Simulate the outcome of a pandemic, using your own input parameters. The plugin generates charts and tables for better understanding of results.

CodeRevolution

What Can You Do With This Plugin?
Using this plugin, you can simulate the outcome of a pandemic, using your own input parameters. The plugin generates charts and tables for better understanding of generated results. 
Go ahead and simulate how the SARS-CoV-2 Coronavirus causing the COVID-19 disease (Wuhan China Outbreak or Pandemic) can spread over the entire globe, with this Coronavirus Spreading Prediction Tool. You can use it to test your own scenarios, enter your own parameters for the virus, or use real live data provided by the CDC / WHO to add an outbreak outcome simulation (tables and charts) to your own personal website!
** Quick Links **
<ul>
<li>Join our <a href="https://www.facebook.com/groups/coderevo/" rel="nofollow ugc">Facebook Group</a>, a community of WordPress automation enthusiasts</li>
<li><a href="https://www.buymeacoffee.com/coderevolution" rel="nofollow ugc">Buy me a coffee</a></li>
<li>Subscribe to <a href="https://www.youtube.com/channel/UCVLIksvzyk-D_oEdHab2Lgg" rel="nofollow ugc">CodeRevolution’s YouTube Channel</a> for tutorials, news and updates for my plugins</li>
<li><a href="https://coderevolution.ro/member/a-large-list-of-premium-blogging-and-marketing-courses-that-are-free-during-the-covid-19-pandemic/" rel="nofollow ugc">Free Stuff During The COVID-19 Pandemic</a></li>
</ul>
Embed Tables and Charts Showing Pandemic Progression:
You can embed tables and charts with the prediction of the evolution of the spreading of a global or regional pandemic. – It can also use iframes to automatically embed dashboards from WHO and Johns Hopkins, to track in real time the progress of the outbreak. The goal is to achieve the following: 
COVID-19 Coronavirus – Viral Pandemic Prediction Tools will automatically create prediction tables and charts.
Features included in the free version:
<ul>
<li>Show modeling tables and graphs of possible outcomes of a pandemic</li>
<li>Graph for modeling new infected cases and new deaths for the period of the pandemic</li>
<li>Graph for modeling total infected cases and total deaths for the period of the pandemic</li>
<li>Graph for modeling total population decline, over time</li>
<li>Graph for modeling total death count, over time</li>
<li>Table with detailed data on the ongoing of the pandemic (columns detailing: date, day count, new infected count, total infected count, new death count, total death count, population alive count)</li>
<li>You can set your own pandemic parameters, including: starting population, start date, initial infected count, immune and unkillable elite in bunkers, infection rate, incubation period, mortality rate, mortality complicator, disease burnout rate</li>
<li>Gutenberg blocks available</li>
<li>And many more cool features!</li>
</ul>
Features included in the <a href="//1.envato.market/covid19" title="full version of the plugin" rel="nofollow ugc">full version of the plugin</a>:
<ul>
<li>Embed Official Pandemic Tracking Dashboard from Johns Hopkins Institute</li>
<li>Embed Official Pandemic Tracking Dashboard from WHO</li>
<li>Allow your web site’s visitors to enter their own data to simulate the outcome of pandemics</li>
<li>Pandemic summary charts and tables</li>
<li>Sample past outbreaks data, to use in the plugin (SARS-CoV-2, MERS, SARS, Spanish Flu, Common Flu)</li>
<li>Detailed documentation, with parameter explanations</li>
<li>New updates and features added regularly</li>
<li>Premium support</li>
<li>And many more cool features!</li>
</ul>
Check the full version of the plugin, here: <a href="//1.envato.market/covid19" title="COVID-19 Coronavirus - Viral Pandemic Prediction Tools WordPress Plugin" rel="nofollow ugc">COVID-19 Coronavirus – Viral Pandemic Prediction Tools WordPress Plugin</a>
Parameter Explanations:
Starting Population – The starting population for the outbreak/pandemic. This can be the population of the globe, your country, city or even university. 
Elite in Bunkers and Immune – This is the number of people that will never get sick – because they are naturally immune or they are hiding in bunkers or are fully isolated from the infected population. 
Start Date – This is the date when the first patient is infected. 
Initial Infections – The number of initial infections that occurred on the start date. 
Infection Rate (R0) – The number of additional people that are infected by a single patient that already has the virus (during the incubation period). 
Incubation Period (Days) – The average time from becoming infected to showing thee first symptoms. 
Mortality Rate (Percentage) – How many people die of the virus as a percentage of those who become infected (an average death rate). 
Mortality Complicator (Percentage) – This will increase the ‘Mortality Rate’ where there is a large number of new infected in a short period of time and is based on the increasing likelihood of mortality as more of the health care system becomes overwhelmed (more and more severe and critical cases that need medical help to survive, in a short period of time). 
Virus Burnout Rate (Percentage) – This represents a reduction of the ‘Infection Rate’ over time – it represents the increased quarantine measures, progress with discovering a cure or vaccine and fewer healthy hosts to infect.
Documentation:
Please check the documentation of this plugin, here: <a href="https://coderevolution.ro/docs/covid19-free/" title="CodeRevolution's Documentation Portal" rel="nofollow ugc">CodeRevolution’s Documentation Portal</a>.
Some more info on pandemic spreading and epidemiology:
Public health efforts depend heavily on predicting how diseases such as that caused by the 2019 novel coronavirus, now named COVID-19 by the World Health Organization, spread across the globe. During the early days of a new outbreak, when reliable data are still scarce, researchers turn to mathematical models that can predict where people who could be infected are going and how likely they are to bring the disease with them. These computational methods use known statistical equations that calculate the probability of individuals transmitting the illness. 
How fast a disease spreads is determined by calculating a reproduction number, or R0. The WHO estimates the coronavirus R0 at somewhere between 1.4 and 2.5. WHO also reports that 12-21 percent of the people with the virus became critically ill, and 2-3 percent of those infected have died. 
The R0 refers to the average number of people a sick person will infect. So, if a virus has an R0 of 2, patient zero will likely infect two people, and then those two people will each infect two more people. The cycle repeats. If an RO is greater than 1, the infection will likely continue to spread. If it is below 1, it is unlikely to spread further.
Footnotes:
This plugin was made by <a href="//coderevolution.ro/our-story/" title="Szabi" rel="nofollow ugc">Szabi</a> from CodeRevolution. He sells his premium plugins and scripts on Envato Market. Be sure to check his work <a href="//1.envato.market/coderevolution" title="@CodeRevolution" rel="nofollow ugc">@CodeRevolution</a>. Be sure to check his <a href="https://coderevolution.ro/blog/" title="blog" rel="nofollow ugc">blog</a> and <a href="https://www.youtube.com/channel/UCVLIksvzyk-D_oEdHab2Lgg" title="YouTube channel" rel="nofollow ugc">YouTube channel</a> for updates and news.
<h3>Plugin Requirements</h3>
PHP 5.2 or higher

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