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app-PPE-screenshot: "Show a screenshot of the calaculator"
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app-PPE-documentation: |+
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Refer to our <a href="{link_to_docs}">user documentation for instructions on how to use the tool</a>.
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Refer to our <a href="{link_to_docs}">user documentation for instructions on how to use the calculator</a>.
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app-SIR-title: "Susceptible, Infected, and Recovered"
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app-SIR-text: "The number of susceptible, infected, and recovered individuals in the hospital catchment region at any given moment"
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charts-date: "Date"
@@ -22,13 +22,15 @@ en:
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<a id="title" class="penn-medicine-header__title">COVID-19 Hospital Impact Model for Epidemics (CHIME)</a>
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</div>
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presentation-notice: |+
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**Notice**: *There is a high
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degree of uncertainty about the details of COVID-19 infection, transmission, and the effectiveness of social distancing
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measures. Long-term projections made using this simplified model of outbreak progression should be treated with extreme caution.*
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**Notice**: **CHIME is a modified [SIR](https://mathworld.wolfram.com/SIRModel.html) model of outbreak progression that is limited to short term forecasting
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It is only applicable during the period prior to a region’s peak infections, and it accounts only for a single significant social distancing policy.
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Penn Medicine is actively developing [BayesCHIME](https://github.com/pennsignals/chime_sims/blob/master/README.md) to make use of more data and provide probabilistic forecasts beyond peak infections.**
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presentation-developed-by: |+
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This tool was developed by [Predictive Healthcare](http://predictivehealthcare.pennmedicine.org/) at
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Penn Medicine to assist hospitals and public health officials with hospital capacity planning.
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Please read [How to Use CHIME]({docs_url}) to customize inputs for your region.
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The Personal Protective Equipment (PPE) Forecasting Calculator was developed collaboratively by
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the University of Pennsylvania and Penn Medicine.
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presentation-estimated-number-of-infection: |+
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The estimated number of currently infected individuals is **{total_infections:.0f}**. This is based on current inputs for
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Hospitalizations (**{current_hosp}**), Hospitalization rate (**{hosp_rate:.0%}**), Regional population (**{S}**),
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