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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)

Interventions

 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