu>7</catValu>
    <labl>Macambini</labl>
  </catgry>
  <catgry>
    <catValu>8</catValu>
    <labl>Machibini</labl>
  </catgry>
  <catgry>
    <catValu>9</catValu>
    <labl>Madwaleni</labl>
  </catgry>
  <catgry>
    <catValu>10</catValu>
    <labl>Mahunjini</labl>
  </catgry>
  <catgry>
    <catValu>11</catValu>
    <labl>Makhambane</labl>
  </catgry>
  <catgry>
    <catValu>12</catValu>
    <labl>Mapheleni</labl>
  </catgry>
  <catgry>
    <catValu>13</catValu>
    <labl>Mfekayi</labl>
  </catgry>
  <catgry>
    <catValu>14</catValu>
    <labl>Mshaya</labl>
  </catgry>
  <catgry>
    <catValu>15</catValu>
    <labl>Mvutshini</labl>
  </catgry>
  <catgry>
    <catValu>16</catValu>
    <labl>Myeki</labl>
  </catgry>
  <catgry>
    <catValu>17</catValu>
    <labl>Ndlovu Village</labl>
  </catgry>
  <catgry>
    <catValu>18</catValu>
    <labl>Nkolokotho</labl>
  </catgry>
  <catgry>
    <catValu>19</catValu>
    <labl>Nkombose</labl>
  </catgry>
  <catgry>
    <catValu>20</catValu>
    <labl>Nkundusi</labl>
  </catgry>
  <catgry>
    <catValu>21</catValu>
    <labl>Nomathiya</labl>
  </catgry>
  <catgry>
    <catValu>22</catValu>
    <labl>Nompondo</labl>
  </catgry>
  <catgry>
    <catValu>23</catValu>
    <labl>Nqopheni</labl>
  </catgry>
  <catgry>
    <catValu>24</catValu>
    <labl>Nsolweni</labl>
  </catgry>
  <catgry>
    <catValu>25</catValu>
    <labl>Ogengele</labl>
  </catgry>
  <catgry>
    <catValu>26</catValu>
    <labl>Ophaphasi (Mpukunyoni)</labl>
  </catgry>
  <catgry>
    <catValu>27</catValu>
    <labl>Ophondweni</labl>
  </catgry>
  <catgry>
    <catValu>28</catValu>
    <labl>Qakwini</labl>
  </catgry>
  <catgry>
    <catValu>29</catValu>
    <labl>Shikishela</labl>
  </catgry>
</var>
<var ID="V482" name="phq4_cats" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>PHQ-4 categories</labl>
  <sumStat type="vald">15610</sumStat>
  <sumStat type="invd">99</sumStat>
  <catgry>
    <labl>Normal</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Mild</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Moderate</labl>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Severe</labl>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V483" name="pandemic_change" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="15"/>
  <labl>Change in community wellbeing since March 2020</labl>
  <sumStat type="vald">11073</sumStat>
  <sumStat type="invd">4636</sumStat>
  <catgry>
    <catValu>1</catValu>
    <labl>Got better</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Stayed the same</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Got worse</labl>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V484" name="econ_stability" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="19"/>
  <labl>Change in economic stability during Covid</labl>
  <sumStat type="vald">11073</sumStat>
  <sumStat type="invd">4636</sumStat>
  <catgry>
    <catValu>1</catValu>
    <labl>Much better off</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>A little better off</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>About the same</labl>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>A little worse off</labl>
  </catgry>
  <catgry>
    <catValu>5</catValu>
    <labl>Much worse off</labl>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V485" name="kzn_7day_incid_1000" files="F8" intrvl="contin">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Past 7-day KZN case count per 1000 population</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <sumStat type="min">0.0208</sumStat>
  <sumStat type="max">1.52</sumStat>
  <sumStat type="mean">0.227</sumStat>
  <sumStat type="stdev">0.282</sumStat>
</var>
<var ID="V486" name="exposure_concern" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="12"/>
  <labl>Future COVID infection concern level</labl>
  <sumStat type="vald">15677</sumStat>
  <sumStat type="invd">32</sumStat>
  <catgry>
    <catValu>1</catValu>
    <labl>Not at all</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>2</catValu>
    <labl>Slightly concerned</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>3</catValu>
    <labl>Moderately concerned</labl>
  </catgry>
  <catgry>
    <catValu>4</catValu>
    <labl>Very concerned</labl>
  </catgry>
  <catgry>
    <catValu>5</catValu>
    <labl>Not applicable</labl>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V487" name="covid_knowperson" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Knows someone who has had COVID</labl>
  <sumStat type="vald">15658</sumStat>
  <sumStat type="invd">51</sumStat>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
  <catgry>
    <catValu>Sysmiss</catValu>
  </catgry>
</var>
<var ID="V488" name="stigma_stereotype_std" files="F8" intrvl="contin">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Covid stereotype stigma score, z-scores</labl>
  <sumStat type="vald">11073</sumStat>
  <sumStat type="invd">4636</sumStat>
  <sumStat type="min">-2.188</sumStat>
  <sumStat type="max">5.408</sumStat>
  <sumStat type="mean">0.153</sumStat>
  <sumStat type="stdev">0.814</sumStat>
</var>
<var ID="V489" name="stigma_anticipate_std" files="F8" intrvl="contin">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Covid anticipated stigma score, z-scores</labl>
  <sumStat type="vald">11073</sumStat>
  <sumStat type="invd">4636</sumStat>
  <sumStat type="min">-1.424</sumStat>
  <sumStat type="max">4.945</sumStat>
  <sumStat type="mean">0.0311</sumStat>
  <sumStat type="stdev">0.937</sumStat>
</var>
<var ID="V490" name="cumul_covax_bin" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Any other household members vaccinated up to today</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
</var>
<var ID="V491" name="covax_anyneg" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Binary outcome, any negative response</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
</var>
<var ID="V492" name="covax_negative" files="F8" intrvl="discrete">
  <varFormat type="numeric"/>
  <location width="9"/>
  <labl>Binary outcome, definite negative response</labl>
  <sumStat type="vald">15709</sumStat>
  <sumStat type="invd"/>
  <catgry>
    <labl>No</labl>
    <catStat type="vald"/>
  </catgry>
  <catgry>
    <catValu>1</catValu>
    <labl>Yes</labl>
    <catStat type="invd"/>
  </catgry>
</var>
</dataDscr></codeBook>
