This study represents the first description of actual 6 COVID-19 elective vascular surgical delays in a regional 7 health system and estimates the recovery period at 8 8 months. These findings underscore the importance of 9 triaging patients by risk of harm due to continued delay 10 as well as consideration of interfacility transfer of cases 11 to hospitals with available capacity. Estimates of surgical delays have been limited to surveys of providers at a national level.
Additionally, the capacity of regional health systems to recover from deferred cases and the 9 distribution of that variability has not been explored. 10 We sought to examine the number of delayed cases in the state of Michigan using real-time and 11 historical data and estimate the recovery trajectory using information from a statewide vascular 12 surgical consortium.
Data Source and Study Population 15 We collected data for all adult patients having undergone elective carotid endarterectomy, 
BMC2 is a longitudinal multicenter statewide registry of vascular surgery and carotid 19 interventions in Michigan which has been described in detail previously. 9,10 In short, the registry 20 is composed of a consortium of 35 hospitals within the state of Michigan that was designed as a and 2) carrying forward the historical mean. 12 Both forecasting methods produced similar 4 predictions. Delayed cases were calculated as the difference between the forecasted value for 5 each month following February 2020 with the actual number of cases completed from the 6 registry data for that month. To estimate time to recovery, we set the maximum monthly capacity 7 of each hospital system in the state as the maximum monthly case volume that individual 8 hospital achieved in the three years prior to the decrease in elective surgical volume in March 9 2020. This procedure was repeated for each hospital within the collaborative. All analyses were 10 performed using R, version 3.5.1. 13
Summary statistics for individual hospitals are reported in Table 1 procedures, defined as the difference between the statewide maximum monthly surgical volume and the statewide mean monthly surgical volume for the period of the study, was found to be 1 81.38 cases. This resulted in an estimated recovery time of 8.62 months.
2 Hospital level capacity estimates revealed significant variability across institutions ( Figure S1 ). 3 There was significant variation in three-month backlog volumes across the hospitals in the 4 collaborative, shown graphically in Figure S2 . 5 To model the effect of optimal interfacility referral of cases to hospitals with excess capacity 6 within the collaborative, we estimated the time to recovery with each hospital only operating on 7 backlogged cases within that hospital and compared this to the time to recovery if backlogged 8 cases were transferred to hospitals with excess capacity. The recovery curves are shown in 9 Figure 3 . With hospitals only completing their own backlogged cases, the recovery would take 10 approximately 8 months, whereas the recovery would be reduced to 3 months if hospitals shared 11 the burden of backlogged cases across the collaborative.
In this study from a statewide collaborative, we found that there was a rapid decrease in elective 14 vascular surgical procedures and that this decreased elective surgical volume has led to a large 15 pool of deferred cases. Our models suggest that if hospital systems worked at the maximum 16 capacity they had achieved for vascular surgical volume in the last 3 years, it would take 8 17 months to complete these delayed cases while also caring for the normal flux of surgical patients.
This recovery period could be dramatically shortened if hospitals within the state were to share 19 the burden of delinquent cases across this 35-hospital collaborative.
Completing backlogged cases in the order in which they were delayed may result in unnecessary 21 harm to patients whose cases were delayed later in the pandemic but that may have more time 22 J o u r n a l P r e -p r o o f sensitive underlying diagnoses or may be higher risk to suffer harm associated with delay. Cases 1 should be prioritized based on each patient's probability of harm rather than strictly the patient's 2 position in the queue.
In the pre-COVID-19 era, interfacility referrals for surgical procedures that were capable of 4 being completed at either hospital were uncommon. Our data suggest that there is substantial for hospitals outside the state, particularly given the dramatic regional variation in COVID cases, 10 considering the interfacility transfer of cases to hospitals outside of the regional health system 11 could be another possible mechanism to improve the time to treatment for patients on the 