Mathematical models are a useful tool for exploring the potential effects of NPIs against COVID-19.
a Reducing transmission leads to a “flattening” of the epidemic curve, whereby the peak number of simultaneously infected individuals is smaller and the peak occurs later.
b,
c Simple models such as the SIR model can be extended to include features such as asymptomatic infectious individuals (
b) and different contact rates between individuals of different ages (
c).
d When intense interventions are removed, case numbers may begin to increase again. In
a, the numerical solution of the SIR model (system of Eq.s (
1)) is shown for high transmissibility (
R0 = 3, blue line) and low transmissibility (
R0 = 2, red line), starting with
S = 99,999,
I = 1 and
R = 0. In
c, data show the average numbers of daily contacts that an individual in the age group on the
x-axis has with contacts in the age group on the
y-axis, in the UK under normal circumstances [
4]. Ages are binned into 5-year intervals (with individuals and contacts who are over 80 years old included in the 75–80 age group). In
d, the numerical solution of the SIR model (system of Eq.s (
1)) is shown with
R0 = 0.9 for all times
t ≤ 75 days, and
R0 = 1.5 for all times
t > 75 days, starting with
S = 99,000,
I = 1000 and
R = 0. In
a and
d, the infectious period is set to be 1/
μ = 5 days