China 
Africa 
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Using Data, Computer Models, and Simulations to Predict the Spread of Diseases Like COVID-19
Published in Jay Liebowitz, The Business of Pandemics, 2020
Scott Nestler, Harrison Schramm
We can use this model to explore policies and their impact on the eventual trajectory of the disease. There are, broadly speaking, two things that policymakers can use to mitigate spread—two “levers.” They are: Decrease the rate at which infection spreads among the susceptible population—also known as flattening the curve. Doing this slows the rate of infection, which reduces the number of infected individuals at any given time; but it also has the side effect of lengthening the overall time horizon.Increase the rate at which individuals are recovered. This consists of developing effective treatments, and ideally a vaccine, which would directly move individuals in class S to class R without passing through I.
Epidemiology-Based Models for Information Spread
Published in Michael Muhlmeyer, Shaurya Agarwal, Information Spread in a Social Media Age, 2021
Michael Muhlmeyer, Shaurya Agarwal
Flattening the curve refers to community isolation measures or stay at home orders intended to mitigate the number of disease cases per day to a manageable level so that medical practitioners and medical resources (hospital beds, limited specialized equipment, etc.) do not become overwhelmed. Figure 7.6 shows a SIR curve with both no intervention and the proactive application of mitigation efforts.
Estimation of the doubling time and reproduction number for COVID-19
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2022
Shamim Ahmed, Mohammad Shemanto, Hasin Azhari, Golam Zakaria
The R0 depends on β. By controlling this parameter, the value of R0 can be controlled. A public health strategy viz. flatten the curve was introduced during the COVID-19 (Wiles 2020). The curve being flattened is the epidemic curve, a visual representation of the number of infected people needing health care over time. Flattening the curve means slowing the spread of the epidemic so that the peak number of people requiring care at a time is reduced, and the health care system is not overload. This concept is useful for the decision-makers to evaluate the impact of transmission mitigation strategies and to evaluate whether the different measures have been able to flatten the epidemic curve (Anderson et al. 2020).