Table 2.
Time consumption (in seconds) for training and testing near-optimal NCB, SIR, SEIR, SIS, ARIMA, and ETS models for each COVID-19 daily incidence time data taken into account (Argentina - Ar, Brazil - Br, China - Ch, France - Fr, Germany - Ge, India - In, Iran - Ir, Italy - It, Japan - Ja, Korea, South - KS, Spain - Sp, United Kingdom - UK, US).
| model | phase | Ar | Br | Ch | Fr | Ge | In | Ir | It | Ja | KS | Sp | UK | US | Average |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| NCB | training | 3.150 | 2.820 | 3.250 | 3.540 | 2.890 | 3.230 | 3.050 | 2.970 | 2.900 | 3.330 | 2.860 | 2.900 | 2.870 | 3.058 |
| test | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000 | |
| SIR | training | 10.06 | 10.01 | 10.02 | 10.00 | 10.01 | 10.03 | 10.02 | 10.01 | 10.09 | 10.03 | 10.01 | 10.02 | 10.02 | 10.025 |
| test | 0.02 | 0.02 | 0.01 | 0.00 | 0.02 | 0.00 | 0.01 | 0.02 | 0.02 | 0.01 | 0.02 | 0.01 | 0.01 | 0.013 | |
| SEIR | training | 10.04 | 10.01 | 10.02 | 10.01 | 10.00 | 10.02 | 10.00 | 10.00 | 10.01 | 10.00 | 10.01 | 10.00 | 10.02 | 10.011 |
| test | 0.01 | 0.02 | 0.01 | 0.02 | 0.01 | 0.01 | 0.02 | 0.00 | 0.02 | 0.02 | 0.00 | 0.02 | 0.01 | 0.013 | |
| SIS | training | 10.05 | 10.00 | 10.00 | 10.00 | 10.02 | 10.00 | 10.01 | 10.02 | 10.00 | 10.01 | 10.02 | 10.00 | 10.00 | 10.010 |
| test | 0.02 | 0.01 | 0.02 | 0.01 | 0.00 | 0.00 | 0.02 | 0.01 | 0.01 | 0.00 | 0.01 | 0.01 | 0.02 | 0.011 | |
| ARIMA | training | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.03 | 0.01 | 0.00 | 0.02 | 0.02 | 0.02 | 0.02 | 0.02 | 0.018 |
| test | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000 | |
| ETS | training | 0.03 | 0.05 | 0.04 | 0.06 | 0.06 | 0.03 | 0.05 | 0.05 | 0.03 | 0.05 | 0.03 | 0.03 | 0.07 | 0.045 |
| test | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000 |