A simple disease model

A simple disease spread visualization based on R0, CFR, serial interval and the final size relation. Associated Medium post here.

Assumes a completely isolated, small community in which susceptible depletion kicks in, using the final size relation s∞ = S(0)e^[–R0(1–s∞)] [1 2]. Other assumptions include homogeneous contact & transmission rates (whereas better models consider heterogeneous contact & transmission rates, e.g. [1, 2, 3]), that serial interval == generation interval and that no behavior change occurs over the course of the epidemic. If you see any errors or have questions/concerns/comments, please hit me up.

Example (Smallpox)

Sources for parameters

R0

• Various
• SARS (1.77-1.85)
• Seasonal Influenza (1.3)
• Covid-19 (1.4-2.5)
• Covid-19 high (mean 3.28, median 2.79)
• Covid-19 (1.32 with a corresponding SI of 3.96)

Fatality Rate

• Covid-19 high 3.4%
• Covid-19 CFR high (2.3%)
• Covid-19 IFR (1.6%)
• Covid-19 IFR (0.94%)
• Covid-19 IFR low (0.3%–1%)
• Ebola, SARS and MERS CFR (50%, 10%, 34%)
• Seasonal Influenza CFR (0.1%)
• Smallpox CFR (30%)
• Measles CFR (0.2%)
• Mumps CFR (1%)
• Rubella CFR (0.1% - fatalities almost entirely infants & in utero)

Serial Interval

• MERS (13 days)
• Seasonal Influenza (3 days)
• Covid-19 (5-6 days)
• Covid-19 (3.96 with correspond R0 of 1.32)
• Ebola (15.3 days)
• SARS (8.4 days)
• Mumps (20 days)
• Rubella (18 days)
• Smallpox (18 days)
• Measles (12 days)