Reducing Fatalities from Coronavirus Epidemic

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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.


Contributed by: Michael Nikolaou (March 2020)
(University of Houston)
Open content licensed under CC BY-NC-SA



The model has the form






= 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].


[1] L. T. Vo. "These Charts Break Down Who Is Most at Risk of Dying from the Coronavirus." (Mar 20, 2020)

[2] Central Intelligence Agency. "The World Factbook." (Mar 20, 2020)

[3] J. Kantor. "Modeling and Control of a Campus Outbreak of Coronavirus COVID-19." (Mar 20, 2020) 119ZcE_X7Yev5xq3q _CDex3bxQkRY.

[4] H. Stevens. "Why Outbreaks like Coronavirus Spread Exponentially, and How to 'Flatten the Curve'." (Mar 20, 2020)

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