Reducing Fatalities from Coronavirus Epidemic

A simple dynamic epidemiological model is used to explore two strategies for "flattening the curve," thus avoiding overwhelming the health care system and so reduce fatalities from coronavirus spread:
• Placing uniform restrictions on social contacts for an entire population.
• Placing higher restrictions on the high-risk fraction of the population and lower restrictions on the low-risk fraction of the population.

SNAPSHOTS

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DETAILS

The model has the form
,
,
,
,
where
= high-risk fraction of the population not infected
= low-risk fraction of the population not infected
= high-risk fraction of the population infected
= low-risk fraction of the population infected
= restriction on social contacts placed on high-risk fraction of population
= rate of infection
= rate of recovery after infection
Overall mortality is computed to be
,
where have been computed based on infection rates from [1] and distribution of age over population from [2].
Basic information on the subject along with additional references can be found at [3]. A nice visualization can also be found at [4].
References
[1] L. T. Vo. "These Charts Break Down Who Is Most at Risk of Dying from the Coronavirus." (Mar 20, 2020) www.buzzfeednews.com/article/lamvo/coronavirus-death-rates-age-charts-us-china.
[2] Central Intelligence Agency. "The World Factbook." (Mar 20, 2020) www.cia.gov/library/publications/the-world-factbook/geos/ch.html.
[4] H. Stevens. "Why Outbreaks like Coronavirus Spread Exponentially, and How to 'Flatten the Curve'." (Mar 20, 2020) www.washingtonpost.com/graphics/2020/world/corona-simulator.
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