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diff --git a/.github/workflows/compatability_testing.yml b/.github/workflows/compatability_testing.yml
@@ -1,15 +1,15 @@
 name: compatability_testing
 
-on: [push, pull_request]
+on: [workflow_dispatch]
 
 jobs:
   build:
 
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
-        #os: [ubuntu-latest]
+        #os: [ubuntu-latest, macos-latest, windows-latest]
+        os: [ubuntu-latest]
         python-version: ['3.9', '3.10', '3.11', '3.12']
         dependencies: ["latest"]
 

diff --git a/Harris_County/Documentation/Harris_County_2018_bg_config.xlsx b/Harris_County/Documentation/Harris_County_2018_bg_config.xlsx
diff --git a/Harris_County/SVIs/Harris_County_2018_bg_config_svi.csv b/Harris_County/SVIs/Harris_County_2018_bg_config_svi.csv
diff --git a/Harris_County/SVIs/Harris_County_2018_bg_config_svi.gpkg b/Harris_County/SVIs/Harris_County_2018_bg_config_svi.gpkg
diff --git a/Travis_County/Documentation/Travis_County_2013_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2013_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2014_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2014_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2015_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2015_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2016_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2016_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2017_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2017_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2018_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2018_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2019_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2019_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2020_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2020_bg_SVI.xlsx
diff --git a/Travis_County/Documentation/Travis_County_2021_bg_SVI.xlsx b/Travis_County/Documentation/Travis_County_2021_bg_SVI.xlsx
diff --git a/Travis_County/Figures/2013_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2013_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2014_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2014_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2015_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2015_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2016_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2016_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2017_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2017_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2018_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2018_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2019_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2019_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2020_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2020_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/Figures/2021_bg_SVI_FA_SVI_Percentile.png b/Travis_County/Figures/2021_bg_SVI_FA_SVI_Percentile.png
diff --git a/Travis_County/SVIs/Travis_County_2013_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2013_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2013_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2013_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2014_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2014_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2014_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2014_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2015_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2015_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2015_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2015_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2016_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2016_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2016_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2016_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2017_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2017_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2017_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2017_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2018_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2018_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2018_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2018_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2019_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2019_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2019_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2019_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2020_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2020_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2020_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2020_bg_SVI_svi.gpkg
diff --git a/Travis_County/SVIs/Travis_County_2021_bg_SVI_svi.csv b/Travis_County/SVIs/Travis_County_2021_bg_SVI_svi.csv
diff --git a/Travis_County/SVIs/Travis_County_2021_bg_SVI_svi.gpkg b/Travis_County/SVIs/Travis_County_2021_bg_SVI_svi.gpkg
diff --git a/doc/Background/all_refac_.png b/doc/Background/all_refac_.png
diff --git a/doc/Background/final_fac_.png b/doc/Background/final_fac_.png
diff --git a/doc/Background/loading_fac_.png b/doc/Background/loading_fac_.png
diff --git a/doc/Background/sig_comp_.png b/doc/Background/sig_comp_.png
diff --git a/doc/Background/understanding.rst b/doc/Background/understanding.rst
@@ -13,7 +13,7 @@ Significant Components
 ----------------------
 This sheet shows what components are significantly contributing to each factor from the final factor analysis. The number of iterations can be determined based on the name of each factor. For example, in this run *'F2'* means that this went through three rounds of factor analysis (zero-based numbering rules). As can be seen, there are 5 factors in the final index. Information on which variables contribute to which factor is useful in determining "themes" for the factors (e.g., wealth theme, social characteristics theme, etc.). In this example, one could identify the first factor as Social Status, and the second factor as Economic Status. These are for description only and will be unique based on the study area and year being analyzed. They may or may not be easily definable into distinct themes, but do show what variables are correlated within a study area. 
 
-.. figure:: ../Background/sig_comp_.pdf
+.. figure:: ../Background/sig_comp_.png
    :alt: Table of significant components for 2017 Travis County, Texas Block Group SVI estimate
 
 *Table 1: Significant components for 2017 Travis County, Texas Block Group SVI estimate*
@@ -24,7 +24,7 @@ Loading Factors
 ---------------
 Based on the variables within the final index, each has a loading factor associated with it for each factor. This information is critical in determining the weights for each variable for each factor when calculating the final index. For every boundary in the study area and for every factor, the variable is multiplied by the loading factor and summed within each factor. This is how the factor scores are determined. 
 
-.. figure:: ../Background/loading_fac_.pdf
+.. figure:: ../Background/loading_fac_.png
    :alt: Table of loading factors for 2017 Travis County, Texas Block Group SVI estimate
 
 *Table 2: Loading factors for 2017 Travis County, Texas Block Group SVI estimate*
@@ -46,7 +46,7 @@ Final Variances
 ---------------
 An abbreviated version of All Refactor Variances, showing only the final table for the final iteration.
 
-.. figure:: ../Background/final_fac_.pdf
+.. figure:: ../Background/final_fac_.png
    :alt: Table of Final factor analysis variance statistics for 2017 Travis County, Texas Block Group SVI estimate
 
 *Table 4: Final factor analysis variance statistics for 2017 Travis County, Texas Block Group SVI estimate*

diff --git a/doc/Examples/SVInsight_example_SETx.ipynb b/doc/Examples/SVInsight_example_SETx.ipynb
diff --git a/doc/Examples/examples.rst b/doc/Examples/examples.rst
@@ -1,4 +1,13 @@
 Examples
 ========
 
-Examples will go here.
+Bellow you will find a Jupyter Notebook that computes an SVI for the Southeast Texas region. More example scripts can be found on the `GitHub page in the Examples folder <https://github.com/mdp0023/SVInsight/tree/main/examples>`_.
+
+
+
+Example Notebooks
+#################
+.. toctree::
+   :maxdepth: 2
+
+   SVInsight_example_SETx.ipynb
diff --git a/doc/Getting_Started/quickstart.rst b/doc/Getting_Started/quickstart.rst
@@ -10,7 +10,7 @@ First we load the SVInsight package, set the necessary variables, and create the
 
 .. doctest::
 
-    >>> from SVInsight import SVInsight as svi
+    >>> from svinsight import SVInsight as svi
     >>> project_name = 'YOUR PROJECT NAME HERE'
     >>> file_path = "YOUR PARENT FOLDER HERE"
     >>> api_key = 'YOUR CENSUS API KEY HERE'

diff --git a/doc/User_Guide/userguide.rst b/doc/User_Guide/userguide.rst
@@ -29,7 +29,7 @@ The first step to the project is importing :obj:`SVInsight` and setting the proj
 
 .. doctest::
 
-   >>> from SVInsight import SVInsight as svi 
+   >>> from svinsight import SVInsight as svi 
    >>> project_name = 'Travis_County'
    >>> file_path = "/User/Documents"
    >>> api_key = os.environ.get('API_KEY')

diff --git a/doc/_build/doctrees/Acknowledgements/acknowledgements.doctree b/doc/_build/doctrees/Acknowledgements/acknowledgements.doctree
diff --git a/doc/_build/doctrees/Background/background.doctree b/doc/_build/doctrees/Background/background.doctree
diff --git a/doc/_build/doctrees/Background/paper.doctree b/doc/_build/doctrees/Background/paper.doctree
diff --git a/doc/_build/doctrees/Background/understanding.doctree b/doc/_build/doctrees/Background/understanding.doctree
diff --git a/doc/_build/doctrees/Contributions/contributions.doctree b/doc/_build/doctrees/Contributions/contributions.doctree
diff --git a/doc/_build/doctrees/Examples/SVInsight_example_SETx.doctree b/doc/_build/doctrees/Examples/SVInsight_example_SETx.doctree
diff --git a/doc/_build/doctrees/Examples/examples.doctree b/doc/_build/doctrees/Examples/examples.doctree
diff --git a/doc/_build/doctrees/Getting_Started/install.doctree b/doc/_build/doctrees/Getting_Started/install.doctree
diff --git a/doc/_build/doctrees/Getting_Started/quickstart.doctree b/doc/_build/doctrees/Getting_Started/quickstart.doctree
diff --git a/doc/_build/doctrees/User_Guide/userguide.doctree b/doc/_build/doctrees/User_Guide/userguide.doctree
diff --git a/doc/_build/doctrees/apiref/apiref.doctree b/doc/_build/doctrees/apiref/apiref.doctree
diff --git a/doc/_build/doctrees/apiref/license.doctree b/doc/_build/doctrees/apiref/license.doctree
diff --git a/doc/_build/doctrees/environment.pickle b/doc/_build/doctrees/environment.pickle
diff --git a/doc/_build/doctrees/index.doctree b/doc/_build/doctrees/index.doctree
diff --git a/doc/_build/doctrees/nbsphinx/Examples/SVInsight_example_SETx.ipynb b/doc/_build/doctrees/nbsphinx/Examples/SVInsight_example_SETx.ipynb
diff --git a/doc/_build/doctrees/nbsphinx/Examples_SVInsight_example_SETx_6_0.png b/doc/_build/doctrees/nbsphinx/Examples_SVInsight_example_SETx_6_0.png
diff --git a/doc/_build/html/.buildinfo b/doc/_build/html/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 6b2bd8b92764ff171da02403603cbf26
+config: ff7d8f827686d46c87724026e85529e0
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/doc/_build/html/Acknowledgements/acknowledgements.html b/doc/_build/html/Acknowledgements/acknowledgements.html
@@ -5,7 +5,7 @@
     <meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 <link rel="index" title="Index" href="../genindex.html" /><link rel="search" title="Search" href="../search.html" /><link rel="prev" title="Issues, Questions, and Contributions" href="../Contributions/contributions.html" />
 
-    <!-- Generated with Sphinx 7.2.6 and Furo 2024.01.29 -->
+    <!-- Generated with Sphinx 7.3.7 and Furo 2024.01.29 -->
         <title>Acknowledgements - SVInsight documentation</title>
       <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=362ab14a" />
     <link rel="stylesheet" type="text/css" href="../_static/styles/furo.css?v=135e06be" />
@@ -171,7 +171,10 @@
 <li class="toctree-l1"><a class="reference internal" href="../apiref/license.html">License</a></li>
 </ul>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../Examples/examples.html">Examples</a></li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../Examples/examples.html">Examples</a><input class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" role="switch" type="checkbox"/><label for="toctree-checkbox-1"><div class="visually-hidden">Toggle navigation of Examples</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../Examples/SVInsight_example_SETx.html">SVInsight Example: Southeast Texas</a></li>
+</ul>
+</li>
 </ul>
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../Contributions/contributions.html">Issues, Questions, and Contributions</a></li>
@@ -213,7 +216,7 @@
         </div>
         <article role="main">
           <section id="acknowledgements">
-<h1>Acknowledgements<a class="headerlink" href="#acknowledgements" title="Link to this heading">#</a></h1>
+<h1>Acknowledgements<a class="headerlink" href="#acknowledgements" title="Link to this heading">¶</a></h1>
 <p>We would like to thank the many collaborators who have helped us developing our methodologies. This work has been incorporated into numerous projects that have been supported by the following grants:</p>
 <ul class="simple">
 <li><p>National Science Foundation Graduate Research Fellowship (grant no. DGE-1610403)</p></li>
@@ -265,8 +268,9 @@ <h1>Acknowledgements<a class="headerlink" href="#acknowledgements" title="Link t
     </aside>
   </div>
 </div><script src="../_static/documentation_options.js?v=5929fcd5"></script>
-    <script src="../_static/doctools.js?v=888ff710"></script>
+    <script src="../_static/doctools.js?v=9a2dae69"></script>
     <script src="../_static/sphinx_highlight.js?v=dc90522c"></script>
     <script src="../_static/scripts/furo.js?v=32e29ea5"></script>
+    <script crossorigin="anonymous" integrity="sha256-Ae2Vz/4ePdIu6ZyI/5ZGsYnb+m0JlOmKPjt6XZ9JJkA=" src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.4/require.min.js"></script>
     </body>
 </html>
diff --git a/doc/_build/html/Background/background.html b/doc/_build/html/Background/background.html
@@ -5,7 +5,7 @@
     <meta name="color-scheme" content="light dark"><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
 <link rel="index" title="Index" href="../genindex.html" /><link rel="search" title="Search" href="../search.html" /><link rel="next" title="Understanding Iterative Factor Analysis Results" href="understanding.html" /><link rel="prev" title="Getting Started" href="../Getting_Started/quickstart.html" />
 
-    <!-- Generated with Sphinx 7.2.6 and Furo 2024.01.29 -->
+    <!-- Generated with Sphinx 7.3.7 and Furo 2024.01.29 -->
         <title>Background - SVInsight documentation</title>
       <link rel="stylesheet" type="text/css" href="../_static/pygments.css?v=362ab14a" />
     <link rel="stylesheet" type="text/css" href="../_static/styles/furo.css?v=135e06be" />
@@ -171,7 +171,10 @@
 <li class="toctree-l1"><a class="reference internal" href="../apiref/license.html">License</a></li>
 </ul>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../Examples/examples.html">Examples</a></li>
+<li class="toctree-l1 has-children"><a class="reference internal" href="../Examples/examples.html">Examples</a><input class="toctree-checkbox" id="toctree-checkbox-1" name="toctree-checkbox-1" role="switch" type="checkbox"/><label for="toctree-checkbox-1"><div class="visually-hidden">Toggle navigation of Examples</div><i class="icon"><svg><use href="#svg-arrow-right"></use></svg></i></label><ul>
+<li class="toctree-l2"><a class="reference internal" href="../Examples/SVInsight_example_SETx.html">SVInsight Example: Southeast Texas</a></li>
+</ul>
+</li>
 </ul>
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../Contributions/contributions.html">Issues, Questions, and Contributions</a></li>
@@ -213,21 +216,21 @@
         </div>
         <article role="main">
           <section id="background">
-<h1>Background<a class="headerlink" href="#background" title="Link to this heading">#</a></h1>
+<h1>Background<a class="headerlink" href="#background" title="Link to this heading">¶</a></h1>
 <section id="motivation">
-<h2>Motivation<a class="headerlink" href="#motivation" title="Link to this heading">#</a></h2>
+<h2>Motivation<a class="headerlink" href="#motivation" title="Link to this heading">¶</a></h2>
 <p>SVInsight was developed to provide an open-source tool for creating social vulnerability indices or SVIs based on user defined study areas and input variables. SVInsight uses two methodologies to create indices based on existing scholarly research: (1) a factor analysis method and (2) a rank method. This tool’s purpose is to provide researchers with the ability to quickly create exploratory estimates of vulnerability based on existing and known relationships between socio-demographic variables and a community’s sensitivity (a proxy for vulnerability).</p>
 <p>While SVInsight is capable of rapidly producing tailor made estimates of relative vulnerability of a given region for researchers and/or practitioners, it does not replace the in-depth investigation required to definitively define what makes someone more or less vulnerable. Indices created with SVInsight can be used as a starting point for understanding the complex relationship between socio-demographic variables and community characteristics including vulnerability, sensitivity, and adaptive capacity by highlighting prominent geographic disparities. It is further important to note that vulnerability estimates are relative, and calculated scores should be taken in the context of the study area being examined.</p>
 <p>This package was specifically written in conjunction with past and ongoing projects at the University of Texas at Austin <a class="footnote-reference brackets" href="#id8" id="id1" role="doc-noteref"><span class="fn-bracket">[</span>2<span class="fn-bracket">]</span></a> <a class="footnote-reference brackets" href="#id9" id="id2" role="doc-noteref"><span class="fn-bracket">[</span>3<span class="fn-bracket">]</span></a> <a class="footnote-reference brackets" href="#id10" id="id3" role="doc-noteref"><span class="fn-bracket">[</span>4<span class="fn-bracket">]</span></a>. More detailed information regarding funding sources can be found in the <a class="reference internal" href="../Acknowledgements/acknowledgements.html"><span class="doc">Acknowledgements section</span></a>.</p>
 </section>
 <section id="methodology">
-<h2>Methodology<a class="headerlink" href="#methodology" title="Link to this heading">#</a></h2>
+<h2>Methodology<a class="headerlink" href="#methodology" title="Link to this heading">¶</a></h2>
 <section id="data-source">
-<h3>Data Source<a class="headerlink" href="#data-source" title="Link to this heading">#</a></h3>
+<h3>Data Source<a class="headerlink" href="#data-source" title="Link to this heading">¶</a></h3>
 <p>All data comes from the American Community Survey 5-Year Estimates because they contain data at the Census block group and tract level. More information on data quality can be found on their <a class="reference external" href="https://www.census.gov/data/developers/data-sets/acs-5year.html">website</a>.</p>
 </section>
 <section id="iterative-factor-analysis">
-<h3>Iterative Factor Analysis<a class="headerlink" href="#iterative-factor-analysis" title="Link to this heading">#</a></h3>
+<h3>Iterative Factor Analysis<a class="headerlink" href="#iterative-factor-analysis" title="Link to this heading">¶</a></h3>
 <p>This methodology is heavily influenced by the original SoVI® <a class="footnote-reference brackets" href="#id7" id="id4" role="doc-noteref"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></a> developed by Dr. Susan Cutter. By utilizing a data reduction methodology, a large subset of American Community Survey 5-Year Estimate variables can be dimensionally reduced and combined into a single index. Both principal component analyses and factor analyses are data reduction techniques that have been utilized to create vulnerability indices. A principal component analysis (PCA) reduces data by creating one or more index variables, or ‘components,’ by using a linear combination (i.e., a weighted average) from a larger set of measured variables. The purpose of a PCA is to determine the optimal number of components, the optimal choice of measured variables for each component, and the optimal weights. A factor analysis (FA) is a model of latent variables. A ‘latent variable’ cannot be directly measured with a single variable. A common example used to describe this is we cannot directly measure something like social anxiety, but we can measure whether someone has a high or low social anxiety based on a set of questions like “I am uncomfortable in large groups” or “ I get nervous talking to strangers.” We utilize a factor analysis approach because it is the data reduction methodology most often associated with creating composite indices, which is our end goal.</p>
 <p>The follow are the steps in the iterative factor analysis approach:</p>
 <ol class="arabic simple">
@@ -299,12 +302,12 @@ <h3>Iterative Factor Analysis<a class="headerlink" href="#iterative-factor-analy
 <p>The purpose of the factor analysis and composite score index in the scope of social vulnerability is to determine which variables are most distinguishable across the study area. The variables with the highest variability are likely to influence the index the most and therefore they must be taken into context of the study area. For example, in Austin, TX a variable that is highly variant across the city is the percent of population that identifies as Hispanic. If this trait contributes to social vulnerability, then our index is working properly to identify areas of higher vulnerability. However, if we discovered that this trait does not contribute to social vulnerability, we cannot include it in this workflow because we are unintentionally weighting the index incorrectly. That is why it is <em>imperative that indices are developed through collaborations with local experts</em> to identify which variables are likely contributing to vulnerability.</p>
 </section>
 <section id="rank-method">
-<h3>Rank Method<a class="headerlink" href="#rank-method" title="Link to this heading">#</a></h3>
+<h3>Rank Method<a class="headerlink" href="#rank-method" title="Link to this heading">¶</a></h3>
 <p>Another commonly employed method to estimate social vulnerability is a ranking method, which was popularized by the <a class="reference external" href="https://www.atsdr.cdc.gov/placeandhealth/svi/index.html">Center for Disease Control’s Social Vulnerability Index</a> <a class="footnote-reference brackets" href="#id11" id="id5" role="doc-noteref"><span class="fn-bracket">[</span>5<span class="fn-bracket">]</span></a>. This method is a more simplified way to produce an index for a given area. Each variable of interest is sorted from high to low and ranked. For each location within the study area, the ranks are summed so that locations with a higher overall rank have a greater vulnerability score. In our method, the final summed ranks are also minmax scaled so that the most vulnerable block group has a composite index of 1 and the least as a composite index of 0.</p>
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 </section>
 <section id="variables">
-<span id="id6"></span><h2>Variables<a class="headerlink" href="#variables" title="Link to this heading">#</a></h2>
+<span id="id6"></span><h2>Variables<a class="headerlink" href="#variables" title="Link to this heading">¶</a></h2>
 <p>SVInsight comes with a standard set of 27 variables which come from the original principal component analysis method, SoVI®. We omit two variables from the original list of 29 due to data availability issues for all of the years and geographic boundaries of interest (the percentage of the population living in nursing facilities, and the number of hospitals per capita). It is important to note that the CDC SVI uses a list of 16 variables that are similar to those from the SoVI® method. Determining which or how many variables to use depends completely on the study area and objectives of the researcher/practitioner and can greatly influence the estimates. Special consideration must be taken to determine the most appropriate set of variables to use.</p>
 <p>The variables, there definitions, and the American Community Survey 5-Year Estimate sources can be found below:</p>
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-<h2>References<a class="headerlink" href="#references" title="Link to this heading">#</a></h2>
+<h2>References<a class="headerlink" href="#references" title="Link to this heading">¶</a></h2>
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