Table 2.
Scenarios modelled.
| Scenario | Duration | Extent of disruption to: |
|||
|---|---|---|---|---|---|
| Routine primary screening | Surveillance visits | Colposcopy/precancer treatment | Symptomatic detection | ||
| S0 | None | None | None | None | None |
| S1 | 6 months | 100% ↓ | None | None | None |
| S2 | 100% ↓ | 100% ↓ | None | None | |
| S3 | 100% ↓ | 100% ↓ | 100% ↓ | None | |
| S4 | 100% ↓ | 100% ↓ | 100% ↓ | 100% ↓ | |
| S5 | 12 months | 100% ↓ | None | None | None |
| S6 | 100% ↓ | 100% ↓ | None | None | |
| S7 | 100% ↓ | 100% ↓ | 100% ↓ | None | |
| S8 | 100% ↓ | 100% ↓ | 100% ↓ | 100% ↓ | |
Disruptions are assumed to occur across all affected services for the duration, followed by rapid recovery of missed visits when the disruption period ends. The exact timing of the disruption differs between the Australian model and other models due to differences in the time-step used in the models (one year for Australia; smaller in other models). Two models (Australia, USA-Policy1) assume the 12-month disruption occurs over the full year of 2020 (recovery from January 2021); other models assume the 12-month disruption occurs from March 2020 – February 2021 (recovery from March 2021). All models assume the 6-month disruption occurs entirely within 2020. In the 6-month disruption scenarios, recovery is assumed to commence from September 2020 in all models apart from the Australian model, where it is assumed to commence from January 2021.