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Table 1 Model input parameters, assumptions, and references

From: The impact of phased university reopenings on mitigating the spread of COVID-19: a modeling study

Model parameter Input
On-campus population (N) 7500 (assumption)
Time horizon (weeks) 18 weeks
Disease dynamics a
 Mean incubation time, 1/σ 3 days [23]
 Mean asymptomatic infectious time (days), 1/φ 10 days [22]
 Mean symptomatic infection time before detection and isolation (days), 1/γ 3 days (accounting for 2-day pre-symptomatic period and 1-day test turnaround time) [23]
 Isolation time, 1/ρ (days) 10 days [22]
 Proportion of infections that are symptomatic, α 0.4 [18]
Transmission rate, β Dependent on Rt
Baseline infectious rate (%) b 3% [18]
Baseline recovered rate (%) 10% [10, 14, 24]
Mitigation strategies throughout semester (Rt) c
 Highly effective (best case) 1.5 [5]
 Moderately effective (base case) 2.5 [5]
 Ineffective (worst case) 3.5 [5]
 Time-varying Month 0: 4; Month 1: 2.5; Month 2+: 1.25 (assumption)
 Test characteristics
  Sensitivity (%) 90% [5, 25]
  Specificity (%) 100% (assumption)
 Phased re-opening
  Phase 1: Calendar time (months)/sub-population returning to campus 0 months/2500 students (assumption)
  Phase 2: Calendar time (months)/sub-population returning to campus/cumulative population 1 months/2500 students/5000 students (assumption)
  Phase 3: Calendar time (months)/sub-population returning to campus/cumulative population 2 months/2500 students/7500 students (assumption)
  1. a We assume a closed system (i.e., no exogenous infections or deaths)
  2. b Under pre-arrival testing, baseline infections are reduced by 90%
  3. c Under phased reopening, we assume this number is reduced by 20% during the first phase and 10% during the second phase