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authorhannajankowski <hkj@yorku.ca>2024-05-30 10:57:36 -0400
committerGitHub <noreply@github.com>2024-05-30 10:57:36 -0400
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-<h1>Welcome to the Rnaught web application</h1>
-<p>
- Rnaught is an R package and web application for estimating the
- <a href="https://en.wikipedia.org/wiki/Basic_reproduction_number" target="_blank">basic reproduction number</a>
- of infectious diseases. For information about using this application, view the
- <span class="fw-bold text-primary">Help <span class="glyphicon glyphicon-question-sign"></span></span> tab.
- To learn more about the package, visit the online
- <a href="https://MI2YorkU.github.io/Rnaught" target="_blank">documentation</a> or
- <a href="https://github.com/MI2YorkU/Rnaught" target="_blank">GitHub</a> repository.
- Technical details about the estimators featured in this project can be found in the reference
- <a href="https://doi.org/10.1371/journal.pone.0269306" target="_blank">article</a>.
-</p>
-
-<h4>What is the basic reproduction number?</h4>
-<p>
- The basic reproduction number, denoted <em>R<sub>0</sub></em>, is defined as the expected number of infections caused by a
- single infectious individual when introduced into a totally susceptible population. It assumes that all individuals in a given population are susceptible to the disease,
- and that no preventive measures (such as lockdowns or vaccinations) have been enforced. It is a useful
- indicator of the transmissibility of an infectious disease during the early stages of its spread and detection.
-</p>
-<p>
- If <em>R<sub>0</sub></em> &lt; 1, then the disease will eventually die out. On the other hand, if
- <em>R<sub>0</sub></em> &gt; 1, the disease will spread (the higher the <em>R<sub>0</sub></em>, the faster this will happen). Due to uncertainty of known data about the disease, it is difficult to
- determine <em>R<sub>0</sub></em> precisely.
- Therefore, many estimation methods exist, each based on different assumptions and yielding different estimates. It is the
- responsibility of users to employ the most appropriate estimator (or suite of estimators) given the situation at hand.
-</p>